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Sample records for adaptive signal control

  1. Kalman filtering to suppress spurious signals in Adaptive Optics control

    SciTech Connect

    Poyneer, L; Veran, J P

    2010-03-29

    In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.

  2. Adaptive control of human action: the role of outcome representations and reward signals

    PubMed Central

    Marien, Hans; Aarts, Henk; Custers, Ruud

    2013-01-01

    The present paper aims to advance the understanding of the control of human behavior by integrating two lines of literature that so far have led separate lives. First, one line of literature is concerned with the ideomotor principle of human behavior, according to which actions are represented in terms of their outcomes. The second line of literature mainly considers the role of reward signals in adaptive control. Here, we offer a combined perspective on how outcome representations and reward signals work together to modulate adaptive control processes. We propose that reward signals signify the value of outcome representations and facilitate the recruitment of control resources in situations where behavior needs to be maintained or adapted to attain the represented outcome. We discuss recent research demonstrating how adaptive control of goal-directed behavior may emerge when outcome representations are co-activated with positive reward signals. PMID:24058352

  3. Model reference adaptive control, estimation and identification using only input and output signals

    NASA Technical Reports Server (NTRS)

    Carroll, R. L.; Monopoli, R. V.

    1975-01-01

    Significant recent advances in the application of stability theory to the adaptive control and identification of systems, and adaptive state estimation, are considered. Emphasis is on those methods which utilize only input and output measurements of the system, and do not require derivatives of the output signal.

  4. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    NASA Astrophysics Data System (ADS)

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-03-01

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

  5. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    PubMed Central

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-01-01

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

  6. Impact of adaptive signal control on major and minor approach delay

    SciTech Connect

    Wolshon, B.; Taylor, W.C.

    1999-01-01

    One of the primary difficulties in completing evaluations of real-time adaptive traffic signal systems has been the lack of effective modeling tools to perform controlled and repeatable analytical experiments. Recently, a method to analyze the delay characteristics of an existing real-time adaptive traffic signal control system has been developed. The procedure has been used to evaluate the performance of the Sydney Coordinated Adaptive Traffic System (SCATS) in South Lyon, Michigan. The objective of this study was to more closely examine the relationship of major and minor street delay under the SCATS and fixed-time forms of signal control. The effect on left turn delay at critical locations was also compared to the delay change in the through traffic. The comparisons showed that SCATS control resulted in significant delay reductions to left turn traffic compared to the through movements. The improvement was especially pronounced at the major street approaches. To further address the delay effect of SCATS control in South Lyon, the relationships between volume, delay, and green time of the various traffic moments were also compared. These comparisons showed that SCATS tended to allocate more green time to left turn traffic when compared to the fixed-time system.

  7. Adaptive Signal Processing Testbed

    NASA Astrophysics Data System (ADS)

    Parliament, Hugh A.

    1991-09-01

    The design and implementation of a system for the acquisition, processing, and analysis of signal data is described. The initial application for the system is the development and analysis of algorithms for excision of interfering tones from direct sequence spread spectrum communication systems. The system is called the Adaptive Signal Processing Testbed (ASPT) and is an integrated hardware and software system built around the TMS320C30 chip. The hardware consists of a radio frequency data source, digital receiver, and an adaptive signal processor implemented on a Sun workstation. The software components of the ASPT consists of a number of packages including the Sun driver package; UNIX programs that support software development on the TMS320C30 boards; UNIX programs that provide the control, user interaction, and display capabilities for the data acquisition, processing, and analysis components of the ASPT; and programs that perform the ASPT functions including data acquisition, despreading, and adaptive filtering. The performance of the ASPT system is evaluated by comparing actual data rates against their desired values. A number of system limitations are identified and recommendations are made for improvements.

  8. Adaptive neuro-fuzzy logic analysis based on myoelectric signals for multifunction prosthesis control.

    PubMed

    Favieiro, Gabriela W; Balbinot, Alexandre

    2011-01-01

    The myoelectric signal is a sign of control of the human body that contains the information of the user's intent to contract a muscle and, therefore, make a move. Studies shows that the Amputees are able to generate standardized myoelectric signals repeatedly before of the intention to perform a certain movement. This paper presents a study that investigates the use of forearm surface electromyography (sEMG) signals for classification of five distinguish movements of the arm using just three pairs of surface electrodes located in strategic places. The classification is done by an adaptive neuro-fuzzy inference system (ANFIS) to process signal features to recognize performed movements. The average accuracy reached for the classification of five motion classes was 86-98% for three subjects. PMID:22256169

  9. Use of Frontal Lobe Hemodynamics as Reinforcement Signals to an Adaptive Controller

    PubMed Central

    DiStasio, Marcello M.; Francis, Joseph T.

    2013-01-01

    Decision-making ability in the frontal lobe (among other brain structures) relies on the assignment of value to states of the animal and its environment. Then higher valued states can be pursued and lower (or negative) valued states avoided. The same principle forms the basis for computational reinforcement learning controllers, which have been fruitfully applied both as models of value estimation in the brain, and as artificial controllers in their own right. This work shows how state desirability signals decoded from frontal lobe hemodynamics, as measured with near-infrared spectroscopy (NIRS), can be applied as reinforcers to an adaptable artificial learning agent in order to guide its acquisition of skills. A set of experiments carried out on an alert macaque demonstrate that both oxy- and deoxyhemoglobin concentrations in the frontal lobe show differences in response to both primarily and secondarily desirable (versus undesirable) stimuli. This difference allows a NIRS signal classifier to serve successfully as a reinforcer for an adaptive controller performing a virtual tool-retrieval task. The agent's adaptability allows its performance to exceed the limits of the NIRS classifier decoding accuracy. We also show that decoding state desirabilities is more accurate when using relative concentrations of both oxyhemoglobin and deoxyhemoglobin, rather than either species alone. PMID:23894500

  10. Current Tracking Control of Voltage Source PWM Inverters Using Adaptive Digital Signal Processing

    NASA Astrophysics Data System (ADS)

    Fukuda, Shoji; Furukawa, Yuya

    An active filter (AF) is required to have a high control capability of tracking a time-varying current reference. However, a steady-state current error always exists if a conventional proportional and integral (PI) regulator is used because the current reference varies in time. This paper proposes the application of adaptive digital signal processing (ADSP) to the current control of voltage source PWM inverters. ADSP does not require any additional hardware. It can automatically minimize the mean square-error. Since the processing time available by a computer is limited, ADSP cannot eliminate higher order harmonics but can eliminate lower order harmonics such as 5th to 17th. Experimental results demonstrate that ADSP is useful for improving the reference tracking performance of voltage source inverters.

  11. Adaptive control for accelerators

    DOEpatents

    Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

    1991-01-01

    An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.

  12. Adaptive sequential controller

    DOEpatents

    El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso

    1994-01-01

    An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

  13. Cis and trans RET signaling control the survival and central projection growth of rapidly adapting mechanoreceptors.

    PubMed

    Fleming, Michael S; Vysochan, Anna; Paixão, Sόnia; Niu, Jingwen; Klein, Rüdiger; Savitt, Joseph M; Luo, Wenqin

    2015-04-02

    RET can be activated in cis or trans by its co-receptors and ligands in vitro, but the physiological roles of trans signaling are unclear. Rapidly adapting (RA) mechanoreceptors in dorsal root ganglia (DRGs) express Ret and the co-receptor Gfrα2 and depend on Ret for survival and central projection growth. Here, we show that Ret and Gfrα2 null mice display comparable early central projection deficits, but Gfrα2 null RA mechanoreceptors recover later. Loss of Gfrα1, the co-receptor implicated in activating RET in trans, causes no significant central projection or cell survival deficit, but Gfrα1;Gfrα2 double nulls phenocopy Ret nulls. Finally, we demonstrate that GFRα1 produced by neighboring DRG neurons activates RET in RA mechanoreceptors. Taken together, our results suggest that trans and cis RET signaling could function in the same developmental process and that the availability of both forms of activation likely enhances but not diversifies outcomes of RET signaling.

  14. Cis and trans RET signaling control the survival and central projection growth of rapidly adapting mechanoreceptors

    PubMed Central

    Fleming, Michael S; Vysochan, Anna; Paixão, Sόnia; Niu, Jingwen; Klein, Rüdiger; Savitt, Joseph M; Luo, Wenqin

    2015-01-01

    RET can be activated in cis or trans by its co-receptors and ligands in vitro, but the physiological roles of trans signaling are unclear. Rapidly adapting (RA) mechanoreceptors in dorsal root ganglia (DRGs) express Ret and the co-receptor Gfrα2 and depend on Ret for survival and central projection growth. Here, we show that Ret and Gfrα2 null mice display comparable early central projection deficits, but Gfrα2 null RA mechanoreceptors recover later. Loss of Gfrα1, the co-receptor implicated in activating RET in trans, causes no significant central projection or cell survival deficit, but Gfrα1;Gfrα2 double nulls phenocopy Ret nulls. Finally, we demonstrate that GFRα1 produced by neighboring DRG neurons activates RET in RA mechanoreceptors. Taken together, our results suggest that trans and cis RET signaling could function in the same developmental process and that the availability of both forms of activation likely enhances but not diversifies outcomes of RET signaling. DOI: http://dx.doi.org/10.7554/eLife.06828.001 PMID:25838128

  15. Control of metabolic adaptation to fasting by dILP6-induced insulin signaling in Drosophila oenocytes.

    PubMed

    Chatterjee, Debamita; Katewa, Subhash D; Qi, Yanyan; Jackson, Susan A; Kapahi, Pankaj; Jasper, Heinrich

    2014-12-16

    Metabolic adaptation to changing dietary conditions is critical to maintain homeostasis of the internal milieu. In metazoans, this adaptation is achieved by a combination of tissue-autonomous metabolic adjustments and endocrine signals that coordinate the mobilization, turnover, and storage of nutrients across tissues. To understand metabolic adaptation comprehensively, detailed insight into these tissue interactions is necessary. Here we characterize the tissue-specific response to fasting in adult flies and identify an endocrine interaction between the fat body and liver-like oenocytes that regulates the mobilization of lipid stores. Using tissue-specific expression profiling, we confirm that oenocytes in adult flies play a central role in the metabolic adaptation to fasting. Furthermore, we find that fat body-derived Drosophila insulin-like peptide 6 (dILP6) induces lipid uptake in oenocytes, promoting lipid turnover during fasting and increasing starvation tolerance of the animal. Selective activation of insulin/IGF signaling in oenocytes by a fat body-derived peptide represents a previously unidentified regulatory principle in the control of metabolic adaptation and starvation tolerance. PMID:25472843

  16. Control of metabolic adaptation to fasting by dILP6-induced insulin signaling in Drosophila oenocytes.

    PubMed

    Chatterjee, Debamita; Katewa, Subhash D; Qi, Yanyan; Jackson, Susan A; Kapahi, Pankaj; Jasper, Heinrich

    2014-12-16

    Metabolic adaptation to changing dietary conditions is critical to maintain homeostasis of the internal milieu. In metazoans, this adaptation is achieved by a combination of tissue-autonomous metabolic adjustments and endocrine signals that coordinate the mobilization, turnover, and storage of nutrients across tissues. To understand metabolic adaptation comprehensively, detailed insight into these tissue interactions is necessary. Here we characterize the tissue-specific response to fasting in adult flies and identify an endocrine interaction between the fat body and liver-like oenocytes that regulates the mobilization of lipid stores. Using tissue-specific expression profiling, we confirm that oenocytes in adult flies play a central role in the metabolic adaptation to fasting. Furthermore, we find that fat body-derived Drosophila insulin-like peptide 6 (dILP6) induces lipid uptake in oenocytes, promoting lipid turnover during fasting and increasing starvation tolerance of the animal. Selective activation of insulin/IGF signaling in oenocytes by a fat body-derived peptide represents a previously unidentified regulatory principle in the control of metabolic adaptation and starvation tolerance.

  17. A muscle-liver-fat signalling axis is essential for central control of adaptive adipose remodelling

    PubMed Central

    Shimizu, Noriaki; Maruyama, Takako; Yoshikawa, Noritada; Matsumiya, Ryo; Ma, Yanxia; Ito, Naoki; Tasaka, Yuki; Kuribara-Souta, Akiko; Miyata, Keishi; Oike, Yuichi; Berger, Stefan; Schütz, Günther; Takeda, Shin’ichi; Tanaka, Hirotoshi

    2015-01-01

    Skeletal muscle has a pleiotropic role in organismal energy metabolism, for example, by storing protein as an energy source, or by excreting endocrine hormones. Muscle proteolysis is tightly controlled by the hypothalamus-pituitary-adrenal signalling axis via a glucocorticoid-driven transcriptional programme. Here we unravel the physiological significance of this catabolic process using skeletal muscle-specific glucocorticoid receptor (GR) knockout (GRmKO) mice. These mice have increased muscle mass but smaller adipose tissues. Metabolically, GRmKO mice show a drastic shift of energy utilization and storage in muscle, liver and adipose tissues. We demonstrate that the resulting depletion of plasma alanine serves as a cue to increase plasma levels of fibroblast growth factor 21 (FGF21) and activates liver-fat communication, leading to the activation of lipolytic genes in adipose tissues. We propose that this skeletal muscle-liver-fat signalling axis may serve as a target for the development of therapies against various metabolic diseases, including obesity. PMID:25827749

  18. Adaptive neuro-fuzzy inference system for classification of background EEG signals from ESES patients and controls.

    PubMed

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    Background electroencephalography (EEG), recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES) syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3-9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE) and sample entropy (SampEn) in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS) classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved. PMID:24790547

  19. Adaptive Neuro-Fuzzy Inference System for Classification of Background EEG Signals from ESES Patients and Controls

    PubMed Central

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    Background electroencephalography (EEG), recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES) syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3–9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE) and sample entropy (SampEn) in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS) classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved. PMID:24790547

  20. Adaptive filtering in biological signal processing.

    PubMed

    Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

    1990-01-01

    The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

  1. Method For Model-Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1990-01-01

    Relatively simple method of model-reference adaptive control (MRAC) developed from two prior classes of MRAC techniques: signal-synthesis method and parameter-adaption method. Incorporated into unified theory, which yields more general adaptation scheme.

  2. Adaptive control of robotic manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1987-01-01

    The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

  3. Adaptive nonlinear flight control

    NASA Astrophysics Data System (ADS)

    Rysdyk, Rolf Theoduor

    1998-08-01

    Research under supervision of Dr. Calise and Dr. Prasad at the Georgia Institute of Technology, School of Aerospace Engineering. has demonstrated the applicability of an adaptive controller architecture. The architecture successfully combines model inversion control with adaptive neural network (NN) compensation to cancel the inversion error. The tiltrotor aircraft provides a specifically interesting control design challenge. The tiltrotor aircraft is capable of converting from stable responsive fixed wing flight to unstable sluggish hover in helicopter configuration. It is desirable to provide the pilot with consistency in handling qualities through a conversion from fixed wing flight to hover. The linear model inversion architecture was adapted by providing frequency separation in the command filter and the error-dynamics, while not exiting the actuator modes. This design of the architecture provides for a model following setup with guaranteed performance. This in turn allowed for convenient implementation of guaranteed handling qualities. A rigorous proof of boundedness is presented making use of compact sets and the LaSalle-Yoshizawa theorem. The analysis allows for the addition of the e-modification which guarantees boundedness of the NN weights in the absence of persistent excitation. The controller is demonstrated on the Generic Tiltrotor Simulator of Bell-Textron and NASA Ames R.C. The model inversion implementation is robustified with respect to unmodeled input dynamics, by adding dynamic nonlinear damping. A proof of boundedness of signals in the system is included. The effectiveness of the robustification is also demonstrated on the XV-15 tiltrotor. The SHL Perceptron NN provides a more powerful application, based on the universal approximation property of this type of NN. The SHL NN based architecture is also robustified with the dynamic nonlinear damping. A proof of boundedness extends the SHL NN augmentation with robustness to unmodeled actuator

  4. Decentralized adaptive control

    NASA Technical Reports Server (NTRS)

    Oh, B. J.; Jamshidi, M.; Seraji, H.

    1988-01-01

    A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

  5. Adaptive Control For Flexible Structures

    NASA Technical Reports Server (NTRS)

    Bayard, David S.; Ih, Che-Hang Charles; Wang, Shyh Jong

    1988-01-01

    Paper discusses ways to cope with measurement noise in adaptive control system for large, flexible structure in outer space. System generates control signals for torque and thrust actuators to turn all or parts of structure to desired orientations while suppressing torsional and other vibrations. Main result of paper is general theory for introduction of filters to suppress measurement noise while preserving stability.

  6. Simple method for model reference adaptive control

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1989-01-01

    A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.

  7. Effects of incomplete adaptation and disturbance in adaptive control.

    NASA Technical Reports Server (NTRS)

    Lindorff, D. P.

    1972-01-01

    In this paper consideration is given to the effects of disturbance and incomplete parameter adaptation on the performance of adaptive control systems in which Liapunov theory is used in deriving the control law. A design equation for the bounded error is derived. It is further shown that parameters in the adaptive controller may not converge in the presence of disturbance unless the input signal has a rich enough frequency constant. Design examples are presented.

  8. Study Of Adaptive-Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Satorius, Edgar H.; Griffiths, Lloyd

    1990-01-01

    Report describes study of adaptive signal-processing techniques for suppression of mutual satellite interference in mobile (on ground)/satellite communication system. Presents analyses and numerical simulations of performances of two approaches to signal processing for suppression of interference. One approach, known as "adaptive side lobe canceling", second called "adaptive temporal processing".

  9. A Novel Approach for Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Chen, Ya-Chin; Juang, Jer-Nan

    1998-01-01

    Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

  10. Adaptive Cruise Control (ACC)

    NASA Astrophysics Data System (ADS)

    Reif, Konrad

    Die adaptive Fahrgeschwindigkeitsregelung (ACC, Adaptive Cruise Control) ist eine Weiterentwicklung der konventionellen Fahrgeschwindigkeitsregelung, die eine konstante Fahrgeschwindigkeit einstellt. ACC überwacht mittels eines Radarsensors den Bereich vor dem Fahrzeug und passt die Geschwindigkeit den Gegebenheiten an. ACC reagiert auf langsamer vorausfahrende oder einscherende Fahrzeuge mit einer Reduzierung der Geschwindigkeit, sodass der vorgeschriebene Mindestabstand zum vorausfahrenden Fahrzeug nicht unterschritten wird. Hierzu greift ACC in Antrieb und Bremse ein. Sobald das vorausfahrende Fahrzeug beschleunigt oder die Spur verlässt, regelt ACC die Geschwindigkeit wieder auf die vorgegebene Sollgeschwindigkeit ein (Bild 1). ACC steht somit für eine Geschwindigkeitsregelung, die sich dem vorausfahrenden Verkehr anpasst.

  11. Optical Profilometers Using Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Hall, Gregory A.; Youngquist, Robert; Mikhael, Wasfy

    2006-01-01

    A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

  12. Linear ubiquitination signals in adaptive immune responses

    PubMed Central

    Ikeda, Fumiyo

    2015-01-01

    Summary Ubiquitin can form eight different linkage types of chains using the intrinsic Met 1 residue or one of the seven intrinsic Lys residues. Each linkage-type of ubiquitin chain has a distinct three-dimensional topology, functioning as a tag to attract specific signaling molecules, which are so-called ubiquitin readers, and regulates various biological functions. Ubiquitin chains linked via Met 1 in a head-to-tail manner are called linear ubiquitin chains. Linear ubiquitination plays an important role in the regulation of cellular signaling, including the best-characterized Tumor Necrosis Factor (TNF) -induced canonical nuclear factor-kappa B (NF-κB) pathway. Linear ubiquitin chains are specifically generated by an E3 ligase complex called the linear ubiquitin chain assembly complex (LUBAC) and hydrolyzed by a deubiquitinase (DUB) called ovarian tumor (OTU) DUB with linear linkage specificity (OTULIN). LUBAC linearly ubiquitinates critical molecules in the TNF pathway, such as NEMO and RIPK1. The linear ubiquitin chains are then recognized by the ubiquitin readers, including NEMO, which control the TNF pathway. Accumulating evidence indicates an importance of the LUBAC complex in the regulation of apoptosis, development, and inflammation in mice. In this article, I focus on the role of linear ubiquitin chains in adaptive immune responses with an emphasis on the TNF-induced signaling pathways. PMID:26085218

  13. An adaptive signal-processing approach to online adaptive tutoring.

    PubMed

    Bergeron, Bryan; Cline, Andrew

    2011-01-01

    Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

  14. Adaptive antenna arrays for weak interfering signals

    NASA Technical Reports Server (NTRS)

    Gupta, I. J.

    1985-01-01

    The interference protection provided by adaptive antenna arrays to an Earth station or satellite receive antenna system is studied. The case where the interference is caused by the transmission from adjacent satellites or Earth stations whose signals inadverently enter the receiving system and interfere with the communication link is considered. Thus, the interfering signals are very weak. To increase the interference suppression, one can either decrease the thermal noise in the feedback loops or increase the gain of the auxiliary antennas in the interfering signal direction. Both methods are examined. It is shown that one may have to reduce the noise correlation to impractically low values and if directive auxiliary antennas are used, the auxiliary antenna size may have to be too large. One can, however, combine the two methods to achieve the specified interference suppression with reasonable requirements of noise decorrelation and auxiliary antenna size. Effects of the errors in the steering vector on the adaptive array performance are studied.

  15. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2007-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  16. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2003-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  17. Nonlinear adaptive wavelet analysis of electrocardiogram signals

    NASA Astrophysics Data System (ADS)

    Yang, H.; Bukkapatnam, S. T.; Komanduri, R.

    2007-08-01

    Wavelet representation can provide an effective time-frequency analysis for nonstationary signals, such as the electrocardiogram (EKG) signals, which contain both steady and transient parts. In recent years, wavelet representation has been emerging as a powerful time-frequency tool for the analysis and measurement of EKG signals. The EKG signals contain recurring, near-periodic patterns of P , QRS , T , and U waveforms, each of which can have multiple manifestations. Identification and extraction of a compact set of features from these patterns is critical for effective detection and diagnosis of various disorders. This paper presents an approach to extract a fiducial pattern of EKG based on the consideration of the underlying nonlinear dynamics. The pattern, in a nutshell, is a combination of eigenfunctions of the ensembles created from a Poincare section of EKG dynamics. The adaptation of wavelet functions to the fiducial pattern thus extracted yields two orders of magnitude (some 95%) more compact representation (measured in terms of Shannon signal entropy). Such a compact representation can facilitate in the extraction of features that are less sensitive to extraneous noise and other variations. The adaptive wavelet can also lead to more efficient algorithms for beat detection and QRS cancellation as well as for the extraction of multiple classical EKG signal events, such as widths of QRS complexes and QT intervals.

  18. Optimal and adaptive methods of processing hydroacoustic signals (review)

    NASA Astrophysics Data System (ADS)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  19. Adaptive Noise Suppression Using Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Kozel, David; Nelson, Richard

    1996-01-01

    A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

  20. Adaptive wavelet Wiener filtering of ECG signals.

    PubMed

    Smital, Lukáš; Vítek, Martin; Kozumplík, Jiří; Provazník, Ivo

    2013-02-01

    In this study, we focused on the reduction of broadband myopotentials (EMG) in ECG signals using the wavelet Wiener filtering with noise-free signal estimation. We used the dyadic stationary wavelet transform (SWT) in the Wiener filter as well as in estimating the noise-free signal. Our goal was to find a suitable filter bank and to choose other parameters of the Wiener filter with respect to the signal-to-noise ratio (SNR) obtained. Testing was performed on artificially noised signals from the standard CSE database sampled at 500 Hz. When creating an artificial interference, we started from the generated white Gaussian noise, whose power spectrum was modified according to a model of the power spectrum of an EMG signal. To improve the filtering performance, we used adaptive setting parameters of filtering according to the level of interference in the input signal. We were able to increase the average SNR of the whole test database by about 10.6 dB. The proposed algorithm provides better results than the classic wavelet Wiener filter.

  1. Adaptive wavelet Wiener filtering of ECG signals.

    PubMed

    Smital, Lukáš; Vítek, Martin; Kozumplík, Jiří; Provazník, Ivo

    2013-02-01

    In this study, we focused on the reduction of broadband myopotentials (EMG) in ECG signals using the wavelet Wiener filtering with noise-free signal estimation. We used the dyadic stationary wavelet transform (SWT) in the Wiener filter as well as in estimating the noise-free signal. Our goal was to find a suitable filter bank and to choose other parameters of the Wiener filter with respect to the signal-to-noise ratio (SNR) obtained. Testing was performed on artificially noised signals from the standard CSE database sampled at 500 Hz. When creating an artificial interference, we started from the generated white Gaussian noise, whose power spectrum was modified according to a model of the power spectrum of an EMG signal. To improve the filtering performance, we used adaptive setting parameters of filtering according to the level of interference in the input signal. We were able to increase the average SNR of the whole test database by about 10.6 dB. The proposed algorithm provides better results than the classic wavelet Wiener filter. PMID:23192472

  2. Aircraft adaptive learning control

    NASA Technical Reports Server (NTRS)

    Lee, P. S. T.; Vanlandingham, H. F.

    1979-01-01

    The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.

  3. Adaptive Control with Reference Model Modification

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

  4. A population genetic signal of polygenic adaptation.

    PubMed

    Berg, Jeremy J; Coop, Graham

    2014-08-01

    Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of [Q(ST)/F(ST)] comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153

  5. Adaptive Control Of Remote Manipulator

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1989-01-01

    Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

  6. Adaptive Modal Identification for Flutter Suppression Control

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

    2016-01-01

    In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

  7. Nonlinear and adaptive control

    NASA Technical Reports Server (NTRS)

    Athans, Michael

    1989-01-01

    The primary thrust of the research was to conduct fundamental research in the theories and methodologies for designing complex high-performance multivariable feedback control systems; and to conduct feasibiltiy studies in application areas of interest to NASA sponsors that point out advantages and shortcomings of available control system design methodologies.

  8. Linearly-Constrained Adaptive Signal Processing Methods

    NASA Astrophysics Data System (ADS)

    Griffiths, Lloyd J.

    1988-01-01

    In adaptive least-squares estimation problems, a desired signal d(n) is estimated using a linear combination of L observation values samples xi (n), x2(n), . . . , xL-1(n) and denoted by the vector X(n). The estimate is formed as the inner product of this vector with a corresponding L-dimensional weight vector W. One particular weight vector of interest is Wopt which minimizes the mean-square between d(n) and the estimate. In this context, the term `mean-square difference' is a quadratic measure such as statistical expectation or time average. The specific value of W which achieves the minimum is given by the prod-uct of the inverse data covariance matrix and the cross-correlation between the data vector and the desired signal. The latter is often referred to as the P-vector. For those cases in which time samples of both the desired and data vector signals are available, a variety of adaptive methods have been proposed which will guarantee that an iterative weight vector Wa(n) converges (in some sense) to the op-timal solution. Two which have been extensively studied are the recursive least-squares (RLS) method and the LMS gradient approximation approach. There are several problems of interest in the communication and radar environment in which the optimal least-squares weight set is of interest and in which time samples of the desired signal are not available. Examples can be found in array processing in which only the direction of arrival of the desired signal is known and in single channel filtering where the spectrum of the desired response is known a priori. One approach to these problems which has been suggested is the P-vector algorithm which is an LMS-like approximate gradient method. Although it is easy to derive the mean and variance of the weights which result with this algorithm, there has never been an identification of the corresponding underlying error surface which the procedure searches. The purpose of this paper is to suggest an alternative

  9. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2011-01-01

    This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

  10. Multiple model adaptive control with mixing

    NASA Astrophysics Data System (ADS)

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  11. Criticality of Adaptive Control Dynamics

    NASA Astrophysics Data System (ADS)

    Patzelt, Felix; Pawelzik, Klaus

    2011-12-01

    We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.

  12. Adaptive control with aerospace applications

    NASA Astrophysics Data System (ADS)

    Gadient, Ross

    Robust and adaptive control techniques have a rich history of theoretical development with successful application. Despite the accomplishments made, attempts to combine the best elements of each approach into robust adaptive systems has proven challenging, particularly in the area of application to real world aerospace systems. In this research, we investigate design methods for general classes of systems that may be applied to representative aerospace dynamics. By combining robust baseline control design with augmentation designs, our work aims to leverage the advantages of each approach. This research contributes the development of robust model-based control design for two classes of dynamics: 2nd order cascaded systems, and a more general MIMO framework. We present a theoretically justified method for state limiting via augmentation of a robust baseline control design. Through the development of adaptive augmentation designs, we are able to retain system performance in the presence of uncertainties. We include an extension that combines robust baseline design with both state limiting and adaptive augmentations. In addition we develop an adaptive augmentation design approach for a class of dynamic input uncertainties. We present formal stability proofs and analyses for all proposed designs in the research. Throughout the work, we present real world aerospace applications using relevant flight dynamics and flight test results. We derive robust baseline control designs with application to both piloted and unpiloted aerospace system. Using our developed methods, we add a flight envelope protecting state limiting augmentation for piloted aircraft applications and demonstrate the efficacy of our approach via both simulation and flight test. We illustrate our adaptive augmentation designs via application to relevant fixed-wing aircraft dynamics. Both a piloted example combining the state limiting and adaptive augmentation approaches, and an unpiloted example with

  13. Endocannabinoid signalling in innate and adaptive immunity

    PubMed Central

    Chiurchiù, Valerio; Battistini, Luca; Maccarrone, Mauro

    2015-01-01

    The immune system can be modulated and regulated not only by foreign antigens but also by other humoral factors and metabolic products, which are able to affect several quantitative and qualitative aspects of immunity. Among these, endocannabinoids are a group of bioactive lipids that might serve as secondary modulators, which when mobilized coincident with or shortly after first-line immune modulators, increase or decrease many immune functions. Most immune cells express these bioactive lipids, together with their set of receptors and of enzymes regulating their synthesis and degradation. In this review, a synopsis of the manifold immunomodulatory effects of endocannabinoids and their signalling in the different cell populations of innate and adaptive immunity is appointed, with a particular distinction between mice and human immune system compartments. PMID:25585882

  14. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  15. Stable adaptive fuzzy controllers with application to inverted pendulum tracking.

    PubMed

    Wang, L X

    1996-01-01

    An adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given-trajectory. In this paper, two adaptive fuzzy controllers are designed based on the Lyapunov synthesis approach. We require that the final closed-loop system must be globally stable in the sense that all signals involved (states, controls, parameters, etc.) must be uniformly bounded. Roughly speaking, the adaptive fuzzy controllers are designed through the following steps: first, construct an initial controller based on linguistic descriptions (in the form of fuzzy IF-THEN rules) about the unknown plant from human experts; then, develop an adaptation law to adjust the parameters of the fuzzy controller on-line. We prove, for both adaptive fuzzy controllers, that: (1) all signals in the closed-loop systems are uniformly bounded; and (2) the tracking errors converge to zero under mild conditions. We provide the specific formulas of the bounds so that controller designers can determine the bounds based on their requirements. Finally, the adaptive fuzzy controllers are used to control the inverted pendulum to track a given trajectory, and the simulation results show that: (1) the adaptive fuzzy controllers can perform successful tracking without using any linguistic information; and (2) after incorporating some linguistic fuzzy rules into the controllers, the adaptation speed becomes faster and the tracking error becomes smaller.

  16. Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems.

    PubMed

    Wang, Chi-Hsu; Lin, Tsung-Chih; Lee, Tsu-Tian; Liu, Han-Leih

    2002-01-01

    A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect adaptive FNN controllers. A weighting factor, which can be adjusted by the tradeoff between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive FNN controller and direct adaptive FNN controller. Furthermore, a supervisory controller is appended into the FNN controller to force the state to be within the constraint set. Therefore, if the FNN controller cannot maintain the stability, the supervisory controller starts working to guarantee stability. On the other hand, if the FNN controller works well, the supervisory controller will be deactivated. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. Two nonlinear systems, namely, inverted pendulum system and Chua's (1989) chaotic circuit, are fully illustrated to track sinusoidal signals. The resulting hybrid direct/indirect FNN control systems show better performances, i.e., tracking error and control effort can be made smaller and it is more flexible during the design process.

  17. Repeated observation of an uncertain signal. [sensory adaptation

    NASA Technical Reports Server (NTRS)

    Swets, J. A.; Birdsall, T. G.

    1978-01-01

    The focus here is on sensory adaptation, or progressively more appropriate attention, as repeated observations yield more information about a signal with an uncertain parameter. The signal was a brief sinusoid; its uncertain parameter was frequency. Detection performance is predicted from data on a signal of known and constant frequency, as a function of the number of frequencies the uncertain signal could assume. A comparison condition presented a signal that varied in a manner not permitting adaptation. Models derived from signal detection theory describe the ideal observation processes for the three signal conditions, and supply quantitative predictions of relative performances. The models are generally supported by the data.

  18. Adaptable state based control system

    NASA Technical Reports Server (NTRS)

    Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)

    2004-01-01

    An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.

  19. Adaptive Control Allocation in the Presence of Actuator Failures

    NASA Technical Reports Server (NTRS)

    Liu, Yu; Crespo, Luis G.

    2010-01-01

    In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

  20. Adaptive controller for hyperthermia robot

    SciTech Connect

    Kress, R.L.

    1997-03-01

    This paper describes the development of an adaptive computer control routine for a robotically, deployed focused, ultrasonic hyperthermia cancer treatment system. The control algorithm developed herein uses physiological models of a tumor and the surrounding healthy tissue regions and transient temperature data to estimate the treatment region`s blood perfusion. This estimate is used to vary the specific power profile of a scanned, focused ultrasonic transducer to achieve a temperature distribution as close as possible to an optimal temperature distribution. The controller is evaluated using simulations of diseased tissue and using limited experiments on a scanned, focused ultrasonic treatment system that employs a 5-Degree-of-Freedom (D.O.F.) robot to scan the treatment transducers over a simulated patient. Results of the simulations and experiments indicate that the adaptive control routine improves the temperature distribution over standard classical control algorithms if good (although not exact) knowledge of the treated region is available. Although developed with a scanned, focused ultrasonic robotic treatment system in mind, the control algorithm is applicable to any system with the capability to vary specific power as a function of volume and having an unknown distributed energy sink proportional to temperature elevation (e.g., other robotically deployed hyperthermia treatment methods using different heating modalities).

  1. Keck adaptive optics: control subsystem

    SciTech Connect

    Brase, J.M.; An, J.; Avicola, K.

    1996-03-08

    Adaptive optics on the Keck 10 meter telescope will provide an unprecedented level of capability in high resolution ground based astronomical imaging. The system is designed to provide near diffraction limited imaging performance with Strehl {gt} 0.3 n median Keck seeing of r0 = 25 cm, T =10 msec at 500 nm wavelength. The system will be equipped with a 20 watt sodium laser guide star to provide nearly full sky coverage. The wavefront control subsystem is responsible for wavefront sensing and the control of the tip-tilt and deformable mirrors which actively correct atmospheric turbulence. The spatial sampling interval for the wavefront sensor and deformable mirror is de=0.56 m which gives us 349 actuators and 244 subapertures. This paper summarizes the wavefront control system and discusses particular issues in designing a wavefront controller for the Keck telescope.

  2. Adaptive Force Control in Compliant Motion

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1994-01-01

    This paper addresses the problem of controlling a manipulator in compliant motion while in contact with an environment having an unknown stiffness. Two classes of solutions are discussed: adaptive admittance control and adaptive compliance control. In both admittance and compliance control schemes, compensator adaptation is used to ensure a stable and uniform system performance.

  3. Adaptive Controller Effects on Pilot Behavior

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2014-01-01

    Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

  4. Neural Control Adaptation to Motor Noise Manipulation.

    PubMed

    Hasson, Christopher J; Gelina, Olga; Woo, Garrett

    2016-01-01

    Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability. PMID:26973487

  5. Neural Control Adaptation to Motor Noise Manipulation

    PubMed Central

    Hasson, Christopher J.; Gelina, Olga; Woo, Garrett

    2016-01-01

    Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability. PMID:26973487

  6. Adaptive classification on brain-computer interfaces using reinforcement signals.

    PubMed

    Llera, A; Gómez, V; Kappen, H J

    2012-11-01

    We introduce a probabilistic model that combines a classifier with an extra reinforcement signal (RS) encoding the probability of an erroneous feedback being delivered by the classifier. This representation computes the class probabilities given the task related features and the reinforcement signal. Using expectation maximization (EM) to estimate the parameter values under such a model shows that some existing adaptive classifiers are particular cases of such an EM algorithm. Further, we present a new algorithm for adaptive classification, which we call constrained means adaptive classifier, and show using EEG data and simulated RS that this classifier is able to significantly outperform state-of-the-art adaptive classifiers.

  7. Phase coherence adaptive processor for automatic signal detection and identification

    NASA Astrophysics Data System (ADS)

    Wagstaff, Ronald A.

    2006-05-01

    A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

  8. Dual-arm manipulators with adaptive control

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun (Inventor)

    1991-01-01

    The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.

  9. Diagnostic analysis of vibration signals using adaptive digital filtering techniques

    NASA Technical Reports Server (NTRS)

    Jewell, R. E.; Jones, J. H.; Paul, J. E.

    1983-01-01

    Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.

  10. Statistical Physics for Adaptive Distributed Control

    NASA Technical Reports Server (NTRS)

    Wolpert, David H.

    2005-01-01

    A viewgraph presentation on statistical physics for distributed adaptive control is shown. The topics include: 1) The Golden Rule; 2) Advantages; 3) Roadmap; 4) What is Distributed Control? 5) Review of Information Theory; 6) Iterative Distributed Control; 7) Minimizing L(q) Via Gradient Descent; and 8) Adaptive Distributed Control.

  11. Flight Test Approach to Adaptive Control Research

    NASA Technical Reports Server (NTRS)

    Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

    2011-01-01

    The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

  12. A new approach to adaptive control of manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1987-01-01

    An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

  13. Adaptive, predictive controller for optimal process control

    SciTech Connect

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  14. Monitoring the Performance of a Neuro-Adaptive Controller

    NASA Technical Reports Server (NTRS)

    Schumann, Johann; Gupta, Pramod

    2004-01-01

    Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

  15. Robust adaptive control for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Kahveci, Nazli E.

    anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.

  16. The hypoxia signaling pathway and hypoxic adaptation in fishes.

    PubMed

    Xiao, Wuhan

    2015-02-01

    The hypoxia signaling pathway is an evolutionarily conserved cellular signaling pathway present in animals ranging from Caenorhabditis elegans to mammals. The pathway is crucial for oxygen homeostasis maintenance. Hypoxia-inducible factors (HIF-1α and HIF-2α) are master regulators in the hypoxia signaling pathway. Oxygen concentrations vary a lot in the aquatic environment. To deal with this, fishes have adapted and developed varying strategies for living in hypoxic conditions. Investigations into the strategies and mechanisms of hypoxia adaptation in fishes will allow us to understand fish speciation and breed hypoxia-tolerant fish species/strains. This review summarizes the process of the hypoxia signaling pathway and its regulation, as well as the mechanism of hypoxia adaptation in fishes.

  17. Research in digital adaptive flight controllers

    NASA Technical Reports Server (NTRS)

    Kaufman, H.

    1976-01-01

    A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Both explicit controllers which directly utilize parameter identification and implicit controllers which do not require identification were considered. Extensive analytical and simulation efforts resulted in the recommendation of two explicit digital adaptive flight controllers. Interface weighted least squares estimation procedures with control logic were developed using either optimal regulator theory or with control logic based upon single stage performance indices.

  18. An adaptive Cartesian control scheme for manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1987-01-01

    A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

  19. Adaptive control: Myths and realities

    NASA Technical Reports Server (NTRS)

    Athans, M.; Valavani, L.

    1984-01-01

    It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.

  20. Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna; Gregory, Irene

    2013-01-01

    Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.

  1. Adaptive array for weak interfering signals: Geostationary satellite experiments

    NASA Astrophysics Data System (ADS)

    Steadman, Karl

    The performance of an experimental adaptive array is evaluated using signals from an existing geostationary satellite interference environment. To do this, an earth station antenna was built to receive signals from various geostationary satellites. In these experiments the received signals have a frequency of approximately 4 GHz (C-band) and have a bandwidth of over 35 MHz. These signals are downconverted to a 69 MHz intermediate frequency in the experimental system. Using the downconverted signals, the performance of the experimental system for various signal scenarios is evaluated. In this situation, due to the inherent thermal noise, qualitative instead of quantitative test results are presented. It is shown that the experimental system can null up to two interfering signals well below the noise level. However, to avoid the cancellation of the desired signal, the use a steering vector is needed. Various methods to obtain an estimate of the steering vector are proposed.

  2. Adaptive control of dual-arm robots

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1987-01-01

    Three strategies for adaptive control of cooperative dual-arm robots are described. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through the load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions, while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. The controllers have simple structures and are computationally fast for on-line implementation with high sampling rates.

  3. Adaptive Attitude Control of the Crew Launch Vehicle

    NASA Technical Reports Server (NTRS)

    Muse, Jonathan

    2010-01-01

    An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.

  4. Green light signaling and adaptive response

    PubMed Central

    Zhang, Tingting; Folta, Kevin M.

    2012-01-01

    To a plant, the sun’s light is not exclusively energy for photosynthesis, it also provides a package of data about time and prevailing conditions. The plant’s surroundings may dampen or filter solar energies, altering spectral profiles of their light environment. Plants use this information to adjust form and physiology, tailoring gene expression to best match ambient conditions. Extensive literature exists on how blue, red and far-red light contribute to plant adaptive responses. A growing body of work identifies discrete effects of green light (500–565 nm) that also shape plant biology. Green light responses are known to be either mediated through, or independent of, the cryptochrome blue light receptors. Responses to green light share a general tendency to oppose blue- or red-light-induced responses, including stem growth rate inhibition, anthocyanin accumulation or chloroplast gene expression. Recent evidence demonstrates a role for green light in sensing a shaded environment, independent from far-red shade responses. PMID:22301972

  5. Near-Perfect Adaptation in the E. coli Chemotaxis Signal Transduction Network

    NASA Astrophysics Data System (ADS)

    Yang, Yang; Setayeshgar, Sima

    2007-03-01

    Biochemical reaction networks constitute the computing language of the cell, from converting external stimuli into appropriate intracellular signals to regulating gene expression. Precise adaptation is an important property of many signaling networks, allowing compensation for continued stimulation without saturation. Furthermore, a common feature of intracellular reaction networks is the ability to operate in a noisy environment where concentrations of key components, such as signaling molecules and enzymes controlling reaction rates are typically small and therefore fluctuations in their numbers are significant. In the context of the well- characterized E. coli chemotaxis signal transduction network, we present a new computational scheme that explores surfaces in the space of total protein concentrations and reaction rates on which (near-)perfect adaptation holds. The resulting dependencies between parameters provide conditions for (near-)perfect adaptation as well as ranges of numerical values for parameters not reliably known from experiments. We generalize the applicability of this scheme to other signaling networks.

  6. Effects of incomplete adaption and disturbance in adaptive control

    NASA Technical Reports Server (NTRS)

    Lindorff, D. P.

    1972-01-01

    This investigation focused attention on the fact that the synthesis of adaptive control systems has often been discussed in the framework of idealizations which may represent over simplifications. A condition for boundedness of the tracking error has been derived for the case in which incomplete adaption and disturbance are present. When using Parks' design it is shown that instability of the adaptive gains can result due to the presence of disturbance. The theory has been applied to a nontrivial example in order to illustrate the concepts involved.

  7. Study on adaptive compressed sensing & reconstruction of quantized speech signals

    NASA Astrophysics Data System (ADS)

    Yunyun, Ji; Zhen, Yang

    2012-12-01

    Compressed sensing (CS) is a rising focus in recent years for its simultaneous sampling and compression of sparse signals. Speech signals can be considered approximately sparse or compressible in some domains for natural characteristics. Thus, it has great prospect to apply compressed sensing to speech signals. This paper is involved in three aspects. Firstly, the sparsity and sparsifying matrix for speech signals are analyzed. Simultaneously, a kind of adaptive sparsifying matrix based on the long-term prediction of voiced speech signals is constructed. Secondly, a CS matrix called two-block diagonal (TBD) matrix is constructed for speech signals based on the existing block diagonal matrix theory to find out that its performance is empirically superior to that of the dense Gaussian random matrix when the sparsifying matrix is the DCT basis. Finally, we consider the quantization effect on the projections. Two corollaries about the impact of the adaptive quantization and nonadaptive quantization on reconstruction performance with two different matrices, the TBD matrix and the dense Gaussian random matrix, are derived. We find that the adaptive quantization and the TBD matrix are two effective ways to mitigate the quantization effect on reconstruction of speech signals in the framework of CS.

  8. Dynamic optimization and adaptive controller design

    NASA Astrophysics Data System (ADS)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  9. Sensorimotor adaptation error signals are derived from realistic predictions of movement outcomes.

    PubMed

    Wong, Aaron L; Shelhamer, Mark

    2011-03-01

    Neural systems that control movement maintain accuracy by adaptively altering motor commands in response to errors. It is often assumed that the error signal that drives adaptation is equivalent to the sensory error observed at the conclusion of a movement; for saccades, this is typically the visual (retinal) error. However, we instead propose that the adaptation error signal is derived as the difference between the observed visual error and a realistic prediction of movement outcome. Using a modified saccade-adaptation task in human subjects, we precisely controlled the amount of error experienced at the conclusion of a movement by back-stepping the target so that the saccade is hypometric (positive retinal error), but less hypometric than if the target had not moved (smaller retinal error than expected). This separates prediction error from both visual errors and motor corrections. Despite positive visual errors and forward-directed motor corrections, we found an adaptive decrease in saccade amplitudes, a finding that is well-explained by the employment of a prediction-based error signal. Furthermore, adaptive changes in movement size were linearly correlated to the disparity between the predicted and observed movement outcomes, in agreement with the forward-model hypothesis of motor learning, which states that adaptation error signals incorporate predictions of motor outcomes computed using a copy of the motor command (efference copy).

  10. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

  11. Modeling-Error-Driven Performance-Seeking Direct Adaptive Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John

    2008-01-01

    This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.

  12. Demonstration of adaptation in beluga whale echolocation signals.

    PubMed

    Au, W W; Carder, D A; Penner, R H; Scronce, B L

    1985-02-01

    The echolocation signals of the same beluga whale (Delphinapterus leucas) were measured first in San Diego Bay, and later in Kaneohe Bay, Oahu, Hawaii. The ambient noise level in Kaneohe Bay is typically 12-17 dB greater than in San Diego Bay. The whale demonstrated the adaptiveness of its biosonar by shifting to higher frequencies and intensities after it was moved to Kaneohe. In San Diego, the animal emitted echolocation signals with peak frequencies between 40 and 60 kHz, and bandwidths between 15 and 25 kHz. In Kaneohe, the whale shifted its signals approximately an octave higher in frequencies with peak frequencies between 100 and 120 kHz, and bandwidths between 20 and 40 kHz. Signal intensities measured in Kaneohe were up to 18 dB higher than in San Diego. The data collected represent the first quantitative evidence of the adaptive capability of a cetacean biosonar system.

  13. Adaptive control applied to Space Station attitude control system

    NASA Technical Reports Server (NTRS)

    Lam, Quang M.; Chipman, Richard; Hu, Tsay-Hsin G.; Holmes, Eric B.; Sunkel, John

    1992-01-01

    This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.

  14. Predictor-Based Model Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2009-01-01

    This paper is devoted to robust, Predictor-based Model Reference Adaptive Control (PMRAC) design. The proposed adaptive system is compared with the now-classical Model Reference Adaptive Control (MRAC) architecture. Simulation examples are presented. Numerical evidence indicates that the proposed PMRAC tracking architecture has better than MRAC transient characteristics. In this paper, we presented a state-predictor based direct adaptive tracking design methodology for multi-input dynamical systems, with partially known dynamics. Efficiency of the design was demonstrated using short period dynamics of an aircraft. Formal proof of the reported PMRAC benefits constitute future research and will be reported elsewhere.

  15. Adaptive muffler based on controlled flow valves.

    PubMed

    Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij

    2015-06-01

    An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462

  16. Flight Approach to Adaptive Control Research

    NASA Technical Reports Server (NTRS)

    Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

    2011-01-01

    The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

  17. Statistical-uncertainty-based adaptive filtering of lidar signals

    SciTech Connect

    Fuehrer, P. L.; Friehe, C. A.; Hristov, T. S.; Cooper, D. I.; Eichinger, W. E.

    2000-02-10

    An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H{sub 2}O and the N{sub 2} photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America.

  18. Statistical-uncertainty-based adaptive filtering of lidar signals.

    PubMed

    Fuehrer, P L; Friehe, C A; Hristov, T S; Cooper, D I; Eichinger, W E

    2000-02-10

    An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometeorological humidity data were used to calibrate the ratio of the lidar gains of the H(2)O and the N(2) photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem.

  19. Mechanical signal transduction in skeletal muscle growth and adaptation.

    PubMed

    Tidball, James G

    2005-05-01

    The adaptability of skeletal muscle to changes in the mechanical environment has been well characterized at the tissue and system levels, but the mechanisms through which mechanical signals are transduced to chemical signals that influence muscle growth and metabolism remain largely unidentified. However, several findings have suggested that mechanical signal transduction in muscle may occur through signaling pathways that are shared with insulin-like growth factor (IGF)-I. The involvement of IGF-I-mediated signaling for mechanical signal transduction in muscle was originally suggested by the observations that muscle releases IGF-I on mechanical stimulation, that IGF-I is a potent agent for promoting muscle growth and affecting phenotype, and that IGF-I can function as an autocrine hormone in muscle. Accumulating evidence shows that at least two signaling pathways downstream of IGF-I binding can influence muscle growth and adaptation. Signaling via the calcineurin/nuclear factor of activated T-cell pathway has been shown to have a powerful influence on promoting the slow/type I phenotype in muscle but can also increase muscle mass. Neural stimulation of muscle can activate this pathway, although whether neural activation of the pathway can occur independent of mechanical activation or independent of IGF-I-mediated signaling remains to be explored. Signaling via the Akt/mammalian target of rapamycin pathway can also increase muscle growth, and recent findings show that activation of this pathway can occur as a response to mechanical stimulation applied directly to muscle cells, independent of signals derived from other cells. In addition, mechanical activation of mammalian target of rapamycin, Akt, and other downstream signals is apparently independent of autocrine factors, which suggests that activation of the mechanical pathway occurs independent of muscle-mediated IGF-I release.

  20. Diabetes: Models, Signals, and Control

    PubMed Central

    Cobelli, Claudio; Man, Chiara Dalla; Sparacino, Giovanni; Magni, Lalo; De Nicolao, Giuseppe; Kovatchev, Boris P.

    2010-01-01

    The control of diabetes is an interdisciplinary endeavor, which includes a significant biomedical engineering component, with traditions of success beginning in the early 1960s. It began with modeling of the insulin-glucose system, and progressed to large-scale in silico experiments, and automated closed-loop control (artificial pancreas). Here, we follow these engineering efforts through the last, almost 50 years. We begin with the now classic minimal modeling approach and discuss a number of subsequent models, which have recently resulted in the first in silico simulation model accepted as substitute to animal trials in the quest for optimal diabetes control. We then review metabolic monitoring, with a particular emphasis on the new continuous glucose sensors, on the analyses of their time-series signals, and on the opportunities that they present for automation of diabetes control. Finally, we review control strategies that have been successfully employed in vivo or in silico, presenting a promise for the development of a future artificial pancreas and, in particular, discuss a modular architecture for building closed-loop control systems, including insulin delivery and patient safety supervision layers. We conclude with a brief discussion of the unique interactions between human physiology, behavioral events, engineering modeling and control relevant to diabetes. PMID:20936056

  1. Adaptive Impedance Control Of Redundant Manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun; Colbaugh, Richard D.; Glass, Kristin L.

    1994-01-01

    Improved method of controlling mechanical impedance of end effector of redundant robotic manipulator based on adaptive-control theory. Consists of two subsystems: adaptive impedance controller generating force-control inputs in Cartesian space of end effector to provide desired end-effector-impedance characteristics, and subsystem implementing algorithm that maps force-control inputs into torques applied to joints of manipulator. Accurate control of end effector and effective utilization of redundancy achieved simultaneously by use of method. Potential use to improve performance of such typical impedance-control tasks as deburring edges and accommodating transitions between unconstrained and constrained motions of end effectors.

  2. Adaptive spacecraft attitude control utilizing eigenaxis rotations

    NASA Technical Reports Server (NTRS)

    Cochran, J. E., Jr.; Colburn, B. K.; Speakman, N. O.

    1975-01-01

    Conventional and adaptive attitude control of spacecraft which use control moment gyros (CMG's) as torque sources are discussed. Control laws predicated on the assumption of a linear system are used since the spacecraft equations of motion are formulated in an 'eigenaxis system' so that they are essentially linear during 'slow' maneuvers even if large angles are involved. The overall control schemes are 'optimal' in several senses. Eigenaxis rotations and a weighted pseudo-inverse CMG steering law are used and, in the adaptive case, a Model Reference Adaptive System (MRAS) controller based on Liapunov's Second Method is adopted. To substantiate the theory, digital simulation results obtained using physical parameters of a Large Space Telescope type spacecraft are presented. These results indicate that an adaptive control law is often desirable.

  3. Chaotic satellite attitude control by adaptive approach

    NASA Astrophysics Data System (ADS)

    Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping

    2014-06-01

    In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.

  4. Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal

    2006-01-01

    This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.

  5. Adaptive Flight Control Research at NASA

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.

    2008-01-01

    A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.

  6. An adaptive hierarchical sensing scheme for sparse signals

    NASA Astrophysics Data System (ADS)

    Schütze, Henry; Barth, Erhardt; Martinetz, Thomas

    2014-02-01

    In this paper, we present Adaptive Hierarchical Sensing (AHS), a novel adaptive hierarchical sensing algorithm for sparse signals. For a given but unknown signal with a sparse representation in an orthogonal basis, the sensing task is to identify its non-zero transform coefficients by performing only few measurements. A measurement is simply the inner product of the signal and a particular measurement vector. During sensing, AHS partially traverses a binary tree and performs one measurement per visited node. AHS is adaptive in the sense that after each measurement a decision is made whether the entire subtree of the current node is either further traversed or omitted depending on the measurement value. In order to acquire an N -dimensional signal that is K-sparse, AHS performs O(K log N/K) measurements. With AHS, the signal is easily reconstructed by a basis transform without the need to solve an optimization problem. When sensing full-size images, AHS can compete with a state-of-the-art compressed sensing approach in terms of reconstruction performance versus number of measurements. Additionally, we simulate the sensing of image patches by AHS and investigate the impact of the choice of the sparse coding basis as well as the impact of the tree composition.

  7. Decentralized digital adaptive control of robot motion

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1990-01-01

    A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

  8. The Adapter Molecule Sin Regulates T-Cell-Receptor-Mediated Signal Transduction by Modulating Signaling Substrate Availability

    PubMed Central

    Xing, Luzhou; Donlin, Laura T.; Miller, Rebecca H.; Alexandropoulos, Konstantina

    2004-01-01

    Engagement of the T-cell receptor (TCR) results in the activation of a multitude of signaling events that regulate the function of T lymphocytes. These signaling events are in turn modulated by adapter molecules, which control the final functional output through the formation of multiprotein complexes. In this report, we identified the adapter molecule Sin as a new regulator of T-cell activation. We found that the expression of Sin in transgenic T lymphocytes and Jurkat T cells inhibited interleukin-2 expression and T-cell proliferation. This inhibitory effect was specific and was due to defective phospholipase C-γ (PLC-γ) phosphorylation and activation. In contrast to other adapters that become phosphorylated upon TCR stimulation, Sin was constitutively phosphorylated in resting cells by the Src kinase Fyn and bound to signaling intermediates, including PLC-γ. In stimulated cells, Sin was transiently dephosphorylated, which coincided with transient dissociation of Fyn and PLC-γ. Downregulation of Sin expression using Sin-specific short interfering RNA oligonucleotides inhibited transcriptional activation in response to TCR stimulation. Our results suggest that endogenous Sin influences T-lymphocyte signaling by sequestering signaling substrates and regulating their availability and/or activity in resting cells, while Sin is required for targeting these intermediates to the TCR for fast signal transmission during stimulation. PMID:15121874

  9. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment

  10. On fractional Model Reference Adaptive Control.

    PubMed

    Shi, Bao; Yuan, Jian; Dong, Chao

    2014-01-01

    This paper extends the conventional Model Reference Adaptive Control systems to fractional ones based on the theory of fractional calculus. A control law and an incommensurate fractional adaptation law are designed for the fractional plant and the fractional reference model. The stability and tracking convergence are analyzed using the frequency distributed fractional integrator model and Lyapunov theory. Moreover, numerical simulations of both linear and nonlinear systems are performed to exhibit the viability and effectiveness of the proposed methodology. PMID:24574897

  11. Hybrid adaptive ascent flight control for a flexible launch vehicle

    NASA Astrophysics Data System (ADS)

    Lefevre, Brian D.

    For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the

  12. Adaptive whitening of ambient ocean noise with narrowband signal preservation.

    PubMed

    Hollmann, Luke J; Stevenson, Robert L

    2016-06-01

    Passive underwater listening devices are often deployed to listen for narrowband signals of interest in time-varying background ocean noise. Such tonals are generated mechanically by ships, submarines, and machines, or acoustically by aquatic wildlife. Quantization of the sensor data for storage or low bit-rate transmission adds white noise which can overwhelm weak narrowband signals if the background noise is sufficiently colored. Whitening the background noise prior to quantization can reduce the detrimental effects, but the whitening process must preserve any tonals in the signal for maximum effectiveness. Existing adaptive whitening techniques make no effort to avoid suppressing tonals in the whitening process, while existing spectral separation methods fail to whiten background noise. The proposed methods perform adaptive whitening of background ambient noise while preserving narrowband tones at their original signal-to-noise ratios. The proposed methods are shown to outperform combinations of existing partial solutions both subjectively and by evaluating the objective criteria introduced. The stability and convergence properties of the proposed algorithms match or surpass those of existing well-known adaptive algorithms. PMID:27369136

  13. Simple adaptive tracking control for mobile robots

    NASA Astrophysics Data System (ADS)

    Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton

    2014-12-01

    The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.

  14. An adaptive grid with directional control

    NASA Technical Reports Server (NTRS)

    Brackbill, J. U.

    1993-01-01

    An adaptive grid generator for adaptive node movement is here derived by combining a variational formulation of Winslow's (1981) variable-diffusion method with a directional control functional. By applying harmonic-function theory, it becomes possible to define conditions under which there exist unique solutions of the resulting elliptic equations. The results obtained for the grid generator's application to the complex problem posed by the fluid instability-driven magnetic field reconnection demonstrate one-tenth the computational cost of either a Eulerian grid or an adaptive grid without directional control.

  15. Genetic algorithms in adaptive fuzzy control

    NASA Technical Reports Server (NTRS)

    Karr, C. Lucas; Harper, Tony R.

    1992-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

  16. Adaptive Control for Microgravity Vibration Isolation System

    NASA Technical Reports Server (NTRS)

    Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

    2005-01-01

    Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

  17. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  18. Intelligent Engine Systems: Adaptive Control

    NASA Technical Reports Server (NTRS)

    Gibson, Nathan

    2008-01-01

    We have studied the application of the baseline Model Predictive Control (MPC) algorithm to the control of main fuel flow rate (WF36), variable bleed valve (AE24) and variable stator vane (STP25) control of a simulated high-bypass turbofan engine. Using reference trajectories for thrust and turbine inlet temperature (T41) generated by a simulated new engine, we have examined MPC for tracking these two reference outputs while controlling a deteriorated engine. We have examined the results of MPC control for six different transients: two idle-to-takeoff transients at sea level static (SLS) conditions, one takeoff-to-idle transient at SLS, a Bode power command and reverse Bode power command at 20,000 ft/Mach 0.5, and a reverse Bode transient at 35,000 ft/Mach 0.84. For all cases, our primary focus was on the computational effort required by MPC for varying MPC update rates, control horizons, and prediction horizons. We have also considered the effects of these MPC parameters on the performance of the control, with special emphasis on the thrust tracking error, the peak T41, and the sizes of violations of the constraints on the problem, primarily the booster stall margin limit, which for most cases is the lone constraint that is violated with any frequency.

  19. Adaptive control of large space structures using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures was studied. Lattice filters are used widely in the areas of speech and signal processing. Herein, they are used to identify the structural dynamics model of the flexible structures. This identified model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures control is engaged. This type of validation scheme prevents instability when the overall loop is closed. The results obtained from simulation were compared to those obtained from experiments. In this regard, the flexible beam and grid apparatus at the Aerospace Control Research Lab (ACRL) of NASA Langley Research Center were used as the principal candidates for carrying out the above tasks. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods.

  20. Enhanced weak-signal sensitivity in two-photon microscopy by adaptive illumination.

    PubMed

    Chu, Kengyeh K; Lim, Daryl; Mertz, Jerome

    2007-10-01

    We describe a technique to enhance both the weak-signal relative sensitivity and the dynamic range of a laser scanning optical microscope. The technique is based on maintaining a fixed detection power by fast feedback control of the illumination power, thereby transferring high measurement resolution to weak signals while virtually eliminating the possibility of image saturation. We analyze and demonstrate the benefits of adaptive illumination in two-photon fluorescence microscopy.

  1. Adaptive Nonlinear Signal Approximation Using Bacterial Foraging Strategy

    NASA Astrophysics Data System (ADS)

    Kumar, Naik Manoj; Rutuparna, Panda

    Uniform approximation of signals has been an area of interest for researchers working in different disciplines of science and engineering. This paper presents an adaptive algorithm based on E. coli bacteria foraging strategy (EBFS) for uniform approximation of signals by linear combinations of shifted nonlinear basis functions. New class of nonlinear basis functions has been derived from a sigmoid function. The weight factor of the newly proposed nonlinear basis functions has been optimized by using the EBFS to minimize the mean square error. Different test signals are considered for validation of the present technique. Results are also compared with Genetic algorithm approach. The proposed technique could also be useful in fractional signal processing applications.

  2. Specificity, cross-talk and adaptation in Interferon signaling

    NASA Astrophysics Data System (ADS)

    Zilman, Anton

    Innate immune system is the first line of defense of higher organisms against pathogens. It coordinates the behavior of millions of cells of multiple types, achieved through numerous signaling molecules. This talk focuses on the signaling specificity of a major class of signaling molecules - Type I Interferons - which are also used therapeutically in the treatment of a number of diseases, such as Hepatitis C, multiple sclerosis and some cancers. Puzzlingly, different Interferons act through the same cell surface receptor but have different effects on the target cells. They also exhibit a strange pattern of temporal cross-talk resulting in a serious clinical problem - loss of response to Interferon therapy. We combined mathematical modeling with quantitative experiments to develop a quantitative model of specificity and adaptation in the Interferon signaling pathway. The model resolves several outstanding experimental puzzles and directly affects the clinical use of Type I Interferons in treatment of viral hepatitis and other diseases.

  3. Adaptive change in corporate control practices.

    PubMed

    Alexander, J A

    1991-03-01

    Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.

  4. Sensory adaptation of Dictyostelium discoideum cells to chemotactic signals

    PubMed Central

    1983-01-01

    Postvegetative Dictyostelium discoideum cells react chemotactically to gradients of cAMP, folic acid, and pterin. In the presence of a constant concentration of 10(-5) M cAMP cells move at random. They still are able to respond to superimposed gradients of cAMP, although the response is less efficient than without the high background level of cAMP. Cells which are accommodated to 10(-5) M cAMP do not react to a gradient of cAMP if the mean cAMP concentration is decreasing with time. This indicates the involvement of adaptation in the detection of chemotactic gradients: cells adapt to the mean concentration of chemoattractant and respond to positive deviations from the mean concentration. Cells adapted to high cAMP concentrations react normally to gradients of folic acid or pterin. Adaptation to one of these compounds does not affect the response to the other attractants. This suggests that cAMP, folic acid, and pterin are detected by different receptors, and that adaptation is localized at a step in the transduction process before the signals from these receptors coincide into one pathway. I discuss the implications of adaptation for chemotaxis and cell aggregation. PMID:6304109

  5. Ethanolamine Signaling Promotes Salmonella Niche Recognition and Adaptation during Infection

    PubMed Central

    Anderson, Christopher J.; Clark, David E.; Adli, Mazhar; Kendall, Melissa M.

    2015-01-01

    Chemical and nutrient signaling are fundamental for all cellular processes, including interactions between the mammalian host and the microbiota, which have a significant impact on health and disease. Ethanolamine is an essential component of cell membranes and has profound signaling activity within mammalian cells by modulating inflammatory responses and intestinal physiology. Here, we describe a virulence-regulating pathway in which the foodborne pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) exploits ethanolamine signaling to recognize and adapt to distinct niches within the host. The bacterial transcription factor EutR promotes ethanolamine metabolism in the intestine, which enables S. Typhimurium to establish infection. Subsequently, EutR directly activates expression of the Salmonella pathogenicity island 2 in the intramacrophage environment, and thus augments intramacrophage survival. Moreover, EutR is critical for robust dissemination during mammalian infection. Our findings reveal that S. Typhimurium co-opts ethanolamine as a signal to coordinate metabolism and then virulence. Because the ability to sense ethanolamine is a conserved trait among pathogenic and commensal bacteria, our work indicates that ethanolamine signaling may be a key step in the localized adaptation of bacteria within their mammalian hosts. PMID:26565973

  6. Synthetic aperture radar signal data compression using block adaptive quantization

    NASA Technical Reports Server (NTRS)

    Kuduvalli, Gopinath; Dutkiewicz, Melanie; Cumming, Ian

    1994-01-01

    This paper describes the design and testing of an on-board SAR signal data compression algorithm for ESA's ENVISAT satellite. The Block Adaptive Quantization (BAQ) algorithm was selected, and optimized for the various operational modes of the ASAR instrument. A flexible BAQ scheme was developed which allows a selection of compression ratio/image quality trade-offs. Test results show the high quality of the SAR images processed from the reconstructed signal data, and the feasibility of on-board implementation using a single ASIC.

  7. L1 adaptive output-feedback control architectures

    NASA Astrophysics Data System (ADS)

    Kharisov, Evgeny

    This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine

  8. Adaptive Inner-Loop Rover Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

    2006-01-01

    Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

  9. Error Signals in Motor Cortices Drive Adaptation in Reaching.

    PubMed

    Inoue, Masato; Uchimura, Motoaki; Kitazawa, Shigeru

    2016-06-01

    Reaching movements are subject to adaptation in response to errors induced by prisms or external perturbations. Motor cortical circuits have been hypothesized to provide execution errors that drive adaptation, but human imaging studies to date have reported that execution errors are encoded in parietal association areas. Thus, little evidence has been uncovered that supports the motor hypothesis. Here, we show that both primary motor and premotor cortices encode information on end-point errors in reaching. We further show that post-movement microstimulation to these regions caused trial-by-trial increases in errors, which subsided exponentially when the stimulation was terminated. The results indicate for the first time that motor cortical circuits provide error signals that drive trial-by-trial adaptation in reaching movements. PMID:27181058

  10. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Montenegro, Justino (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of Field Programmable Gate Arrays (FPGA's) in the hardware implementation of fast digital signal processing functions. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used Proportional-Integral-Derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a Digital Signal Processor (DSP) device or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using DSP devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, Pulse Width Modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. An alternative is required for compact implementation of such functionality to withstand the harsh environment encountered on spacemap. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive-control algorithm

  11. Adaptive plasticity in wild field cricket's acoustic signaling.

    PubMed

    Bertram, Susan M; Harrison, Sarah J; Thomson, Ian R; Fitzsimmons, Lauren P

    2013-01-01

    Phenotypic plasticity can be adaptive when phenotypes are closely matched to changes in the environment. In crickets, rhythmic fluctuations in the biotic and abiotic environment regularly result in diel rhythms in density of sexually active individuals. Given that density strongly influences the intensity of sexual selection, we asked whether crickets exhibit plasticity in signaling behavior that aligns with these rhythmic fluctuations in the socio-sexual environment. We quantified the acoustic mate signaling behavior of wild-caught males of two cricket species, Gryllus veletis and G. pennsylvanicus. Crickets exhibited phenotypically plastic mate signaling behavior, with most males signaling more often and more attractively during the times of day when mating activity is highest in the wild. Most male G. pennsylvanicus chirped more often and louder, with shorter interpulse durations, pulse periods, chirp durations, and interchirp durations, and at slightly higher carrier frequencies during the time of the day that mating activity is highest in the wild. Similarly, most male G. veletis chirped more often, with more pulses per chirp, longer interpulse durations, pulse periods, and chirp durations, shorter interchirp durations, and at lower carrier frequencies during the time of peak mating activity in the wild. Among-male variation in signaling plasticity was high, with some males signaling in an apparently maladaptive manner. Body size explained some of the among-male variation in G. pennsylvanicus plasticity but not G. veletis plasticity. Overall, our findings suggest that crickets exhibit phenotypically plastic mate attraction signals that closely match the fluctuating socio-sexual context they experience.

  12. Adaptive Control Strategies for Flexible Robotic Arm

    NASA Technical Reports Server (NTRS)

    Bialasiewicz, Jan T.

    1996-01-01

    The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.

  13. Direct adaptive control of a PUMA 560 industrial robot

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun; Lee, Thomas; Delpech, Michel

    1989-01-01

    The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.

  14. A discrete-time adaptive control scheme for robot manipulators

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1990-01-01

    A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

  15. Language control in bilinguals: The adaptive control hypothesis

    PubMed Central

    Abutalebi, Jubin

    2013-01-01

    Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual. PMID:25077013

  16. Remote Control of Neuronal Signaling

    PubMed Central

    Rogan, Sarah C.

    2011-01-01

    A significant challenge for neuroscientists is to determine how both electrical and chemical signals affect the activity of cells and circuits and how the nervous system subsequently translates that activity into behavior. Remote, bidirectional manipulation of those signals with high spatiotemporal precision is an ideal approach to addressing that challenge. Neuroscientists have recently developed a diverse set of tools that permit such experimental manipulation with varying degrees of spatial, temporal, and directional control. These tools use light, peptides, and small molecules to primarily activate ion channels and G protein-coupled receptors (GPCRs) that in turn activate or inhibit neuronal firing. By monitoring the electrophysiological, biochemical, and behavioral effects of such activation/inhibition, researchers can better understand the links between brain activity and behavior. Here, we review the tools that are available for this type of experimentation. We describe the development of the tools and highlight exciting in vivo data. We focus primarily on designer GPCRs (receptors activated solely by synthetic ligands, designer receptors exclusively activated by designer drugs) and microbial opsins (e.g., channelrhodopsin-2, halorhodopsin, Volvox carteri channelrhodopsin) but also describe other novel techniques that use orthogonal receptors, caged ligands, allosteric modulators, and other approaches. These tools differ in the direction of their effect (activation/inhibition, hyperpolarization/depolarization), their onset and offset kinetics (milliseconds/minutes/hours), the degree of spatial resolution they afford, and their invasiveness. Although none of these tools is perfect, each has advantages and disadvantages, which we describe, and they are all still works in progress. We conclude with suggestions for improving upon the existing tools. PMID:21415127

  17. Adaptive output feedback control of flexible systems

    NASA Astrophysics Data System (ADS)

    Yang, Bong-Jun

    Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in

  18. Adaptive beamforming for array signal processing in aeroacoustic measurements.

    PubMed

    Huang, Xun; Bai, Long; Vinogradov, Igor; Peers, Edward

    2012-03-01

    Phased microphone arrays have become an important tool in the localization of noise sources for aeroacoustic applications. In most practical aerospace cases the conventional beamforming algorithm of the delay-and-sum type has been adopted. Conventional beamforming cannot take advantage of knowledge of the noise field, and thus has poorer resolution in the presence of noise and interference. Adaptive beamforming has been used for more than three decades to address these issues and has already achieved various degrees of success in areas of communication and sonar. In this work an adaptive beamforming algorithm designed specifically for aeroacoustic applications is discussed and applied to practical experimental data. It shows that the adaptive beamforming method could save significant amounts of post-processing time for a deconvolution method. For example, the adaptive beamforming method is able to reduce the DAMAS computation time by at least 60% for the practical case considered in this work. Therefore, adaptive beamforming can be considered as a promising signal processing method for aeroacoustic measurements.

  19. Adaptive neural control of aeroelastic response

    NASA Astrophysics Data System (ADS)

    Lichtenwalner, Peter F.; Little, Gerald R.; Scott, Robert C.

    1996-05-01

    The Adaptive Neural Control of Aeroelastic Response (ANCAR) program is a joint research and development effort conducted by McDonnell Douglas Aerospace (MDA) and the National Aeronautics and Space Administration, Langley Research Center (NASA LaRC) under a Memorandum of Agreement (MOA). The purpose of the MOA is to cooperatively develop the smart structure technologies necessary for alleviating undesirable vibration and aeroelastic response associated with highly flexible structures. Adaptive control can reduce aeroelastic response associated with buffet and atmospheric turbulence, it can increase flutter margins, and it may be able to reduce response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Phase I of the ANCAR program involved development and demonstration of a neural network-based semi-adaptive flutter suppression system which used a neural network for scheduling control laws as a function of Mach number and dynamic pressure. This controller was tested along with a robust fixed-gain control law in NASA's Transonic Dynamics Tunnel (TDT) utilizing the Benchmark Active Controls Testing (BACT) wing. During Phase II, a fully adaptive on-line learning neural network control system has been developed for flutter suppression which will be tested in 1996. This paper presents the results of Phase I testing as well as the development progress of Phase II.

  20. Pheromonal control: reconciling physiological mechanism with signalling theory.

    PubMed

    Peso, Marianne; Elgar, Mark A; Barron, Andrew B

    2015-05-01

    Pheromones are intraspecific chemical signals. They can have profound effects on the behaviour and/or physiology of the receiver, and it is still common to hear pheromones described as controlling of the behaviour of the receiver. The discussion of pheromonal control arose initially from a close association between hormones and pheromones in the comparative physiological literature, but the concept of a controlling pheromone is at odds with contemporary signal evolution theory, which predicts that a manipulative pheromonal signal negatively affecting the receiver's fitness should not be stable over evolutionary time. Here we discuss the meaning of pheromonal control, and the ecological circumstances by which it might be supported. We argue that in discussing pheromonal control it is important to differentiate between control applied to the effects of a pheromone on a receiver's physiology (proximate control), and control applied to the effects of a pheromone on a receiver's fitness (ultimate control). Critically, a pheromone signal affecting change in the receiver's behaviour or physiology need not necessarily manipulate the fitness of a receiver. In cases where pheromonal signalling does lead to a reduction in the fitness of the receiver, the signalling system would be stable if the pheromone were an honest signal of a social environment that disadvantages the receiver, and the physiological and behavioural changes observed in the receiver were an adaptive response to the new social circumstances communicated by the pheromone. PMID:24925630

  1. Robust, Practical Adaptive Control for Launch Vehicles

    NASA Technical Reports Server (NTRS)

    Orr, Jeb. S.; VanZwieten, Tannen S.

    2012-01-01

    A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

  2. Bayesian nonparametric adaptive control using Gaussian processes.

    PubMed

    Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

    2015-03-01

    Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

  3. Adaptive control design for hysteretic smart systems

    NASA Astrophysics Data System (ADS)

    McMahan, Jerry A.; Smith, Ralph C.

    2011-04-01

    Ferroelectric and ferromagnetic actuators are being considered for a range of industrial, aerospace, aeronautic and biomedical applications due to their unique transduction capabilities. However, they also exhibit hysteretic and nonlinear behavior that must be accommodated in models and control designs. If uncompensated, these effects can yield reduced system performance and, in the worst case, can produce unpredictable behavior of the control system. In this paper, we address the development of adaptive control designs for hysteretic systems. We review an MRAC-like adaptive control algorithm used to track a reference trajectory while computing online estimates for certain model parameters. This method is incorporated in a composite control algorithm to improve the tracking capabilities of the system. Issues arising in the implementation of these algorithms are addressed, and a numerical example is presented, comparing the results of each method.

  4. Adaptive control of a robotic manipulator

    NASA Technical Reports Server (NTRS)

    Lewis, R. A.

    1977-01-01

    A control hierarchy for a robotic manipulator is described. The hierarchy includes perception and robot/environment interaction, the latter consisting of planning, path control, and terminal guidance loops. Environment-sensitive features include the provision of control governed by proximity, tactile, and visual sensors as well as the usual kinematic sensors. The manipulator is considered as part of an overall robot system. 'Adaptive control' in the present context refers to both the hierarchical nature of the control system and to its environment-responsive nature.

  5. Evolving Systems and Adaptive Key Component Control

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  6. Adaptive control of sulfur recovery units

    SciTech Connect

    Cunningham, D.B. )

    1994-08-01

    In a recent trial, adaptive control reduce the standard deviation of the tail gas ratio by 38%--increasing sulfur recovery efficiency by an estimated 0.3%. By using the controller on other control loops in the process, further increases are expected. Improved process control is a cost effective way to meet existing emissions limits. Future legislation will reduce the permissible emissions level, so it is imperative that existing sulfur recovery equipment by operated at peak efficiency. Peak efficiency can only be achieved with good trim air control, since it determines recovery efficiency. But process time delays and changes in the incoming gas stream make good control difficult to achieve. An adaptive controller is well suited to trim air control, since it can easily handle time delay sand adapt to changing process conditions. The improved efficiency is a considerable economic benefit to gas processing plants, since: (1) capital and operating expenses needed to improve recovery efficiency are avoided; (2) increased production is possible, since sulfur license limits are easier to meet; and (3) catalyst bed life is extended. Results of the test are discussed.

  7. Modeling and control of nonlinear systems using novel fuzzy wavelet networks: The output adaptive control approach

    NASA Astrophysics Data System (ADS)

    Mousavi, Seyyed Hossein; Noroozi, Navid; Safavi, Ali Akbar; Ebadat, Afrooz

    2011-09-01

    This paper proposes an observer based self-structuring robust adaptive fuzzy wave-net (FWN) controller for a class of nonlinear uncertain multi-input multi-output systems. The control signal is comprised of two parts. The first part arises from an adaptive fuzzy wave-net based controller that approximates the system structural uncertainties. The second part comes from a robust H∞ based controller that is used to attenuate the effect of function approximation error and disturbance. Moreover, a new self structuring algorithm is proposed to determine the location of basis functions. Simulation results are provided for a two DOF robot to show the effectiveness of the proposed method.

  8. VSS Robust Adaptive Control Including a Self-Tuning Controller for a Rotary Inverted Pendulum

    NASA Astrophysics Data System (ADS)

    Hirata, Hiroshi; Takabe, Tomohiro; Anabuki, Masatoshi; Ouchi, Shigeto

    So many papers with respect to the stabilization of the inverted pendulum are reported, because it is typically unstable system and is well used as example to verify many control theories. However, few approaches consider the inverted pendulum as unknown parameter system. This paper proposes a new VSS (Variable Structure System) robust adaptive control system including a self-tuning controller for a rotary inverted pendulum whose whole parameters are unknown. The control system prepares two kinds of adaptive controllers, and the stabilization of inverted pendulum is achieved by separating the system to two parts of the pendulum and the rotary arm. The rotational angle of the pendulum is stabilized by tracking type's VSS adaptive control method, and the rotary arm is simultaneously stabilized by STC (self-tuning control) system that assures the boundary reference angle of the pendulum. It is then not sufficient to construct STC system by using only adjustable parameter of VSS adaptive control system. Therefore, whole basic parameters are recursively estimated in order to realize STC system by using least squares parameter adaptive law, and it is achieved by superposing the perturbation signal to the stable adaptive control input on limited short interval. Furthermore, STC system designs LQ controller by developing an efficient QR method for real time operation. Finally, the validity of the proposed system is demonstrated through some numerical simulations and practical experimental result.

  9. An adaptive locally optimal method detecting weak deterministic signals

    NASA Astrophysics Data System (ADS)

    Wang, C. H.

    1983-10-01

    A new method for detecting weak signals in interference and clutter in radar systems is presented. The detector which uses this method is adaptive for an environment varying with time and locally optimal for detecting targets and constant false-alarm ratio (CFAR) for the statistics of interference and clutter varying with time. The loss of CFAR is small, and the detector is also simple in structure. The statistical equivalent transfer characteristic of a rank quantizer which can be used as part of an adaptive locally most powerful detector (ALMP) is obtained. It is shown that the distribution-free Doppler processor of Dillard (1974) is not only a nonparameter detector, but also an ALMP detector under certain conditions.

  10. Adaptive Plasticity in Wild Field Cricket’s Acoustic Signaling

    PubMed Central

    Bertram, Susan M.; Harrison, Sarah J.; Thomson, Ian R.; Fitzsimmons, Lauren P.

    2013-01-01

    Phenotypic plasticity can be adaptive when phenotypes are closely matched to changes in the environment. In crickets, rhythmic fluctuations in the biotic and abiotic environment regularly result in diel rhythms in density of sexually active individuals. Given that density strongly influences the intensity of sexual selection, we asked whether crickets exhibit plasticity in signaling behavior that aligns with these rhythmic fluctuations in the socio-sexual environment. We quantified the acoustic mate signaling behavior of wild-caught males of two cricket species, Gryllus veletis and G. pennsylvanicus. Crickets exhibited phenotypically plastic mate signaling behavior, with most males signaling more often and more attractively during the times of day when mating activity is highest in the wild. Most male G. pennsylvanicus chirped more often and louder, with shorter interpulse durations, pulse periods, chirp durations, and interchirp durations, and at slightly higher carrier frequencies during the time of the day that mating activity is highest in the wild. Similarly, most male G. veletis chirped more often, with more pulses per chirp, longer interpulse durations, pulse periods, and chirp durations, shorter interchirp durations, and at lower carrier frequencies during the time of peak mating activity in the wild. Among-male variation in signaling plasticity was high, with some males signaling in an apparently maladaptive manner. Body size explained some of the among-male variation in G. pennsylvanicus plasticity but not G. veletis plasticity. Overall, our findings suggest that crickets exhibit phenotypically plastic mate attraction signals that closely match the fluctuating socio-sexual context they experience. PMID:23935965

  11. Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Boskovic, Jovan D.

    2008-01-01

    This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.

  12. New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties- comparative study.

    PubMed

    Alavandar, Srinivasan; Nigam, M J

    2009-10-01

    Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. In this paper, some new hybrid adaptive neuro-fuzzy control algorithms (ANFIS) have been proposed for manipulator control with uncertainties. These hybrid controllers consist of adaptive neuro-fuzzy controllers and conventional controllers. The outputs of these controllers are applied to produce the final actuation signal based on current position and velocity errors. Numerical simulation using the dynamic model of six DOF puma robot arm with uncertainties shows the effectiveness of the approach in trajectory tracking problems. Performance indices of RMS error, maximum error are used for comparison. It is observed that the hybrid adaptive neuro-fuzzy controllers perform better than only conventional/adaptive controllers and in particular hybrid controller structure consisting of adaptive neuro-fuzzy controller and critically damped inverse dynamics controller.

  13. Adaptive control of robotic manipulators with structural flexibility

    NASA Astrophysics Data System (ADS)

    Wu, Sijun

    The control problem of mechanically flexible systems was an important issue for the past decade due mainly to the growing needs for fast, precise manipulators in industry and space applications. In this thesis, stable, high precision, and high-bandwidth closed-loop tip position control of a one-link flexible robot was investigated. Two adaptive control methods are developed and studied. A non-dimensionalized dynamic model for the flexible robot arm is developed. Payload mass and moment of inertia are also considered in the modeling. It can be shown that with a set of strain gauge measurements, the payload mass and moment of inertia could be estimated. This provides a convenient tool to detect the variations of the payload, which is crucial for precision control. The lattice filter used in the tip position control of a flexible arm proves to be a good parameter identifier in the on-line identification of the robot due to its high convergence rate and noise rejection capability. Although the lattice filter is usualy designed for auto-regressive or moving-average processes, its applications are extended to include auto-regressive and moving-average processes. The proposed model reference adaptive inverse controller is in the form of a series type of model reference system. It differs from other model reference controller in that the forward controller is the identified systems inverse. Moreover, an additional control signal is applied which comes from a signal synthesis block to compensate the output tracking and parameter identification errors. Compared with other control techniques such as stable factorization and linear quadratic Gaussian, the predictive adaptive controller could provide faster control with reasonably low input energy level.

  14. Adaptive control system for gas producing wells

    SciTech Connect

    Fedor, Pashchenko; Sergey, Gulyaev; Alexander, Pashchenko

    2015-03-10

    Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation.

  15. Predictive Control of Speededness in Adaptive Testing

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    2009-01-01

    An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

  16. Robust Adaptive Control In Hilbert Space

    NASA Technical Reports Server (NTRS)

    Wen, John Ting-Yung; Balas, Mark J.

    1990-01-01

    Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.

  17. Robust adaptive control of HVDC systems

    SciTech Connect

    Reeve, J.; Sultan, M. )

    1994-07-01

    The transient performance of an HVDC power system is highly dependent on the parameters of the current/voltage regulators of the converter controls. In order to better accommodate changes in system structure or dc operating conditions, this paper introduces a new adaptive control strategy. The advantages of automatic tuning for continuous fine tuning are combined with predetermined gain scheduling in order to achieve robustness for large disturbances. Examples are provided for a digitally simulated back-to-back dc system.

  18. Adaptive Variable Bias Magnetic Bearing Control

    NASA Technical Reports Server (NTRS)

    Johnson, Dexter; Brown, Gerald V.; Inman, Daniel J.

    1998-01-01

    Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. With the existence of the bias current, even in no load conditions, there is always some power consumption. In aerospace applications, power consumption becomes an important concern. In response to this concern, an alternative magnetic bearing control method, called Adaptive Variable Bias Control (AVBC), has been developed and its performance examined. The AVBC operates primarily as a proportional-derivative controller with a relatively slow, bias current dependent, time-varying gain. The AVBC is shown to reduce electrical power loss, be nominally stable, and provide control performance similar to conventional bias control. Analytical, computer simulation, and experimental results are presented in this paper.

  19. Adapted Fuzzy Controller for Astronomical Telescope Tracking

    NASA Astrophysics Data System (ADS)

    Attia, Abdel-Fattah

    2004-04-01

    This paper presents a novel application of fuzzy logic (FL) controller driven by an adaptive fuzzy set (AFS) for position tracking of the telescope driven by electric motor. Also, the proposed FL controller, driven by AFS, is compared with a classical FL control, driven by a static fuzzy set (SFS). Both FL controllers algorithm use the position error and its rate of change as an input vector. The mathematical model of the telescope driven by electric motor is highly nonlinear differential equations. Therefore the use of the artificial intelligent controller, such as FL is much better than the conventional controller, to cover a wide range of operating conditions. So, the output of FL control is utilized to force the electric drives, of the telescope, to satisfy a perfect matching of the predefined desired position of the telescope arms. Both of FL controllers, using AFS and SFS, are simulated and tested when the system is subjected to a step change in reference value. In addition, these simulation results are compared with the conventional Proportional-Derivative (PD) controller, driven by fixed gain. The proposed FL, using an adaptive fuzzy set, improve the dynamic response of the overall system by improving the damping coefficient and decreasing the rise time and settling time compared with other two controllers.

  20. Modeling and adaptive control of acoustic noise

    NASA Astrophysics Data System (ADS)

    Venugopal, Ravinder

    Active noise control is a problem that receives significant attention in many areas including aerospace and manufacturing. The advent of inexpensive high performance processors has made it possible to implement real-time control algorithms to effect active noise control. Both fixed-gain and adaptive methods may be used to design controllers for this problem. For fixed-gain methods, it is necessary to obtain a mathematical model of the system to design controllers. In addition, models help us gain phenomenological insights into the dynamics of the system. Models are also necessary to perform numerical simulations. However, models are often inadequate for the purpose of controller design because they involve parameters that are difficult to determine and also because there are always unmodeled effects. This fact motivates the use of adaptive algorithms for control since adaptive methods usually require significantly less model information than fixed-gain methods. The first part of this dissertation deals with derivation of a state space model of a one-dimensional acoustic duct. Two types of actuation, namely, a side-mounted speaker (interior control) and an end-mounted speaker (boundary control) are considered. The techniques used to derive the model of the acoustic duct are extended to the problem of fluid surface wave control. A state space model of small amplitude surfaces waves of a fluid in a rectangular container is derived and two types of control methods, namely, surface pressure control and map actuator based control are proposed and analyzed. The second part of this dissertation deals with the development of an adaptive disturbance rejection algorithm that is applied to the problem of active noise control. ARMARKOV models which have the same structure as predictor models are used for system representation. The algorithm requires knowledge of only one path of the system, from control to performance, and does not require a measurement of the disturbance nor

  1. Blending Gyro Signals To Improve Control Stability

    NASA Technical Reports Server (NTRS)

    Lee, J. F. L.

    1986-01-01

    Interference by structural vibrations reduced by adding signals from spatially separated gyros. Technique involves blending signals from rate gyroscopes located at different parts of structure to obtain composite signal that more nearly represents rotation of entire structure. Aircraft vibrations perpendicular to pitch axis contribute to rotations sensed by pitch-rate gyros. Proper blending of signals from gyros suppress contribution of dominant vibrational mode. Most likely applications of concept are flight-control systems for aircraft.

  2. Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

    NASA Astrophysics Data System (ADS)

    Engel, E.; Kovalev, I. V.; Kobezhicov, V.

    2015-10-01

    This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

  3. Adaptive control of Space Station with control moment gyros

    NASA Technical Reports Server (NTRS)

    Bishop, Robert H.; Paynter, Scott J.; Sunkel, John W.

    1992-01-01

    An adaptive approach to Space Station attitude control is investigated. The main components of the controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is a full-state feedback space station baseline control law. The control gain calculation is based on linear-quadratic regulator theory with eigenvalues placement in a vertical strip. The parameter identification scheme is a recursive extended Kalman filter that estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to estimate Space Station inertias accurately during nominal control moment gyro operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.

  4. Adaptive control strategies for flexible robotic arm

    NASA Technical Reports Server (NTRS)

    Bialasiewicz, Jan T.

    1993-01-01

    The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity if not unstable closed-loop behavior. Therefore a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

  5. Decentralized adaptive control of robot manipulators with robust stabilization design

    NASA Technical Reports Server (NTRS)

    Yuan, Bau-San; Book, Wayne J.

    1988-01-01

    Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.

  6. Adaptive Input Reconstruction with Application to Model Refinement, State Estimation, and Adaptive Control

    NASA Astrophysics Data System (ADS)

    D'Amato, Anthony M.

    Input reconstruction is the process of using the output of a system to estimate its input. In some cases, input reconstruction can be accomplished by determining the output of the inverse of a model of the system whose input is the output of the original system. Inversion, however, requires an exact and fully known analytical model, and is limited by instabilities arising from nonminimum-phase zeros. The main contribution of this work is a novel technique for input reconstruction that does not require model inversion. This technique is based on a retrospective cost, which requires a limited number of Markov parameters. Retrospective cost input reconstruction (RCIR) does not require knowledge of nonminimum-phase zero locations or an analytical model of the system. RCIR provides a technique that can be used for model refinement, state estimation, and adaptive control. In the model refinement application, data are used to refine or improve a model of a system. It is assumed that the difference between the model output and the data is due to an unmodeled subsystem whose interconnection with the modeled system is inaccessible, that is, the interconnection signals cannot be measured and thus standard system identification techniques cannot be used. Using input reconstruction, these inaccessible signals can be estimated, and the inaccessible subsystem can be fitted. We demonstrate input reconstruction in a model refinement framework by identifying unknown physics in a space weather model and by estimating an unknown film growth in a lithium ion battery. The same technique can be used to obtain estimates of states that cannot be directly measured. Adaptive control can be formulated as a model-refinement problem, where the unknown subsystem is the idealized controller that minimizes a measured performance variable. Minimal modeling input reconstruction for adaptive control is useful for applications where modeling information may be difficult to obtain. We demonstrate

  7. Adaptable and adaptive materials for light flux control

    NASA Astrophysics Data System (ADS)

    Sixou, Pierre; Magnaldo, A.; Nourry, J.; Laye, C.

    1996-04-01

    The purpose of this paper is to describe and examine properties of light flux control materials. Indeed, intelligent light flux control is necessary not only to improve everyday visual convenience but also in an economical point of view in order to reduce global home energetic cost. Several types of materials are good potential candidates for such functions: (1) The most well-known investigations concern inorganic materials such as tungsten or molybdenum oxides in which an electrochrom layer darkens when enriched in ions, and looses its color when impoverished. Unfortunately, at the moment, there is no convenient way to realize correct ions suppliers. Moreover, other drawbacks arise, such as poor reversibility, reactive interferences or a sensitivity of the material to its environment. These systems only need a low voltage level to work. But, their dynamic response, which is correlated to the component surface, is quite long. (2) At the present time, another attractive issue seems promising. More and more studies concern micro-composite liquid crystal films. For first, we shall remind their principles as well as their way of preparation. After having talked about their main advantages as intelligent materials, we shall discuss their control, their light flux adaptability, or their memory capabilities.

  8. Parallel computations and control of adaptive structures

    NASA Technical Reports Server (NTRS)

    Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)

    1991-01-01

    The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.

  9. Robust stochastic resonance: Signal detection and adaptation in impulsive noise

    NASA Astrophysics Data System (ADS)

    Kosko, Bart; Mitaim, Sanya

    2001-11-01

    Stochastic resonance (SR) occurs when noise improves a system performance measure such as a spectral signal-to-noise ratio or a cross-correlation measure. All SR studies have assumed that the forcing noise has finite variance. Most have further assumed that the noise is Gaussian. We show that SR still occurs for the more general case of impulsive or infinite-variance noise. The SR effect fades as the noise grows more impulsive. We study this fading effect on the family of symmetric α-stable bell curves that includes the Gaussian bell curve as a special case. These bell curves have thicker tails as the parameter α falls from 2 (the Gaussian case) to 1 (the Cauchy case) to even lower values. Thicker tails create more frequent and more violent noise impulses. The main feedback and feedforward models in the SR literature show this fading SR effect for periodic forcing signals when we plot either the signal-to-noise ratio or a signal correlation measure against the dispersion of the α-stable noise. Linear regression shows that an exponential law γopt(α)=cAα describes this relation between the impulsive index α and the SR-optimal noise dispersion γopt. The results show that SR is robust against noise ``outliers.'' So SR may be more widespread in nature than previously believed. Such robustness also favors the use of SR in engineering systems. We further show that an adaptive system can learn the optimal noise dispersion for two standard SR models (the quartic bistable model and the FitzHugh-Nagumo neuron model) for the signal-to-noise ratio performance measure. This also favors practical applications of SR and suggests that evolution may have tuned the noise-sensitive parameters of biological systems.

  10. F-8C adaptive flight control laws

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Harvey, C. A.; Stein, G.; Carlson, D. N.; Hendrick, R. C.

    1977-01-01

    Three candidate digital adaptive control laws were designed for NASA's F-8C digital flyby wire aircraft. Each design used the same control laws but adjusted the gains with a different adaptative algorithm. The three adaptive concepts were: high-gain limit cycle, Liapunov-stable model tracking, and maximum likelihood estimation. Sensors were restricted to conventional inertial instruments (rate gyros and accelerometers) without use of air-data measurements. Performance, growth potential, and computer requirements were used as criteria for selecting the most promising of these candidates for further refinement. The maximum likelihood concept was selected primarily because it offers the greatest potential for identifying several aircraft parameters and hence for improved control performance in future aircraft application. In terms of identification and gain adjustment accuracy, the MLE design is slightly superior to the other two, but this has no significant effects on the control performance achievable with the F-8C aircraft. The maximum likelihood design is recommended for flight test, and several refinements to that design are proposed.

  11. Optogenetic control of intracellular signaling pathways.

    PubMed

    Zhang, Kai; Cui, Bianxiao

    2015-02-01

    Cells employ a plethora of signaling pathways to make their life-and-death decisions. Extensive genetic, biochemical, and physiological studies have led to the accumulation of knowledge about signaling components and their interactions within signaling networks. These conventional approaches, although useful, lack the ability to control the spatial and temporal aspects of signaling processes. The recently emerged optogenetic tools open exciting opportunities by enabling signaling regulation with superior temporal and spatial resolution, easy delivery, rapid reversibility, fewer off-target side effects, and the ability to dissect complex signaling networks. Here we review recent achievements in using light to control intracellular signaling pathways and discuss future prospects for the field, including integration of new genetic approaches into optogenetics.

  12. Optogenetic control of intracellular signaling pathways

    PubMed Central

    Zhang, Kai; Cui, Bianxiao

    2014-01-01

    Cells employ a plethora of signaling pathways to make their life-and-death decisions. Extensive genetic, biochemical, and physiological studies have led to the accumulation of knowledge about signaling components and their interactions within signaling networks. These conventional approaches, though useful, lack the ability to control the spatial and temporal aspects of signaling processes. The recently emerged optogenetic tools open up exciting opportunities by enabling signaling regulation with superior temporal and spatial resolution, easy delivery, rapid reversibility, fewer off-target side effects, and the ability to dissect complex signaling networks. Here we review recent achievements in using light to control intracellular signaling pathways, and discuss future prospects for the field, including integration of new genetic approaches into optogenetics. PMID:25529484

  13. TGF-β superfamily signaling in muscle and tendon adaptation to resistance exercise

    PubMed Central

    Gumucio, Jonathan P; Sugg, Kristoffer B; Mendias, Christopher L

    2015-01-01

    Numerous studies in muscle and tendon have identified a central role of the TGF-β superfamily of cytokines in the regulation of extracellular matrix growth and remodeling, protein degradation, and cell proliferation and differentiation. Here we provide a novel framework for TGF-β and myostatin signaling in controlling the coordinated adaptation of both skeletal muscle and tendon tissue to resistance training. PMID:25607281

  14. Model reference adaptive control of robots

    NASA Technical Reports Server (NTRS)

    Steinvorth, Rodrigo

    1991-01-01

    This project presents the results of controlling two types of robots using new Command Generator Tracker (CGT) based Direct Model Reference Adaptive Control (MRAC) algorithms. Two mathematical models were used to represent a single-link, flexible joint arm and a Unimation PUMA 560 arm; and these were then controlled in simulation using different MRAC algorithms. Special attention was given to the performance of the algorithms in the presence of sudden changes in the robot load. Previously used CGT based MRAC algorithms had several problems. The original algorithm that was developed guaranteed asymptotic stability only for almost strictly positive real (ASPR) plants. This condition is very restrictive, since most systems do not satisfy this assumption. Further developments to the algorithm led to an expansion of the number of plants that could be controlled, however, a steady state error was introduced in the response. These problems led to the introduction of some modifications to the algorithms so that they would be able to control a wider class of plants and at the same time would asymptotically track the reference model. This project presents the development of two algorithms that achieve the desired results and simulates the control of the two robots mentioned before. The results of the simulations are satisfactory and show that the problems stated above have been corrected in the new algorithms. In addition, the responses obtained show that the adaptively controlled processes are resistant to sudden changes in the load.

  15. Adaptive integral dynamic surface control of a hypersonic flight vehicle

    NASA Astrophysics Data System (ADS)

    Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick

    2015-07-01

    In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.

  16. Adaptive control based on retrospective cost optimization

    NASA Technical Reports Server (NTRS)

    Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)

    2012-01-01

    A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

  17. Block adaptive rate controlled image data compression

    NASA Technical Reports Server (NTRS)

    Rice, R. F.; Hilbert, E.; Lee, J.-J.; Schlutsmeyer, A.

    1979-01-01

    A block adaptive rate controlled (BARC) image data compression algorithm is described. It is noted that in the algorithm's principal rate controlled mode, image lines can be coded at selected rates by combining practical universal noiseless coding techniques with block adaptive adjustments in linear quantization. Compression of any source data at chosen rates of 3.0 bits/sample and above can be expected to yield visual image quality with imperceptible degradation. Exact reconstruction will be obtained if the one-dimensional difference entropy is below the selected compression rate. It is noted that the compressor can also be operated as a floating rate noiseless coder by simply not altering the input data quantization. Here, the universal noiseless coder ensures that the code rate is always close to the entropy. Application of BARC image data compression to the Galileo orbiter mission of Jupiter is considered.

  18. Durham adaptive optics real-time controller.

    PubMed

    Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy

    2010-11-10

    The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems.

  19. Applying statistical process control to the adaptive rate control problem

    NASA Astrophysics Data System (ADS)

    Manohar, Nelson R.; Willebeek-LeMair, Marc H.; Prakash, Atul

    1997-12-01

    Due to the heterogeneity and shared resource nature of today's computer network environments, the end-to-end delivery of multimedia requires adaptive mechanisms to be effective. We present a framework for the adaptive streaming of heterogeneous media. We introduce the application of online statistical process control (SPC) to the problem of dynamic rate control. In SPC, the goal is to establish (and preserve) a state of statistical quality control (i.e., controlled variability around a target mean) over a process. We consider the end-to-end streaming of multimedia content over the internet as the process to be controlled. First, at each client, we measure process performance and apply statistical quality control (SQC) with respect to application-level requirements. Then, we guide an adaptive rate control (ARC) problem at the server based on the statistical significance of trends and departures on these measurements. We show this scheme facilitates handling of heterogeneous media. Last, because SPC is designed to monitor long-term process performance, we show that our online SPC scheme could be used to adapt to various degrees of long-term (network) variability (i.e., statistically significant process shifts as opposed to short-term random fluctuations). We develop several examples and analyze its statistical behavior and guarantees.

  20. Classification of transient signals using sparse representations over adaptive dictionaries

    NASA Astrophysics Data System (ADS)

    Moody, Daniela I.; Brumby, Steven P.; Myers, Kary L.; Pawley, Norma H.

    2011-06-01

    Automatic classification of broadband transient radio frequency (RF) signals is of particular interest in persistent surveillance applications. Because such transients are often acquired in noisy, cluttered environments, and are characterized by complex or unknown analytical models, feature extraction and classification can be difficult. We propose a fast, adaptive classification approach based on non-analytical dictionaries learned from data. Conventional representations using fixed (or analytical) orthogonal dictionaries, e.g., Short Time Fourier and Wavelet Transforms, can be suboptimal for classification of transients, as they provide a rigid tiling of the time-frequency space, and are not specifically designed for a particular signal class. They do not usually lead to sparse decompositions, and require separate feature selection algorithms, creating additional computational overhead. Pursuit-type decompositions over analytical, redundant dictionaries yield sparse representations by design, and work well for target signals in the same function class as the dictionary atoms. The pursuit search however has a high computational cost, and the method can perform poorly in the presence of realistic noise and clutter. Our approach builds on the image analysis work of Mairal et al. (2008) to learn a discriminative dictionary for RF transients directly from data without relying on analytical constraints or additional knowledge about the signal characteristics. We then use a pursuit search over this dictionary to generate sparse classification features. We demonstrate that our learned dictionary is robust to unexpected changes in background content and noise levels. The target classification decision is obtained in almost real-time via a parallel, vectorized implementation.

  1. Adaptive pitch control for variable speed wind turbines

    DOEpatents

    Johnson, Kathryn E.; Fingersh, Lee Jay

    2012-05-08

    An adaptive method for adjusting blade pitch angle, and controllers implementing such a method, for achieving higher power coefficients. Average power coefficients are determined for first and second periods of operation for the wind turbine. When the average power coefficient for the second time period is larger than for the first, a pitch increment, which may be generated based on the power coefficients, is added (or the sign is retained) to the nominal pitch angle value for the wind turbine. When the average power coefficient for the second time period is less than for the first, the pitch increment is subtracted (or the sign is changed). A control signal is generated based on the adapted pitch angle value and sent to blade pitch actuators that act to change the pitch angle of the wind turbine to the new or modified pitch angle setting, and this process is iteratively performed.

  2. Adaptive and aberrant reward prediction signals in the human brain.

    PubMed

    Roiser, Jonathan P; Stephan, Klaas E; den Ouden, Hanneke E M; Friston, Karl J; Joyce, Eileen M

    2010-04-01

    Theories of the positive symptoms of schizophrenia hypothesize a role for aberrant reinforcement signaling driven by dysregulated dopamine transmission. Recently, we provided evidence of aberrant reward learning in symptomatic, but not asymptomatic patients with schizophrenia, using a novel paradigm, the Salience Attribution Test (SAT). The SAT is a probabilistic reward learning game that employs cues that vary across task-relevant and task-irrelevant dimensions; it provides behavioral indices of adaptive and aberrant reward learning. As an initial step prior to future clinical studies, here we used functional magnetic resonance imaging to examine the neural basis of adaptive and aberrant reward learning during the SAT in healthy volunteers. As expected, cues associated with high relative to low reward probabilities elicited robust hemodynamic responses in a network of structures previously implicated in motivational salience; the midbrain, in the vicinity of the ventral tegmental area, and regions targeted by its dopaminergic projections, i.e. medial dorsal thalamus, ventral striatum and prefrontal cortex (PFC). Responses in the medial dorsal thalamus and polar PFC were strongly correlated with the degree of adaptive reward learning across participants. Finally, and most importantly, differential dorsolateral PFC and middle temporal gyrus (MTG) responses to cues with identical reward probabilities were very strongly correlated with the degree of aberrant reward learning. Participants who showed greater aberrant learning exhibited greater dorsolateral PFC responses, and reduced MTG responses, to cues erroneously inferred to be less strongly associated with reward. The results are discussed in terms of their implications for different theories of associative learning. PMID:19969090

  3. Adaptation with disturbance attenuation in nonlinear control systems

    SciTech Connect

    Basar, T.

    1997-12-31

    We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.

  4. Genetic Adaptive Control for PZT Actuators

    NASA Technical Reports Server (NTRS)

    Kim, Jeongwook; Stover, Shelley K.; Madisetti, Vijay K.

    1995-01-01

    A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.

  5. Adaptive multimode signal reconstruction from time–frequency representations

    PubMed Central

    Meignen, Sylvain; Oberlin, Thomas; Depalle, Philippe; Flandrin, Patrick

    2016-01-01

    This paper discusses methods for the adaptive reconstruction of the modes of multicomponent AM–FM signals by their time–frequency (TF) representation derived from their short-time Fourier transform (STFT). The STFT of an AM–FM component or mode spreads the information relative to that mode in the TF plane around curves commonly called ridges. An alternative view is to consider a mode as a particular TF domain termed a basin of attraction. Here we discuss two new approaches to mode reconstruction. The first determines the ridge associated with a mode by considering the location where the direction of the reassignment vector sharply changes, the technique used to determine the basin of attraction being directly derived from that used for ridge extraction. A second uses the fact that the STFT of a signal is fully characterized by its zeros (and then the particular distribution of these zeros for Gaussian noise) to deduce an algorithm to compute the mode domains. For both techniques, mode reconstruction is then carried out by simply integrating the information inside these basins of attraction or domains. PMID:26953184

  6. Evolutionary Adaptive Discovery of Phased Array Sensor Signal Identification

    SciTech Connect

    Timothy R. McJunkin; Milos Manic

    2011-05-01

    Tomography, used to create images of the internal properties and features of an object, from phased array ultasonics is improved through many sophisiticated methonds of post processing of data. One approach used to improve tomographic results is to prescribe the collection of more data, from different points of few so that data fusion might have a richer data set to work from. This approach can lead to rapid increase in the data needed to be stored and processed. It also does not necessarily lead to have the needed data. This article describes a novel approach to utilizing the data aquired as a basis for adapting the sensors focusing parameters to locate more precisely the features in the material: specifically, two evolutionary methods of autofocusing on a returned signal are coupled with the derivations of the forumulas for spatially locating the feature are given. Test results of the two novel methods of evolutionary based focusing (EBF) illustrate the improved signal strength and correction of the position of feature using the optimized focal timing parameters, called Focused Delay Identification (FoDI).

  7. Direct model reference adaptive control of a flexible robotic manipulator

    NASA Technical Reports Server (NTRS)

    Meldrum, D. R.

    1985-01-01

    Quick, precise control of a flexible manipulator in a space environment is essential for future Space Station repair and satellite servicing. Numerous control algorithms have proven successful in controlling rigid manipulators wih colocated sensors and actuators; however, few have been tested on a flexible manipulator with noncolocated sensors and actuators. In this thesis, a model reference adaptive control (MRAC) scheme based on command generator tracker theory is designed for a flexible manipulator. Quicker, more precise tracking results are expected over nonadaptive control laws for this MRAC approach. Equations of motion in modal coordinates are derived for a single-link, flexible manipulator with an actuator at the pinned-end and a sensor at the free end. An MRAC is designed with the objective of controlling the torquing actuator so that the tip position follows a trajectory that is prescribed by the reference model. An appealing feature of this direct MRAC law is that it allows the reference model to have fewer states than the plant itself. Direct adaptive control also adjusts the controller parameters directly with knowledge of only the plant output and input signals.

  8. Road map to adaptive optimal control. [jet engine control

    NASA Technical Reports Server (NTRS)

    Boyer, R.

    1980-01-01

    A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

  9. A Methodology for Investigating Adaptive Postural Control

    NASA Technical Reports Server (NTRS)

    McDonald, P. V.; Riccio, G. E.

    1999-01-01

    Our research on postural control and human-environment interactions provides an appropriate scientific foundation for understanding the skill of mass handling by astronauts in weightless conditions (e.g., extravehicular activity or EVA). We conducted an investigation of such skills in NASA's principal mass-handling simulator, the Precision Air-Bearing Floor, at the Johnson Space Center. We have studied skilled movement-body within a multidisciplinary context that draws on concepts and methods from biological and behavioral sciences (e.g., psychology, kinesiology and neurophysiology) as well as bioengineering. Our multidisciplinary research has led to the development of measures, for manual interactions between individuals and the substantial environment, that plausibly are observable by human sensory systems. We consider these methods to be the most important general contribution of our EVA investigation. We describe our perspective as control theoretic because it draws more on fundamental concepts about control systems in engineering than it does on working constructs from the subdisciplines of biomechanics and motor control in the bio-behavioral sciences. At the same time, we have attempted to identify the theoretical underpinnings of control-systems engineering that are most relevant to control by human beings. We believe that these underpinnings are implicit in the assumptions that cut across diverse methods in control-systems engineering, especially the various methods associated with "nonlinear control", "fuzzy control," and "adaptive control" in engineering. Our methods are based on these theoretical foundations rather than on the mathematical formalisms that are associated with particular methods in control-systems engineering. The most important aspects of the human-environment interaction in our investigation of mass handling are the functional consequences that body configuration and stability have for the pick up of information or the achievement of

  10. Adaptive and predictive control of a simulated robot arm.

    PubMed

    Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo

    2013-06-01

    In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs).

  11. Adaptive Accommodation Control Method for Complex Assembly

    NASA Astrophysics Data System (ADS)

    Kang, Sungchul; Kim, Munsang; Park, Shinsuk

    Robotic systems have been used to automate assembly tasks in manufacturing and in teleoperation. Conventional robotic systems, however, have been ineffective in controlling contact force in multiple contact states of complex assemblythat involves interactions between complex-shaped parts. Unlike robots, humans excel at complex assembly tasks by utilizing their intrinsic impedance, forces and torque sensation, and tactile contact clues. By examining the human behavior in assembling complex parts, this study proposes a novel geometry-independent control method for robotic assembly using adaptive accommodation (or damping) algorithm. Two important conditions for complex assembly, target approachability and bounded contact force, can be met by the proposed control scheme. It generates target approachable motion that leads the object to move closer to a desired target position, while contact force is kept under a predetermined value. Experimental results from complex assembly tests have confirmed the feasibility and applicability of the proposed method.

  12. Adaptations in adenosine signaling in drug dependence: therapeutic implications.

    PubMed

    Hack, Stephen P; Christie, Macdonald J

    2003-01-01

    Adenosine is an important endogenous purine neuromodulator in the central nervous system that modulates many important cellular processes in neurons. The physiological effects of adenosine are transduced through four pharmacologically classified receptor types i.e., A1, A2A, A2B and A3. All adenosine receptors are G-protein coupled receptors (GPCR) of the type 1 variety. Adaptations in adenosine signaling have been implicated in a wide range of pathophysiological processes, such as epilepsies, sleep disorders, pain, and drug addictions. Knowledge relating to the etiology of addictive processes is far from complete, and as a result the therapeutic options to deal with drug dependence issues are limited. Drugs of abuse mediate their effects through many distinct cellular effectors, such as neurotransmitter transporters, ion channels, and receptor proteins. However, a unifying feature of the major drugs of abuse-i.e., opiates, cocaine, and alcohol-is that they all directly or indirectly modulate adenosine signaling in neurons. Agents targeting adenosine receptors may therefore offer novel avenues for the development of therapies to manage or treat addictions. A consistent cellular adaptation to long-term drug use is the up- or down-regulation of signaling pathways driven by adenylyl cyclase/cyclic AMP (cAMP) in several brain regions linked to addiction. Withdrawal from mu-opioids or cocaine following their chronic administration leads to an upregulation of adenylyl cyclase-mediated signaling, resulting in high levels of cAMP. Cyclic AMP produced in this way acts as a substrate for the endogenous production of adenosine. Increased levels of endogenous adenosine interact with presynaptic A1 receptors to inhibit the excessive neuronal excitation often seen during morphine/cocaine withdrawal. These pre-clinical findings fit well with other data indicating that drugs which boost endogenous adenosine levels or directly interact with inhibitory A1 receptors can alleviate

  13. Distributed traffic signal control using fuzzy logic

    NASA Technical Reports Server (NTRS)

    Chiu, Stephen

    1992-01-01

    We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.

  14. Controlling cluster synchronization by adapting the topology.

    PubMed

    Lehnert, Judith; Hövel, Philipp; Selivanov, Anton; Fradkov, Alexander; Schöll, Eckehard

    2014-10-01

    We suggest an adaptive control scheme for the control of in-phase and cluster synchronization in delay-coupled networks. Based on the speed-gradient method, our scheme adapts the topology of a network such that the target state is realized. It is robust towards different initial conditions as well as changes in the coupling parameters. The emerging topology is characterized by a delicate interplay of excitatory and inhibitory links leading to the stabilization of the desired cluster state. As a crucial parameter determining this interplay we identify the delay time. Furthermore, we show how to construct networks such that they exhibit not only a given cluster state but also with a given oscillation frequency. We apply our method to coupled Stuart-Landau oscillators, a paradigmatic normal form that naturally arises in an expansion of systems close to a Hopf bifurcation. The successful and robust control of this generic model opens up possible applications in a wide range of systems in physics, chemistry, technology, and life science.

  15. Kalman filter based control for Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Petit, Cyril; Quiros-Pacheco, Fernando; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

    2004-12-01

    Classical Adaptive Optics suffer from a limitation of the corrected Field Of View. This drawback has lead to the development of MultiConjugated Adaptive Optics. While the first MCAO experimental set-ups are presently under construction, little attention has been paid to the control loop. This is however a key element in the optimization process especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications : simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering which seems a very promising solution. Following the work of Brice Leroux, we focus on a frequential characterization of kalman filters, computing a transfer matrix. The result brings much information about their behaviour and allows comparisons with classical controllers. It also appears that straightforward improvements of the system models can lead to static aberrations and vibrations filtering. Simulation results are proposed and analysed thanks to our frequential characterization. Related problems such as model errors, aliasing effect reduction or experimental implementation and testing of Kalman filter control loop on a simplified MCAO experimental set-up could be then discussed.

  16. Adaptive control: Stability, convergence, and robustness

    NASA Technical Reports Server (NTRS)

    Sastry, Shankar; Bodson, Marc

    1989-01-01

    The deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers. Chapters are devoted to basic AC approaches, notation and fundamental theorems, the identification problem, model-reference AC, parameter convergence using averaging techniques, and AC robustness. Consideration is given to the use of prior information, the global stability of indirect AC schemes, multivariable AC, linearizing AC for a class of nonlinear systems, AC of linearizable minimum-phase systems, and MIMO systems decouplable by static state feedback.

  17. Adaptive method with intercessory feedback control for an intelligent agent

    DOEpatents

    Goldsmith, Steven Y.

    2004-06-22

    An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

  18. Dynamic range control of audio signals by digital signal processing

    NASA Astrophysics Data System (ADS)

    Gilchrist, N. H. C.

    It is often necessary to reduce the dynamic range of musical programs, particularly those comprising orchestral and choral music, for them to be received satisfactorily by listeners to conventional FM and AM broadcasts. With the arrival of DAB (Digital Audio Broadcasting) a much wider dynamic range will become available for radio broadcasting, although some listeners may prefer to have a signal with a reduced dynamic range. This report describes a digital processor developed by the BBC to control the dynamic range of musical programs in a manner similar to that of a trained Studio Manager. It may be used prior to transmission in conventional broadcasting, replacing limiters or other compression equipment. In DAB, it offers the possibility of providing a dynamic range control signal to be sent to the receiver via an ancillary data channel, simultaneously with the uncompressed audio, giving the listener the option of the full dynamic range or a reduced dynamic range.

  19. Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

  20. Adaptive vibration control using synchronous demodulation with machine tool controller motor commutation

    DOEpatents

    Hopkins, David James

    2008-05-13

    A control system and method for actively reducing vibration in a spindle housing caused by unbalance forces on a rotating spindle, by measuring the force-induced spindle-housing motion, determining control signals based on synchronous demodulation, and provide compensation for the measured displacement to cancel or otherwise reduce or attenuate the vibration. In particular, the synchronous demodulation technique is performed to recover a measured spindle housing displacement signal related only to the rotation of a machine tool spindle, and consequently rejects measured displacement not related to spindle motion or synchronous to a cycle of revolution. Furthermore, the controller actuates at least one voice-coil (VC) motor, to cancel the original force-induced motion, and adapts the magnitude of voice coil signal until this measured displacement signal is brought to a null. In order to adjust the signal to a null, it must have the correct phase relative to the spindle angle. The feedback phase signal is used to adjust a common (to both outputs) commutation offset register (offset relative to spindle encoder angle) to force the feedback phase signal output to a null. Once both of these feedback signals are null, the system is compensating properly for the spindle-induced motion.

  1. The reduced order model problem in distributed parameter systems adaptive identification and control. [adaptive control of flexible spacecraft

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Lawrence, D. A.

    1981-01-01

    The reduced order model problem in distributed parameter systems adaptive identification and control is investigated. A comprehensive examination of real-time centralized adaptive control options for flexible spacecraft is provided.

  2. Wavefront Control for Extreme Adaptive Optics

    SciTech Connect

    Poyneer, L A

    2003-07-16

    Current plans for Extreme Adaptive Optics systems place challenging requirements on wave-front control. This paper focuses on control system dynamics, wave-front sensing and wave-front correction device characteristics. It may be necessary to run an ExAO system after a slower, low-order AO system. Running two independent systems can result in very good temporal performance, provided specific design constraints are followed. The spatially-filtered wave-front sensor, which prevents aliasing and improves PSF sensitivity, is summarized. Different models of continuous and segmented deformable mirrors are studied. In a noise-free case, a piston-tip-tilt segmented MEMS device can achieve nearly equivalent performance to a continuous-sheet DM in compensating for a static phase aberration with use of spatial filtering.

  3. Adaptive Control of Flexible Structures Using Residual Mode Filters

    NASA Technical Reports Server (NTRS)

    Balas, Mark J.; Frost, Susan

    2010-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

  4. Real-time Adaptive Control Using Neural Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  5. Adaptive myoelectric pattern recognition toward improved multifunctional prosthesis control.

    PubMed

    Liu, Jie

    2015-04-01

    The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications.

  6. Cognitive Control Signals for Neural Prosthetics

    NASA Astrophysics Data System (ADS)

    Musallam, S.; Corneil, B. D.; Greger, B.; Scherberger, H.; Andersen, R. A.

    2004-07-01

    Recent development of neural prosthetics for assisting paralyzed patients has focused on decoding intended hand trajectories from motor cortical neurons and using this signal to control external devices. In this study, higher level signals related to the goals of movements were decoded from three monkeys and used to position cursors on a computer screen without the animals emitting any behavior. Their performance in this task improved over a period of weeks. Expected value signals related to fluid preference, the expected magnitude, or probability of reward were decoded simultaneously with the intended goal. For neural prosthetic applications, the goal signals can be used to operate computers, robots, and vehicles, whereas the expected value signals can be used to continuously monitor a paralyzed patient's preferences and motivation.

  7. Adaptive Training of Manual Control: 1. Comparison of Three Adaptive Variables and Two Logic Schemes.

    ERIC Educational Resources Information Center

    Norman, D. A.; And Others

    "Machine controlled adaptive training is a promising concept. In adaptive training the task presented to the trainee varies as a function of how well he performs. In machine controlled training, adaptive logic performs a function analogous to that performed by a skilled operator." This study looks at the ways in which gain-effective time constant…

  8. Adaptive dynamic programming as a theory of sensorimotor control.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-08-01

    Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment.

  9. Adaptive dynamic programming as a theory of sensorimotor control.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-08-01

    Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment. PMID:24962078

  10. Comparison of adaptive algorithms for the control of tonal disturbances in mechanical systems

    NASA Astrophysics Data System (ADS)

    Zilletti, M.; Elliott, S. J.; Cheer, J.

    2016-09-01

    This paper presents a study on the performance of adaptive control algorithms designed to reduce the vibration of mechanical systems excited by a harmonic disturbance. The mechanical system consists of a mass suspended on a spring and a damper. The system is equipped with a force actuator in parallel with the suspension. The control signal driving the actuator is generated by adjusting the amplitude and phase of a sinusoidal reference signal at the same frequency as the excitation. An adaptive feedforward control algorithm is used to adapt the amplitude and phase of the control signal, to minimise the mean square velocity of the mass. Two adaptation strategies are considered in which the control signal is either updated after each period of the oscillation or at every time sample. The first strategy is traditionally used in vibration control in helicopters for example; the second strategy is normally referred to as the filtered-x least mean square algorithm and is often used to control engine noise in cars. The two adaptation strategies are compared through a parametric study, which investigates the influence of the properties of both the mechanical system and the control system on the convergence speed of the two algorithms.

  11. Adaptive powertrain control for plugin hybrid electric vehicles

    DOEpatents

    Kedar-Dongarkar, Gurunath; Weslati, Feisel

    2013-10-15

    A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

  12. Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.

    PubMed

    Fei, Juntao; Zhou, Jian

    2012-12-01

    In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.

  13. Robust adaptive vibration control of a flexible structure.

    PubMed

    Khoshnood, A M; Moradi, H M

    2014-07-01

    Different types of L1 adaptive control systems show that using robust theories with adaptive control approaches has produced high performance controllers. In this study, a model reference adaptive control scheme considering robust theories is used to propose a practical control system for vibration suppression of a flexible launch vehicle (FLV). In this method, control input of the system is shaped from the dynamic model of the vehicle and components of the control input are adaptively constructed by estimating the undesirable vibration frequencies. Robust stability of the adaptive vibration control system is guaranteed by using the L1 small gain theorem. Simulation results of the robust adaptive vibration control strategy confirm that the effects of vibration on the vehicle performance considerably decrease without the loss of the phase margin of the system.

  14. Direct adaptive control of manipulators in Cartesian space

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1987-01-01

    A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

  15. A new adaptive configuration of PID type fuzzy logic controller.

    PubMed

    Fereidouni, Alireza; Masoum, Mohammad A S; Moghbel, Moayed

    2015-05-01

    In this paper, an adaptive configuration for PID type fuzzy logic controller (FLC) is proposed to improve the performances of both conventional PID (C-PID) controller and conventional PID type FLC (C-PID-FLC). The proposed configuration is called adaptive because its output scaling factors (SFs) are dynamically tuned while the controller is functioning. The initial values of SFs are calculated based on its well-tuned counterpart while the proceeding values are generated using a proposed stochastic hybrid bacterial foraging particle swarm optimization (h-BF-PSO) algorithm. The performance of the proposed configuration is evaluated through extensive simulations for different operating conditions (changes in reference, load disturbance and noise signals). The results reveal that the proposed scheme performs significantly better over the C-PID controller and the C-PID-FLC in terms of several performance indices (integral absolute error (IAE), integral-of-time-multiplied absolute error (ITAE) and integral-of-time-multiplied squared error (ITSE)), overshoot and settling time for plants with and without dead time.

  16. Mitochondrial adaptations to utilize hydrogen sulfide for energy and signaling.

    PubMed

    Olson, Kenneth R

    2012-10-01

    Sulfur is a versatile molecule with oxidation states ranging from -2 to +6. From the beginning, sulfur has been inexorably entwined with the evolution of organisms. Reduced sulfur, prevalent in the prebiotic Earth and supplied from interstellar sources, was an integral component of early life as it could provide energy through oxidization, even in a weakly oxidizing environment, and it spontaneously reacted with iron to form iron-sulfur clusters that became the earliest biological catalysts and structural components of cells. The ability to cycle sulfur between reduced and oxidized states may have been key in the great endosymbiotic event that incorporated a sulfide-oxidizing α-protobacteria into a host sulfide-reducing Archea, resulting in the eukaryotic cell. As eukaryotes slowly adapted from a sulfidic and anoxic (euxinic) world to one that was highly oxidizing, numerous mechanisms developed to deal with increasing oxidants; namely, oxygen, and decreasing sulfide. Because there is rarely any reduced sulfur in the present-day environment, sulfur was historically ignored by biologists, except for an occasional report of sulfide toxicity. Twenty-five years ago, it became evident that the organisms in sulfide-rich environments could synthesize ATP from sulfide, 10 years later came the realization that animals might use sulfide as a signaling molecule, and only within the last 4 years did it become apparent that even mammals could derive energy from sulfide generated in the gastrointestinal tract. It has also become evident that, even in the present-day oxic environment, cells can exploit the redox chemistry of sulfide, most notably as a physiological transducer of oxygen availability. This review will examine how the legacy of sulfide metabolism has shaped natural selection and how some of these ancient biochemical pathways are still employed by modern-day eukaryotes. PMID:22430869

  17. Noise Filtering Strategies in Adaptive Biochemical Signaling Networks. Application to E. Coli Chemotaxis

    NASA Astrophysics Data System (ADS)

    Sartori, Pablo; Tu, Yuhai

    2011-04-01

    Two distinct mechanisms for filtering noise in an input signal are identified in a class of adaptive sensory networks. We find that the high-frequency noise is filtered by the output degradation process through time-averaging; while the low-frequency noise is damped by adaptation through negative feedback. Both filtering processes themselves introduce intrinsic noises, which are found to be unfiltered and can thus amount to a significant internal noise floor even without signaling. These results are applied to E. coli chemotaxis. We show unambiguously that the molecular mechanism for the Berg-Purcell time-averaging scheme is the dephosphorylation of the response regulator CheY-P, not the receptor adaptation process as previously suggested. The high-frequency noise due to the stochastic ligand binding-unbinding events and the random ligand molecule diffusion is averaged by the CheY-P dephosphorylation process to a negligible level in E. coli. We identify a previously unstudied noise source caused by the random motion of the cell in a ligand gradient. We show that this random walk induced signal noise has a divergent low-frequency component, which is only rendered finite by the receptor adaptation process. For gradients within the E. coli sensing range, this dominant external noise can be comparable to the significant intrinsic noise in the system. The dependence of the response and its fluctuations on the key time scales of the system are studied systematically. We show that the chemotaxis pathway may have evolved to optimize gradient sensing, strong response, and noise control in different time scales.

  18. Perfect and Near-Perfect Adaptation in Cell Signaling.

    PubMed

    Ferrell, James E

    2016-02-24

    Adaptation is an important basic feature of cellular regulation. Previous theoretical work has identified three types of circuits-negative feedback loops, incoherent feedforward systems, and state-dependent inactivation systems-that can achieve perfect or near-perfect adaptation. Recent work has added another strategy, termed antithetic integral feedback, to the list of motifs capable of robust perfect adaptation. Here, we discuss the properties, limitations, and biological relevance of each of these circuits. PMID:27135159

  19. A survey of adaptive control technology in robotics

    NASA Technical Reports Server (NTRS)

    Tosunoglu, S.; Tesar, D.

    1987-01-01

    Previous work on the adaptive control of robotic systems is reviewed. Although the field is relatively new and does not yet represent a mature discipline, considerable attention has been given to the design of sophisticated robot controllers. Here, adaptive control methods are divided into model reference adaptive systems and self-tuning regulators with further definition of various approaches given in each class. The similarity and distinct features of the designed controllers are delineated and tabulated to enhance comparative review.

  20. Full-Scale Flight Research Testbeds: Adaptive and Intelligent Control

    NASA Technical Reports Server (NTRS)

    Pahle, Joe W.

    2008-01-01

    This viewgraph presentation describes the adaptive and intelligent control methods used for aircraft survival. The contents include: 1) Motivation for Adaptive Control; 2) Integrated Resilient Aircraft Control Project; 3) Full-scale Flight Assets in Use for IRAC; 4) NASA NF-15B Tail Number 837; 5) Gen II Direct Adaptive Control Architecture; 6) Limited Authority System; and 7) 837 Flight Experiments. A simulated destabilization failure analysis along with experience and lessons learned are also presented.

  1. Mitochondria-controlled signaling mechanisms of brain protection in hypoxia.

    PubMed

    Lukyanova, Ludmila D; Kirova, Yulia I

    2015-01-01

    The article is focused on the role of the cell bioenergetic apparatus, mitochondria, involved in development of immediate and delayed molecular mechanisms for adaptation to hypoxic stress in brain cortex. Hypoxia induces reprogramming of respiratory chain function and switching from oxidation of NAD-related substrates (complex I) to succinate oxidation (complex II). Transient, reversible, compensatory activation of respiratory chain complex II is a major mechanism of immediate adaptation to hypoxia necessary for (1) succinate-related energy synthesis in the conditions of oxygen deficiency and formation of urgent resistance in the body; (2) succinate-related stabilization of HIF-1α and initiation of its transcriptional activity related with formation of long-term adaptation; (3) succinate-related activation of the succinate-specific receptor, GPR91. This mechanism participates in at least four critical regulatory functions: (1) sensor function related with changes in kinetic properties of complex I and complex II in response to a gradual decrease in ambient oxygen concentration; this function is designed for selection of the most efficient pathway for energy substrate oxidation in hypoxia; (2) compensatory function focused on formation of immediate adaptive responses to hypoxia and hypoxic resistance of the body; (3) transcriptional function focused on activated synthesis of HIF-1 and the genes providing long-term adaptation to low pO2; (4) receptor function, which reflects participation of mitochondria in the intercellular signaling system via the succinate-dependent receptor, GPR91. In all cases, the desired result is achieved by activation of the succinate-dependent oxidation pathway, which allows considering succinate as a signaling molecule. Patterns of mitochondria-controlled activation of GPR-91- and HIF-1-dependent reaction were considered, and a possibility of their participation in cellular-intercellular-systemic interactions in hypoxia and adaptation was

  2. Mitochondria-controlled signaling mechanisms of brain protection in hypoxia

    PubMed Central

    Lukyanova, Ludmila D.; Kirova, Yulia I.

    2015-01-01

    The article is focused on the role of the cell bioenergetic apparatus, mitochondria, involved in development of immediate and delayed molecular mechanisms for adaptation to hypoxic stress in brain cortex. Hypoxia induces reprogramming of respiratory chain function and switching from oxidation of NAD-related substrates (complex I) to succinate oxidation (complex II). Transient, reversible, compensatory activation of respiratory chain complex II is a major mechanism of immediate adaptation to hypoxia necessary for (1) succinate-related energy synthesis in the conditions of oxygen deficiency and formation of urgent resistance in the body; (2) succinate-related stabilization of HIF-1α and initiation of its transcriptional activity related with formation of long-term adaptation; (3) succinate-related activation of the succinate-specific receptor, GPR91. This mechanism participates in at least four critical regulatory functions: (1) sensor function related with changes in kinetic properties of complex I and complex II in response to a gradual decrease in ambient oxygen concentration; this function is designed for selection of the most efficient pathway for energy substrate oxidation in hypoxia; (2) compensatory function focused on formation of immediate adaptive responses to hypoxia and hypoxic resistance of the body; (3) transcriptional function focused on activated synthesis of HIF-1 and the genes providing long-term adaptation to low pO2; (4) receptor function, which reflects participation of mitochondria in the intercellular signaling system via the succinate-dependent receptor, GPR91. In all cases, the desired result is achieved by activation of the succinate-dependent oxidation pathway, which allows considering succinate as a signaling molecule. Patterns of mitochondria-controlled activation of GPR-91- and HIF-1-dependent reaction were considered, and a possibility of their participation in cellular-intercellular-systemic interactions in hypoxia and adaptation was

  3. An adaptive neuro-control system of synchronous generator for power system stabilization

    SciTech Connect

    Kobayashi, Takenori; Yokoyama, Akihiko

    1996-09-01

    This paper proposes a nonlinear adaptive generator control system using neural networks, called an adaptive neuro-control system (ANCS). This system generates supplementary control signals to conventional controllers and works adaptively in response to changes in operating conditions and network configuration. Through digital time simulations for a one-machine infinite bus test power system, the control performance of the ANCS and advanced controllers such as a linear optimal regulator and a self-tuning regulator is evaluated from the viewpoint of stability enhancement. As a result, the proposed ANCS using neural networks with nonlinear characteristics improves system damping more effectively and more adaptively than the other two controllers designed for the linearized model of the power system.

  4. Method for removing tilt control in adaptive optics systems

    DOEpatents

    Salmon, Joseph Thaddeus

    1998-01-01

    A new adaptive optics system and method of operation, whereby the method removes tilt control, and includes the steps of using a steering mirror to steer a wavefront in the desired direction, for aiming an impinging aberrated light beam in the direction of a deformable mirror. The deformable mirror has its surface deformed selectively by means of a plurality of actuators, and compensates, at least partially, for existing aberrations in the light beam. The light beam is split into an output beam and a sample beam, and the sample beam is sampled using a wavefront sensor. The sampled signals are converted into corresponding electrical signals for driving a controller, which, in turn, drives the deformable mirror in a feedback loop in response to the sampled signals, for compensating for aberrations in the wavefront. To this purpose, a displacement error (gradient) of the wavefront is measured, and adjusted by a modified gain matrix, which satisfies the following equation: G'=(I-X(X.sup.T X).sup.-1 X.sup.T)G(I-A)

  5. Method for removing tilt control in adaptive optics systems

    DOEpatents

    Salmon, J.T.

    1998-04-28

    A new adaptive optics system and method of operation are disclosed, whereby the method removes tilt control, and includes the steps of using a steering mirror to steer a wavefront in the desired direction, for aiming an impinging aberrated light beam in the direction of a deformable mirror. The deformable mirror has its surface deformed selectively by means of a plurality of actuators, and compensates, at least partially, for existing aberrations in the light beam. The light beam is split into an output beam and a sample beam, and the sample beam is sampled using a wavefront sensor. The sampled signals are converted into corresponding electrical signals for driving a controller, which, in turn, drives the deformable mirror in a feedback loop in response to the sampled signals, for compensating for aberrations in the wavefront. To this purpose, a displacement error (gradient) of the wavefront is measured, and adjusted by a modified gain matrix, which satisfies the following equation: G{prime} = (I{minus}X(X{sup T} X){sup {minus}1}X{sup T})G(I{minus}A). 3 figs.

  6. Adaptive neural control for a class of nonlinearly parametric time-delay systems.

    PubMed

    Ho, Daniel W C; Li, Junmin; Niu, Yugang

    2005-05-01

    In this paper, an adaptive neural controller for a class of time-delay nonlinear systems with unknown nonlinearities is proposed. Based on a wavelet neural network (WNN) online approximation model, a state feedback adaptive controller is obtained by constructing a novel integral-type Lyapunov-Krasovskii functional, which also efficiently overcomes the controller singularity problem. It is shown that the proposed method guarantees the semiglobal boundedness of all signals in the adaptive closed-loop systems. An example is provided to illustrate the application of the approach.

  7. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    NASA Astrophysics Data System (ADS)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  8. Adaptive Combining of Coherently Detected PPM Signals in the Presence of Atmospheric Turbulence

    NASA Technical Reports Server (NTRS)

    Fernandez, Michela Munoz; Vilnrotter, Victor A.

    2004-01-01

    Adaptive combining of experimentally obtained heterodyned pulse position modulated (PPM) signals with pulse-to-pulse coherence, in the presence of simulated spatial distortions resembling atmospheric turbulence, is demonstrated. The adaptively combined PPM signals are phased up via an LMS algorithm suitably optimized to operate with PPM in the presence of additive shot-noise. A convergence study of the algorithm is presented, and results with both computer simulated and experimentally obtained PPM signals are presented and analyzed.

  9. Adaptive Quality of Transmission Control in Elastic Optical Network

    NASA Astrophysics Data System (ADS)

    Cai, Xinran

    Optical fiber communication is becoming increasingly important due to the burgeoning demand in the internet capacity. However, traditional wavelength division multiplexing (WDM) technique fails to address such demand because of its inefficient spectral utilization. As a result, elastic optical networking (EON) has been under extensive investigation recently. Such network allows sub-wavelength and super-wavelength channel accommodation, and mitigates the stranded bandwidth problem in the WDM network. In addition, elastic optical network is also able to dynamically allocate the spectral resources of the network based on channel conditions and impairments, and adaptively control the quality of transmission of a channel. This application requires two aspects to be investigated: an efficient optical performance monitoring scheme and networking control and management algorithms to reconfigure the network in a dynamic fashion. This thesis focuses on the two aspects discussed above about adaptive QoT control. We demonstrated a supervisory channel method for optical signal to noise ratio (OSNR) and chromatic dispersion (CD) monitoring. In addition, our proof-of-principle testbed experiments show successful impairment aware reconfiguration of the network with modulation format switching (MFS) only and MFS combined with lightpath rerouting (LR) for hundred-GHz QPSK superchannels undergoing time-varying OSNR impairment.

  10. Optically Controlled Signal Amplification for DNA Computation.

    PubMed

    Prokup, Alexander; Hemphill, James; Liu, Qingyang; Deiters, Alexander

    2015-10-16

    The hybridization chain reaction (HCR) and fuel-catalyst cycles have been applied to address the problem of signal amplification in DNA-based computation circuits. While they function efficiently, these signal amplifiers cannot be switched ON or OFF quickly and noninvasively. To overcome these limitations, a light-activated initiator strand for the HCR, which enabled fast optical OFF → ON switching, was developed. Similarly, when a light-activated version of the catalyst strand or the inhibitor strand of a fuel-catalyst cycle was applied, the cycle could be optically switched from OFF → ON or ON → OFF, respectively. To move the capabilities of these devices beyond solution-based operations, the components were embedded in agarose gels. Irradiation with customizable light patterns and at different time points demonstrated both spatial and temporal control. The addition of a translator gate enabled a spatially activated signal to travel along a predefined path, akin to a chemical wire. Overall, the addition of small light-cleavable photocaging groups to DNA signal amplification circuits enabled conditional control as well as fast photocontrol of signal amplification. PMID:25621535

  11. Whole genome, whole population sequencing reveals that loss of signaling networks is the major adaptive strategy in a constant environment.

    PubMed

    Kvitek, Daniel J; Sherlock, Gavin

    2013-11-01

    Molecular signaling networks are ubiquitous across life and likely evolved to allow organisms to sense and respond to environmental change in dynamic environments. Few examples exist regarding the dispensability of signaling networks, and it remains unclear whether they are an essential feature of a highly adapted biological system. Here, we show that signaling network function carries a fitness cost in yeast evolving in a constant environment. We performed whole-genome, whole-population Illumina sequencing on replicate evolution experiments and find the major theme of adaptive evolution in a constant environment is the disruption of signaling networks responsible for regulating the response to environmental perturbations. Over half of all identified mutations occurred in three major signaling networks that regulate growth control: glucose signaling, Ras/cAMP/PKA and HOG. This results in a loss of environmental sensitivity that is reproducible across experiments. However, adaptive clones show reduced viability under starvation conditions, demonstrating an evolutionary tradeoff. These mutations are beneficial in an environment with a constant and predictable nutrient supply, likely because they result in constitutive growth, but reduce fitness in an environment where nutrient supply is not constant. Our results are a clear example of the myopic nature of evolution: a loss of environmental sensitivity in a constant environment is adaptive in the short term, but maladaptive should the environment change.

  12. Model Reference Adaptive H∞ Control for Distributed Parameter Systems of Hyperbolic Type with Input Nonlinearity by Finite Dimensional Controllers

    NASA Astrophysics Data System (ADS)

    Miyasato, Yoshihiko

    The problem of constructing model reference adaptive H∞ control for distributed parameter systems of hyperbolic type preceded by unknown input nonlinearity such as dead zone or backlash, is considered in this paper. Distributed parameter systems are infinite dimensional processes, but the proposed control scheme is constructed from finite dimensional controllers. An adaptive inverse model is introduced to estimate and compensate the input nonlinearity. The stabilizing control signal is added to regulate the effect of spill-over terms, and it is derived as a solution of certain H∞ control problem where the residual part of the inverse model and the spill-over term are considered as external disturbances to the process.

  13. Modular and Adaptive Control of Sound Processing

    NASA Astrophysics Data System (ADS)

    van Nort, Douglas

    parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.

  14. Note: On-line weak signal detection via adaptive stochastic resonance.

    PubMed

    Lu, Siliang; He, Qingbo; Kong, Fanrang

    2014-06-01

    We design an instrument with a novel embedded adaptive stochastic resonance (SR) algorithm that consists of a SR module and a digital zero crossing detection module for on-line weak signal detection in digital signal processing applications. The two modules are responsible for noise filtering and adaptive parameter configuration, respectively. The on-line weak signal detection can be stably achieved in seconds. The prototype instrument exhibits an advance of 20 dB averaged signal-to-noise ratio and 5 times averaged adjust R-square as compared to the input noisy signal, in considering different driving frequencies and noise levels.

  15. Note: On-line weak signal detection via adaptive stochastic resonance.

    PubMed

    Lu, Siliang; He, Qingbo; Kong, Fanrang

    2014-06-01

    We design an instrument with a novel embedded adaptive stochastic resonance (SR) algorithm that consists of a SR module and a digital zero crossing detection module for on-line weak signal detection in digital signal processing applications. The two modules are responsible for noise filtering and adaptive parameter configuration, respectively. The on-line weak signal detection can be stably achieved in seconds. The prototype instrument exhibits an advance of 20 dB averaged signal-to-noise ratio and 5 times averaged adjust R-square as compared to the input noisy signal, in considering different driving frequencies and noise levels. PMID:24985875

  16. DEVS-based intelligent control of space adapted fluid mixing

    NASA Technical Reports Server (NTRS)

    Chi, Sung-Do; Zeigler, Bernard P.

    1990-01-01

    The development is described of event-based intelligent control system for a space-adapted mixing process by employing the DEVS (Discrete Event System Specification) formalism. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The DEVS-based intelligent control paradigm was applied in a space-adapted mixing system capable of supporting the laboratory automation aboard a Space Station.

  17. Stochastic retinal mechanisms of light adaptation and gain control.

    PubMed

    Rudd, M E; Brown, L G

    1996-01-01

    Under appropriate experimental conditions, the threshold intensity of a visual stimulus varies as the square-root of the background illuminance. This square-root law has been observed in both psychophysical threshold experiments and in measurements of the thresholds of individual ganglion cells. A signal detection theory developed in the 1940s by H. L. de Vries and A. Rose, and since elaborated by H. B. Barlow and others, explains the square-root law on the basis of 'noise' due to fluctuations in the number of photon absorptions per unit area and unit time at the cornea. An alternative account of the square-root law--and also other threshold-vs-intensity slopes--is founded on the assumption of physiological gain control (W. A. H. Rushton, Proc, Roy. Soc. (London) B 162, 20-46, 1965; W. S. Geisler, J. Physiol. (London) 312, 165-179, 1979). In this paper, a neural model of light adaptation and gain control is described that shows how these two accounts of the square-root law can be reconciled by a stochastic gain control mechanism whose gain depends on the photon fluctuation level. The process by which spikes are generated in a ganglion cell is modeled in terms of a stochastic integrate-and-fire mechanism; this model is used to quantitatively fit toad retinal ganglion cell threshold data. A psychophysical model is then outlined showing how a statistical observer could analyze the ganglion cell spike trains generated by 'signal' and 'noise' trials in order to statistically discriminate the two conditions. The model is also shown to account for some dynamic aspects of ganglion cell responses, including ON- and OFF-responses. The neural light adaptation model predicts that--under the proper conditions--brightness matching judgments will also be subject to a square-root law. Experimental tests of the model under superthreshold conditions are proposed.

  18. Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients.

    PubMed

    Ge, Shuzhi Sam; Hong, Fan; Lee, Tong Heng

    2004-02-01

    In this paper, adaptive neural control is presented for a class of strict-feedback nonlinear systems with unknown time delays. The proposed design method does not require a priori knowledge of the signs of the unknown virtual control coefficients. The unknown time delays are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. It is proved that the proposed backstepping design method is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop. In addition, the output of the system is proven to converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approach.

  19. Least-Squares Adaptive Control Using Chebyshev Orthogonal Polynomials

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Burken, John; Ishihara, Abraham

    2011-01-01

    This paper presents a new adaptive control approach using Chebyshev orthogonal polynomials as basis functions in a least-squares functional approximation. The use of orthogonal basis functions improves the function approximation significantly and enables better convergence of parameter estimates. Flight control simulations demonstrate the effectiveness of the proposed adaptive control approach.

  20. Evolutionary Adaptations of Plant AGC Kinases: From Light Signaling to Cell Polarity Regulation

    PubMed Central

    Rademacher, Eike H.; Offringa, Remko

    2012-01-01

    Signaling and trafficking over membranes involves a plethora of transmembrane proteins that control the flow of compounds or relay specific signaling events. Next to external cues, internal stimuli can modify the activity or abundance of these proteins at the plasma membrane (PM). One such regulatory mechanism is protein phosphorylation by membrane-associated kinases, several of which are AGC kinases. The AGC kinase family is one of seven kinase families that are conserved in all eukaryotic genomes. In plants evolutionary adaptations introduced specific structural changes within the AGC kinases that most likely allow modulation of kinase activity by external stimuli (e.g., light). Starting from the well-defined structural basis common to all AGC kinases we review the current knowledge on the structure-function relationship in plant AGC kinases. Nine of the 39 Arabidopsis AGC kinases have now been shown to be involved in the regulation of auxin transport. In particular, AGC kinase-mediated phosphorylation of the auxin transporters ABCB1 and ABCB19 has been shown to regulate their activity, while auxin transporters of the PIN family are located to different positions at the PM depending on their phosphorylation status, which is a result of counteracting AGC kinase and PP6 phosphatase activities. We therefore focus on regulation of AGC kinase activity in this context. Identified structural adaptations of the involved AGC kinases may provide new insight into AGC kinase functionality and demonstrate their position as central hubs in the cellular network controlling plant development and growth. PMID:23162562

  1. Neural control of chronic stress adaptation

    PubMed Central

    Herman, James P.

    2013-01-01

    Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process. PMID:23964212

  2. Control of Flow Separation Using Adaptive Airfoils

    NASA Technical Reports Server (NTRS)

    Chandrasekhara, M. S.; Wilder, M. C.; Carr, L. W.; Davis, Sanford S. (Technical Monitor)

    1996-01-01

    A novel way of controlling flow separation is reported. The approach involves using an adaptive airfoil geometry that changes its leading edge shape to adjust to the instantaneous flow at high angles of attack such that the flow over it remains attached. In particular, a baseline NACA 0012 airfoil, whose leading edge curvature could be changed dynamically by 400% was tested under quasi-steady compressible flow conditions. A mechanical drive system was used to produce a rounded leading edge to reduce the strong local flow acceleration around its nose and thus reduce the strong adverse pressure gradient that follows such a rapid acceleration. Tests in steady flow showed that at M = 0.3, the flow separated at about 14 deg. angle of attack for the NACA 0012 profile but could be kept attached up to an angle of about 18 deg by changing the nose curvature. No significant hysteresis effects were observed; the flow could be made to reattach from its separated state at high angles by changing the leading edge curvature.

  3. Control of Flow Separation Using Adaptive Airfoils

    NASA Technical Reports Server (NTRS)

    Chandrasekhara, M. S.; Wilder, M. C.; Carr, L. W.; Davis, Sanford S. (Technical Monitor)

    1996-01-01

    A novel way of controlling flow separation is reported. The approach involves using an adaptive airfoil geometry that changes its leading edge shape to adjust to the instantaneous flow at high angles of attack such that the flow over it remains attached. In particular, a baseline NACA 0012 airfoil, whose leading edge curvature could be changed dynamically by 400% was tested under quasi-steady compressible flow conditions. A mechanical drive system was used to produce a rounded leading edge to reduce the strong local flow acceleration around its nose and thus reduce the strong adverse pressure gradient that follows such a rapid acceleration. Tests in steady flow showed that at M = 0.3, the flow separated at about 14 deg. angle of attack for the NACA 0012 profile but could be kept attached up to an angle of about 18 deg by changing the nose curvature. No significant hysteresis effects were observed; the flow could be made to reattach from its separated state at high angles by changing the leading edge curvature. Interestingly, the flow over a nearly semicircular nosed airfoil was separated even at low angles.

  4. Adaptive robust controller based on integral sliding mode concept

    NASA Astrophysics Data System (ADS)

    Taleb, M.; Plestan, F.

    2016-09-01

    This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.

  5. Synthetic consciousness: the distributed adaptive control perspective.

    PubMed

    Verschure, Paul F M J

    2016-08-19

    Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID

  6. Adaptive control system for large annular momentum control device

    NASA Technical Reports Server (NTRS)

    Montgomery, R. C.; Johnson, C. R., Jr.

    1981-01-01

    A dual momentum vector control concept, consisting of two counterrotating rings (each designated as an annular momentum control device), was studied for pointing and slewing control of large spacecraft. In a disturbance free space environment, the concept provides for three axis pointing and slewing capabilities while requiring no expendables. The approach utilizes two large diameter counterrotating rings or wheels suspended magnetically in many race supports distributed around the antenna structure. When the magnets are energized, attracting the two wheels, the resulting gyroscopic torque produces a rate along the appropriate axis. Roll control is provided by alternating the radiative rotational velocity of the two wheels. Wheels with diameters of 500 to 800 m and with sufficient momentum storage capability require rims only a few centimeters thick. The wheels are extremely flexible; therefore, it is necessary to account for the distributed nature of the rings in the design of the bearing controllers. Also, ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. An adaptive control system designed to handle these problems is described.

  7. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    NASA Astrophysics Data System (ADS)

    Williams, Rube B.

    2004-02-01

    Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

  8. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    SciTech Connect

    Williams, Rube B.

    2004-02-04

    Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

  9. Multi-element array signal reconstruction with adaptive least-squares algorithms

    NASA Technical Reports Server (NTRS)

    Kumar, R.

    1992-01-01

    Two versions of the adaptive least-squares algorithm are presented for combining signals from multiple feeds placed in the focal plane of a mechanical antenna whose reflector surface is distorted due to various deformations. Coherent signal combining techniques based on the adaptive least-squares algorithm are examined for nearly optimally and adaptively combining the outputs of the feeds. The performance of the two versions is evaluated by simulations. It is demonstrated for the example considered that both of the adaptive least-squares algorithms are capable of offsetting most of the loss in the antenna gain incurred due to reflector surface deformations.

  10. Adaptive plasticity in vestibular influences on cardiovascular control

    NASA Technical Reports Server (NTRS)

    Yates, B. J.; Holmes, M. J.; Jian, B. J.

    2000-01-01

    Data collected in both human subjects and animal models indicate that the vestibular system influences the control of blood pressure. In animals, peripheral vestibular lesions diminish the capacity to rapidly and accurately make cardiovascular adjustments to changes in posture. Thus, one role of vestibulo-cardiovascular influences is to elicit changes in blood distribution in the body so that stable blood pressure is maintained during movement. However, deficits in correcting blood pressure following vestibular lesions diminish over time, and are less severe when non-labyrinthine sensory cues regarding body position in space are provided. These observations show that pathways that mediate vestibulo-sympathetic reflexes can be subject to plastic changes. This review considers the adaptive plasticity in cardiovascular responses elicited by the central vestibular system. Recent data indicate that the posterior cerebellar vermis may play an important role in adaptation of these responses, such that ablation of the posterior vermis impairs recovery of orthostatic tolerance following subsequent vestibular lesions. Furthermore, recent experiments suggest that non-labyrinthine inputs to the central vestibular system may be important in controlling blood pressure during movement, particularly following vestibular dysfunction. A number of sensory inputs appear to be integrated to produce cardiovascular adjustments during changes in posture. Although loss of any one of these inputs does not induce lability in blood pressure, it is likely that maximal blood pressure stability is achieved by the integration of a variety of sensory cues signaling body position in space.

  11. Analysis of modified SMI method for adaptive array weight control

    NASA Technical Reports Server (NTRS)

    Dilsavor, R. L.; Moses, R. L.

    1989-01-01

    An adaptive array is applied to the problem of receiving a desired signal in the presence of weak interference signals which need to be suppressed. A modification, suggested by Gupta, of the sample matrix inversion (SMI) algorithm controls the array weights. In the modified SMI algorithm, interference suppression is increased by subtracting a fraction F of the noise power from the diagonal elements of the estimated covariance matrix. Given the true covariance matrix and the desired signal direction, the modified algorithm is shown to maximize a well-defined, intuitive output power ratio criterion. Expressions are derived for the expected value and variance of the array weights and output powers as a function of the fraction F and the number of snapshots used in the covariance matrix estimate. These expressions are compared with computer simulation and good agreement is found. A trade-off is found to exist between the desired level of interference suppression and the number of snapshots required in order to achieve that level with some certainty. The removal of noise eigenvectors from the covariance matrix inverse is also discussed with respect to this application. Finally, the type and severity of errors which occur in the covariance matrix estimate are characterized through simulation.

  12. Multivariable output feedback robust adaptive tracking control design for a class of delayed systems

    NASA Astrophysics Data System (ADS)

    Mirkin, Boris; Gutman, Per-Olof

    2015-02-01

    In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.

  13. Algorithms for adaptive control of two-arm flexible manipulators under uncertainty

    NASA Technical Reports Server (NTRS)

    Skowronski, J. M.

    1987-01-01

    A nonlinear extension of model reference adaptive control (MRAC) technique is used to guide a double arm nonlinearizable robot manipulator with flexible links, driven by actuators collocated with joints subject to uncertain payload and inertia. The objective is to track a given simple linear and rigid but compatible dynamical model in real, possible stipulated time and within stipulated degree of accuracy of convergence while avoiding collision of the arms. The objective is attained by a specified signal adaptive feedback controller and by adaptive laws, both given in closed form. A case of 4 DOF manipulator illustrates the technique.

  14. Experimental investigation of adaptive control of a parallel manipulator

    NASA Technical Reports Server (NTRS)

    Nguyen, Charles C.; Antrazi, Sami S.

    1992-01-01

    The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

  15. Adaptive Force Control For Compliant Motion Of A Robot

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1995-01-01

    Two adaptive control schemes offer robust solutions to problem of stable control of forces of contact between robotic manipulator and objects in its environment. They are called "adaptive admittance control" and "adaptive compliance control." Both schemes involve use of force-and torque sensors that indicate contact forces. These schemes performed well when tested in computational simulations in which they were used to control seven-degree-of-freedom robot arm in executing contact tasks. Choice between admittance or compliance control is dictated by requirements of the application at hand.

  16. System and method for adaptively deskewing parallel data signals relative to a clock

    DOEpatents

    Jenkins, Philip Nord; Cornett, Frank N.

    2008-10-07

    A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in detected skew.

  17. System and method for adaptively deskewing parallel data signals relative to a clock

    DOEpatents

    Jenkins, Philip Nord; Cornett, Frank N.

    2011-10-04

    A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in detected skew.

  18. Direct Adaptive Control of Systems with Actuator Failures: State of the Art and Continuing Challenges

    NASA Technical Reports Server (NTRS)

    Tao, Gang; Joshi, Suresh M.

    2008-01-01

    In this paper, the problem of controlling systems with failures and faults is introduced, and an overview of recent work on direct adaptive control for compensation of uncertain actuator failures is presented. Actuator failures may be characterized by some unknown system inputs being stuck at some unknown (fixed or varying) values at unknown time instants, that cannot be influenced by the control signals. The key task of adaptive compensation is to design the control signals in such a manner that the remaining actuators can automatically and seamlessly take over for the failed ones, and achieve desired stability and asymptotic tracking. A certain degree of redundancy is necessary to accomplish failure compensation. The objective of adaptive control design is to effectively use the available actuation redundancy to handle failures without the knowledge of the failure patterns, parameters, and time of occurrence. This is a challenging problem because failures introduce large uncertainties in the dynamic structure of the system, in addition to parametric uncertainties and unknown disturbances. The paper addresses some theoretical issues in adaptive actuator failure compensation: actuator failure modeling, redundant actuation requirements, plant-model matching, error system dynamics, adaptation laws, and stability, tracking, and performance analysis. Adaptive control designs can be shown to effectively handle uncertain actuator failures without explicit failure detection. Some open technical challenges and research problems in this important research area are discussed.

  19. Adaptive robust control of the EBR-II reactor

    SciTech Connect

    Power, M.A.; Edwards, R.M.

    1996-05-01

    Simulation results are presented for an adaptive H{sub {infinity}} controller, a fixed H{sub {infinity}} controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H{sub {infinity}} controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H{sub {infinity}} and classical controllers. This makes for a superior and more robust controller.

  20. A fast converging robust controller using adaptive second order sliding mode.

    PubMed

    Mondal, Sanjoy; Mahanta, Chitralekha

    2012-11-01

    This paper proposes an adaptive second order sliding mode (SOSM) controller with a nonlinear sliding surface. The nonlinear sliding surface consists of a gain matrix having a variable damping ratio. Initially the sliding surface uses a low value of damping ratio to get a quick system response. As the closed loop system approaches the desired reference, the value of the damping ratio gets increased with an aim to reducing the overshoot and the settling time. The time derivative of the control signal is used to design the controller. The actual control input obtained by integrating the derivative control signal is smooth and chattering free. The adaptive tuning law used by the proposed controller eliminates the need of prior knowledge about the upper bound of system uncertainties. Simulation results demonstrate the effectiveness of the proposed control strategy.

  1. Adaptive neural control for a class of perturbed strict-feedback nonlinear time-delay systems.

    PubMed

    Wang, Min; Chen, Bing; Shi, Peng

    2008-06-01

    This paper proposes a novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. Based on the radial basis function neural network online approximation capability, an adaptive neural controller is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals. The proposed controller guarantees the semiglobal boundedness of all the signals in the closed-loop system and contains minimal learning parameters. Finally, three simulation examples are given to demonstrate the effectiveness and applicability of the proposed scheme.

  2. Adaptive identification and control of structural dynamics systems using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Montgomery, R. C.; Williams, J. P.

    1985-01-01

    A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

  3. An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed

    NASA Astrophysics Data System (ADS)

    Kim, H.; Choi, Y.; Yang, Y.

    In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.

  4. An adaptive control scheme for coordinated multimanipulator systems

    SciTech Connect

    Jonghann Jean; Lichen Fu . Dept. of Electrical Engineering)

    1993-04-01

    The problem of adaptive coordinated control of multiple robot arms transporting an object is addressed. A stable adaptive control scheme for both trajectory tracking and internal force control is presented. Detailed analyses on tracking properties of the object position, velocity and the internal forces exerted on the object are given. It is shown that this control scheme can achieve satisfactory tracking performance without using the measurement of contact forces and their derivatives. It can be shown that this scheme can be realized by decentralized implementation to reduce the computational burden. Moreover, some efficient adaptive control strategies can be incorporated to reduce the computational complexity.

  5. Adaptive backstepping sliding mode control with fuzzy monitoring strategy for a kind of mechanical system.

    PubMed

    Song, Zhankui; Sun, Kaibiao

    2014-01-01

    A novel adaptive backstepping sliding mode control (ABSMC) law with fuzzy monitoring strategy is proposed for the tracking-control of a kind of nonlinear mechanical system. The proposed ABSMC scheme combining the sliding mode control and backstepping technique ensure that the occurrence of the sliding motion in finite-time and the trajectory of tracking-error converge to equilibrium point. To obtain a better perturbation rejection property, an adaptive control law is employed to compensate the lumped perturbation. Furthermore, we introduce fuzzy monitoring strategy to improve adaptive capacity and soften the control signal. The convergence and stability of the proposed control scheme are proved by using Lyaponov's method. Finally, numerical simulations demonstrate the effectiveness of the proposed control scheme.

  6. System and method for adaptively deskewing parallel data signals relative to a clock

    DOEpatents

    Jenkins, Philip Nord; Cornett, Frank N.

    2006-04-18

    A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. Each of the plurality of delayed signals is compared to a reference signal to detect changes in the skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in the detected skew.

  7. Application of adaptive subband coding for noisy bandlimited ECG signal processing

    NASA Astrophysics Data System (ADS)

    Aditya, Krishna; Chu, Chee-Hung H.; Szu, Harold H.

    1996-03-01

    An approach to impulsive noise suppression and background normalization of digitized bandlimited electrovcardiogram signals is presented. This approach uses adaptive wavelet filters that incorporate the band-limited a priori information and the shape information of a signal to decompose the data. Empirical results show that the new algorithm has good performance in wideband impulsive noise suppression and background normalization for subsequent wave detection, when compared with subband coding using Daubechie's D4 wavelet, without the bandlimited adaptive wavelet transform.

  8. Closing the Certification Gaps in Adaptive Flight Control Software

    NASA Technical Reports Server (NTRS)

    Jacklin, Stephen A.

    2008-01-01

    Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

  9. Task Control Signals in Pediatric Tourette Syndrome Show Evidence of Immature and Anomalous Functional Activity

    PubMed Central

    Church, Jessica A.; Wenger, Kristin K.; Dosenbach, Nico U. F.; Miezin, Francis M.; Petersen, Steven E.; Schlaggar, Bradley L.

    2009-01-01

    Tourette Syndrome (TS) is a pediatric movement disorder that may affect control signaling in the brain. Previous work has proposed a dual-networks architecture of control processing involving a task-maintenance network and an adaptive control network (Dosenbach et al., 2008). A prior resting-state functional connectivity MRI (rs-fcMRI) analysis in TS has revealed functional immaturity in both putative control networks, with “anomalous” correlations (i.e., correlations outside the typical developmental range) limited to the adaptive control network (Church et al., 2009). The present study used functional MRI (fMRI) to study brain activity related to adaptive control (by studying start-cues signals), and to task-maintenance (by studying signals sustained across a task set). Two hypotheses from the previous rs-fcMRI results were tested. First, adaptive control (i.e., start-cue) activity will be altered in TS, including activity inconsistent with typical development (“anomalous”). Second, group differences found in task-maintenance (i.e., sustained) activity will be consistent with functional immaturity in TS. We examined regions found through a direct comparison of adolescents with and without TS, as well as regions derived from a previous investigation that showed differences between unaffected children and adults. The TS group showed decreased start-cue signal magnitude in regions where start-cue activity is unchanged over typical development, consistent with anomalous adaptive control. The TS group also had higher magnitude sustained signals in frontal cortex regions that overlapped with regions showing differences over typical development, consistent with immature task-maintenance in TS. The results demonstrate task-related fMRI signal differences anticipated by the atypical functional connectivity found previously in adolescents with TS, strengthening the evidence for functional immaturity and anomalous signaling in control networks in adolescents with TS

  10. Adaptive jitter control for tracker line of sight stabilization

    NASA Astrophysics Data System (ADS)

    Gibson, Steve; Tsao, Tsu-Chin; Herrick, Dan; Beairsto, Christopher; Grimes, Ronnie; Harper, Todd; Radtke, Jeff; Roybal, Benito; Spray, Jay; Squires, Stephen; Tellez, Dave; Thurston, Michael

    2010-08-01

    A field test experiment on a range tracking telescope at the U. S. Army's White Sands Missile Range is exploring the use of recently developed adaptive control methods to minimize track loop jitter. Gimbal and platform vibration are the main sources of jitter in the experiments, although atmospheric turbulence also is a factor. In initial experiments, the adaptive controller reduced the track loop jitter significantly in frequency ranges beyond the bandwidth of the existing track loop. This paper presents some of the initial experimental results along with analysis of the performance of the adaptive control loop. The paper also describes the adaptive control scheme, its implementation on the WSMR telescope and the system identification required for adaptive control.

  11. Adaptive sliding mode control for a class of chaotic systems

    SciTech Connect

    Farid, R.; Ibrahim, A.; Zalam, B.

    2015-03-30

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.

  12. A novel algorithm for real-time adaptive signal detection and identification

    SciTech Connect

    Sleefe, G.E.; Ladd, M.D.; Gallegos, D.E.; Sicking, C.W.; Erteza, I.A.

    1998-04-01

    This paper describes a novel digital signal processing algorithm for adaptively detecting and identifying signals buried in noise. The algorithm continually computes and updates the long-term statistics and spectral characteristics of the background noise. Using this noise model, a set of adaptive thresholds and matched digital filters are implemented to enhance and detect signals that are buried in the noise. The algorithm furthermore automatically suppresses coherent noise sources and adapts to time-varying signal conditions. Signal detection is performed in both the time-domain and the frequency-domain, thereby permitting the detection of both broad-band transients and narrow-band signals. The detection algorithm also provides for the computation of important signal features such as amplitude, timing, and phase information. Signal identification is achieved through a combination of frequency-domain template matching and spectral peak picking. The algorithm described herein is well suited for real-time implementation on digital signal processing hardware. This paper presents the theory of the adaptive algorithm, provides an algorithmic block diagram, and demonstrate its implementation and performance with real-world data. The computational efficiency of the algorithm is demonstrated through benchmarks on specific DSP hardware. The applications for this algorithm, which range from vibration analysis to real-time image processing, are also discussed.

  13. Systems and Methods for Derivative-Free Adaptive Control

    NASA Technical Reports Server (NTRS)

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  14. Adaptive Controller for Compact Fourier Transform Spectrometer with Space Applications

    NASA Astrophysics Data System (ADS)

    Keymeulen, D.; Yiu, P.; Berisford, D. F.; Hand, K. P.; Carlson, R. W.; Conroy, M.

    2014-12-01

    Here we present noise mitigation techniques developed as part of an adaptive controller for a very compact Compositional InfraRed Interferometric Spectrometer (CIRIS) implemented on a stand-alone field programmable gate array (FPGA) architecture with emphasis on space applications in high radiation environments such as Europa. CIRIS is a novel take on traditional Fourier Transform Spectrometers (FTS) and replaces linearly moving mirrors (characteristic of Michelson interferometers) with a constant-velocity rotating refractor to variably phase shift and alter the path length of incoming light. The design eschews a monochromatic reference laser typically used for sampling clock generation and instead utilizes constant time-sampling via internally generated clocks. This allows for a compact and robust device, making it ideal for spaceborne measurements in the near-IR to thermal-IR band (2-12 µm) on planetary exploration missions. The instrument's embedded microcontroller is implemented on a VIRTEX-5 FPGA and a PowerPC with the aim of sampling the instrument's detector and optical rotary encoder in order to construct interferograms. Subsequent onboard signal processing provides spectral immunity from the noise effects introduced by the compact design's removal of a reference laser and by the radiation encountered during space flight to destinations such as Europa. A variety of signal processing techniques including resampling, radiation peak removal, Fast Fourier Transform (FFT), spectral feature alignment, dispersion correction and calibration processes are applied to compose the sample spectrum in real-time with signal-to-noise-ratio (SNR) performance comparable to laser-based FTS designs in radiation-free environments. The instrument's FPGA controller is demonstrated with the FTS to characterize its noise mitigation techniques and highlight its suitability for implementation in space systems.

  15. Internal models in sensorimotor integration: perspectives from adaptive control theory.

    PubMed

    Tin, Chung; Poon, Chi-Sang

    2005-09-01

    Internal models and adaptive controls are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models' architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods, such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning, are reviewed and their possible relevance to motor control is discussed. Possible applicability of a Luenberger observer and an extended Kalman filter to state estimation problems-such as sensorimotor prediction or the resolution of vestibular sensory ambiguity-is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal models in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future.

  16. Adaptive filter for reconstruction of stereo audio signals

    NASA Astrophysics Data System (ADS)

    Cisowski, Krzysztof

    2004-05-01

    The paper presents a new approach to reconstruction of impulsively disturbed stereo audio signals. The problems of restoration of large blocks of missing samples are outlined. Present methods of removing of covariance defect are discussed. Model of stereophonic signal is defined and Kalman filter appropriate for this model is introduced. Modifications of the filter directing to the new method of reconstruction of block of missing samples are discussed. Projection based algorithm allows to recover samples of left (or right) stereo channel using additional information included in undistorted samples from the other channel.

  17. Interior Noise Reduction by Adaptive Feedback Vibration Control

    NASA Technical Reports Server (NTRS)

    Lim, Tae W.

    1998-01-01

    The objective of this project is to investigate the possible use of adaptive digital filtering techniques in simultaneous, multiple-mode identification of the modal parameters of a vibrating structure in real-time. It is intended that the results obtained from this project will be used for state estimation needed in adaptive structural acoustics control. The work done in this project is basically an extension of the work on real-time single mode identification, which was performed successfully using a digital signal processor (DSP) at NASA, Langley. Initially, in this investigation the single mode identification work was duplicated on a different processor, namely the Texas Instruments TMS32OC40 DSP. The system identification results for the single mode case were very good. Then an algorithm for simultaneous two mode identification was developed and tested using analytical simulation. When it successfully performed the expected tasks, it was implemented in real-time on the DSP system to identify the first two modes of vibration of a cantilever aluminum beam. The results of the simultaneous two mode case were good but some problems were identified related to frequency warping and spurious mode identification. The frequency warping problem was found to be due to the bilinear transformation used in the algorithm to convert the system transfer function from the continuous-time domain to the discrete-time domain. An alternative approach was developed to rectify the problem. The spurious mode identification problem was found to be associated with high sampling rates. Noise in the signal is suspected to be the cause of this problem but further investigation will be needed to clarify the cause. For simultaneous identification of more than two modes, it was found that theoretically an adaptive digital filter can be designed to identify the required number of modes, but the algebra became very complex which made it impossible to implement in the DSP system used in this study

  18. Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

    PubMed

    Tong, Shaocheng; Sui, Shuai; Li, Yongming

    2015-12-01

    In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

  19. Adaptive control with variable dead-zone nonlinearities

    NASA Technical Reports Server (NTRS)

    Orlicki, D.; Valavani, L.; Athans, M.; Stein, G.

    1984-01-01

    It has been found that fixed error dead-zones as defined in the existing literature result in serious degradation of performance, due to the conservativeness which characterizes the determination of their width. In the present paper, variable width dead-zones are derived for the adaptive control of plants with unmodeled dynamics. The derivation makes use of information available about the unmodeled dynamics both a priori as well as during the adaptation process, so as to stabilize the adaptive loop and at the same time overcome the conservativeness and performance limitations of fixed-dead zone adaptive or fixed gain controllers.

  20. A robust adaptive nonlinear fault-tolerant controller via norm estimation for reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Hu, Chaofang; Gao, Zhifei; Ren, Yanli; Liu, Yunbing

    2016-11-01

    In this paper, a reusable launch vehicle (RLV) attitude control problem with actuator faults is addressed via the robust adaptive nonlinear fault-tolerant control (FTC) with norm estimation. Firstly, the accurate tracking task of attitude angles in the presence of parameter uncertainties and external disturbances is considered. A fault-free controller is proposed using dynamic surface control (DSC) combined with fuzzy adaptive approach. Furthermore, the minimal learning parameter strategy via norm estimation technique is introduced to reduce the multi-parameter adaptive computation burden of fuzzy approximation of the lump uncertainties. Secondly, a compensation controller is designed to handle the partial loss fault of actuator effectiveness. The unknown maximum eigenvalue of actuator efficiency loss factors is estimated online. Moreover, stability analysis guarantees that all signals of the closed-loop control system are semi-global uniformly ultimately bounded. Finally, illustrative simulations show the effectiveness of the proposed method.

  1. Projection Operator: A Step Towards Certification of Adaptive Controllers

    NASA Technical Reports Server (NTRS)

    Larchev, Gregory V.; Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

    One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

  2. Hormesis and adaptive cellular control systems

    EPA Science Inventory

    Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

  3. An adaptive P300-based control system

    NASA Astrophysics Data System (ADS)

    Jin, Jing; Allison, Brendan Z.; Sellers, Eric W.; Brunner, Clemens; Horki, Petar; Wang, Xingyu; Neuper, Christa

    2011-06-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e. 12 columns and 7 rows). The 9- and 14-flash A and B paradigms present all items of the 12 × 7 matrix three times using either 9 or 14 flashes (instead of 19), decreasing the amount of time to present stimuli. Compared to 9-flash A, 9-flash B decreased the likelihood that neighboring items would flash when the target was not flashing, thereby reducing the interference from items adjacent to targets. 14-flash A also reduced the adjacent item interference and 14-flash B additionally eliminated successive (double) flashes of the same item. Results showed that the accuracy and bit rate of the adaptive system were higher than those of the non-adaptive system. In addition, 9- and 14-flash B produced significantly higher performance than their respective A conditions. The results also show the trend that the 14-flash B paradigm was better than the 19-flash pattern for naive users.

  4. STDP with adaptive synaptic delay for robot navigation control

    NASA Astrophysics Data System (ADS)

    Arena, Paolo; Patané, Luca; Distefano, Francesco; Bucolo, Sebastiano; Aiello, Orazio

    2007-05-01

    In this work a biologically inspired network of spiking neurons is used for robot navigation control. The two tasks taken into account are obstacle avoidance and landmark-based navigation. The system learns the correlation among unconditioned stimuli (pre-wired sensors) and conditioned stimuli (high level sensors) through Spike Timing Dependent Plasticity (STDP). In order to improve the robot behaviours not only the synaptic weight but also the synaptic delay is subject to learning. Modulating the synaptic delay the robot is able to store the landmark position, like in a short time memory, and to use this information to smooth the turning actions prolonging the landmark effects also when it is no more visible. Simulations are carried out in a dynamic simulation environment and the robotic system considered is a cockroach-inspired hexapod robot. The locomotion signals are generated by a Central Pattern Generator and the spiking network is devoted to control the heading of the robot acting on the amplitude of the leg steps. Several scenarios have been proposed, for instance a T-shaped labyrinth, used in laboratory experiments with mice to demonstrate classical and operant conditioning, has been considered. Finally the proposed adaptive navigation control structure can be extended in a modular way to include other features detected by new sensors included in the correlation-based learning process.

  5. ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS

    EPA Science Inventory

    A contaminant detection technique and its optimization algorithms have two principal functions. One is the adaptive signal treatment that suppresses background noise and enhances contaminant signals, leading to a promising detection of water quality changes at a false rate as low...

  6. Adaptive torque control of variable speed wind turbines

    NASA Astrophysics Data System (ADS)

    Johnson, Kathryn E.

    Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.

  7. The role of astrocytes in the hypothalamic response and adaptation to metabolic signals.

    PubMed

    Chowen, Julie A; Argente-Arizón, Pilar; Freire-Regatillo, Alejandra; Frago, Laura M; Horvath, Tamas L; Argente, Jesús

    2016-09-01

    The hypothalamus is crucial in the regulation of homeostatic functions in mammals, with the disruption of hypothalamic circuits contributing to chronic conditions such as obesity, diabetes mellitus, hypertension, and infertility. Metabolic signals and hormonal inputs drive functional and morphological changes in the hypothalamus in attempt to maintain metabolic homeostasis. However, the dramatic increase in the incidence of obesity and its secondary complications, such as type 2 diabetes, have evidenced the need to better understand how this system functions and how it can go awry. Growing evidence points to a critical role of astrocytes in orchestrating the hypothalamic response to metabolic cues by participating in processes of synaptic transmission, synaptic plasticity and nutrient sensing. These glial cells express receptors for important metabolic signals, such as the anorexigenic hormone leptin, and determine the type and quantity of nutrients reaching their neighboring neurons. Understanding the mechanisms by which astrocytes participate in hypothalamic adaptations to changes in dietary and metabolic signals is fundamental for understanding the neuroendocrine control of metabolism and key in the search for adequate treatments of metabolic diseases.

  8. Adaptive Control in the Presence of Simultaneous Sensor Bias and Actuator Failures

    NASA Technical Reports Server (NTRS)

    Joshi, Suresh M.

    2012-01-01

    The problem of simultaneously accommodating unknown sensor biases and unknown actuator failures in uncertain systems is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor biases and actuator faults may be present at the outset or may occur at unknown instants of time during operation. A modified MRAC law is proposed, which combines sensor bias estimation with control gain adaptation for accommodation of sensor biases and actuator failures. This control law is shown to provide signal boundedness in the resulting system. For the case when an external asymptotically stable sensor bias estimator is available, an MRAC law is developed to accomplish asymptotic state tracking and signal boundedness. For a special case wherein biases are only present in the rate measurements and bias-free position measurements are available, an MRAC law is developed using a model-independent bias estimator, and is shown to provide asymptotic state tracking with signal boundedness.

  9. Adaptive Fuzzy Control of a Direct Drive Motor

    NASA Technical Reports Server (NTRS)

    Medina, E.; Kim, Y. T.; Akbaradeh-T., M. -R.

    1997-01-01

    This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is verified by simulation results.

  10. Adaptive Fuzzy Control of a Direct Drive Motor: Experimental Aspects

    NASA Technical Reports Server (NTRS)

    Medina, E.; Akbarzadeh-T, M.-R.; Kim, Y. T.

    1998-01-01

    This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is experimentally verified. The real-time performance is compared with simulation results.

  11. Universal signals control slime mold stalk formation.

    PubMed

    van Es, S; Nieuwenhuijsen, B W; Lenouvel, F; van Deursen, E M; Schaap, P

    1994-08-16

    The primitive slime mold Dictyostelium minutum does not display oscillations during aggregation, cannot form migrating slugs, and does not form a prestalk/prespore pattern, all of which are characteristic for development of its advanced relative Dictyostelium discoideum. We used D. minutum to investigate whether slime molds share common mechanisms controlling development. In D. discoideum, the morphogen differentiation inducing factor (DIF) can induce stalk-cell differentiation in vitro. However, stalk formation in vivo is supposedly triggered by local depletion of DIF antagonists such as ammonia or cAMP. A homologue of the D. discoideum stalk gene ecmB was cloned in D. minutum that encodes a 3.4-kb mRNA, and its deduced amino acid sequence shows repeats of 24 amino acids that are characteristic for the D. discoideum ecmB gene. Remarkably, DIF effectively induces expression of the D. minutum ecmB gene and ammonia inhibits its expression. D. discoideum cells were transformed with a construct of the D. minutum ecmB promoter fused to the lacZ reporter gene and showed expression in the stalk, but not in the upper and lower cup of the fruiting body, which also express the D. discoideum ecmB gene. In D. discoideum, the D. minutum ecmB and the ecmB promoter are similarly activated by DIF and repressed by both cAMP and ammonia, suggesting that additional signaling is required for ecmB expression in upper and lower cup cells. Our data indicate that the extracellular signals controlling stalk formation and their intracellular signaling cascades including gene regulatory proteins remained highly conserved during slime mold evolution. PMID:8058783

  12. Spatiotemporal control of opioid signaling and behavior

    PubMed Central

    Siuda, Edward R.; Copits, Bryan A.; Schmidt, Martin J.; Baird, Madison A.; Al-Hasani, Ream; Planer, William J.; Funderburk, Samuel C.; McCall, Jordan G.; Gereau, Robert W.; Bruchas, Michael R.

    2015-01-01

    Summary Optogenetics is now a widely accepted tool for spatiotemporal manipulation of neuronal activity. However, a majority of optogenetic approaches use binary on/off control schemes. Here we extend the optogenetic toolset by developing a neuromodulatory approach using a rationale-based design to generate a Gi-coupled, optically-sensitive, mu-opioid-like receptor, we term opto-MOR. We demonstrate that opto-MOR engages canonical mu-opioid signaling through inhibition of adenylyl cyclase, activation of MAPK and G protein-gated inward rectifying potassium (GIRK) channels, and internalizes with similar kinetics as the mu-opioid receptor. To assess in vivo utility we expressed a Cre-dependent viral opto-MOR in RMTg/VTA GABAergic neurons, which led to a real-time place preference. In contrast, expression of opto-MOR in GABAergic neurons of the ventral pallidum hedonic cold spot, led to real-time place aversion. This tool has generalizable application for spatiotemporal control of opioid signaling and, furthermore, can be used broadly for mimicking endogenous neuronal inhibition pathways. PMID:25937173

  13. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    NASA Technical Reports Server (NTRS)

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  14. Lessons in Fundamental Mechanisms and Diverse Adaptations from the 2015 Bacterial Locomotion and Signal Transduction Meeting

    PubMed Central

    Prüβ, Birgit M.; Liu, Jun; Higgs, Penelope I.

    2015-01-01

    In response to rapid changes in their environment, bacteria control a number of processes, including motility, cell division, biofilm formation, and virulence. Research presented in January 2015 at the biennial Bacterial Locomotion and Signal Transduction (BLAST) meeting in Tucson, AZ, illustrates the elegant complexity of the nanoarrays, nanomachines, and networks of interacting proteins that mediate such processes. Studies employing an array of biophysical, genetic, cell biology, and mathematical methods are providing an increasingly detailed understanding of the mechanisms of these systems within well-studied bacteria. Furthermore, comparisons of these processes in diverse bacterial species are providing insight into novel regulatory and functional mechanisms. This review summarizes research presented at the BLAST meeting on these fundamental mechanisms and diverse adaptations, including findings of importance for applications involving bacteria of medical or agricultural relevance. PMID:26195592

  15. Design of Low Complexity Model Reference Adaptive Controllers

    NASA Technical Reports Server (NTRS)

    Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan

    2012-01-01

    Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.

  16. Adaptive optimization and control using neural networks

    SciTech Connect

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  17. Mode-field adapter for tapered-fiber-bundle signal and pump combiners.

    PubMed

    Koška, Pavel; Baravets, Yauhen; Peterka, Pavel; Bohata, Jan; Písařík, Michael

    2015-02-01

    We report on a novel mode-field adapter that is proposed to be incorporated inside tapered fused-fiber-bundle pump and signal combiners for high-power double-clad fiber lasers. Such an adapter allows optimization of signal-mode-field matching on the input and output fibers. Correspondingly, losses of the combiner signal branch are significantly reduced. The mode-field adapter optimization procedure is demonstrated on a combiner based on commercially available fibers. Signal wavelengths of 1.55 and 2 μm are considered. The losses can be further improved by using specially designed intermediate fiber and by dopant diffusion during splicing as confirmed by preliminary experimental results. PMID:25967784

  18. Adaptive Instability Suppression Controls in a Liquid-fueled Combustor

    NASA Technical Reports Server (NTRS)

    Kopasakis, George; DeLaat, John C.

    2002-01-01

    An adaptive control algorithm has been developed for the suppression of combustion thermo-acoustic instabilities. This technique involves modulating the fuel flow in the combustor with a control phase that continuously slides within the stable phase region, in a back and forth motion. The control method is referred to as Adaptive Sliding Phasor Averaged Control (ASPAC). The control method is evaluated against a simplified simulation of the combustion instability. Plans are to validate the control approach against a more physics-based model and an actual experimental combustor rig.

  19. Adaptive hybrid optimal quantum control for imprecisely characterized systems.

    PubMed

    Egger, D J; Wilhelm, F K

    2014-06-20

    Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful. PMID:24996074

  20. Smart Rehabilitation Devices: Part II – Adaptive Motion Control

    PubMed Central

    Dong, Shufang; Lu, Ke-Qian; Sun, J. Q.; Rudolph, Katherine

    2008-01-01

    This article presents a study of adaptive motion control of smart versatile rehabilitation devices using MR fluids. The device provides both isometric and isokinetic strength training and is reconfigurable for several human joints. Adaptive controls are developed to regulate resistance force based on the prescription of the therapist. Special consideration has been given to the human–machine interaction in the adaptive control that can modify the behavior of the device to account for strength gains or muscle fatigue of the human subject. PMID:18548131

  1. Development of a digital adaptive optimal linear regulator flight controller

    NASA Technical Reports Server (NTRS)

    Berry, P.; Kaufman, H.

    1975-01-01

    Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.

  2. Discrete-time adaptive control of robot manipulators

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1989-01-01

    A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that asymptotic trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation.

  3. Disturbance Accommodating Adaptive Control with Application to Wind Turbines

    NASA Technical Reports Server (NTRS)

    Frost, Susan

    2012-01-01

    Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.

  4. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a dual-adaptive feedback control unit for a highly nonlinear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the nonlinear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a dual-adaptive control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  5. Adaptive Controller for T-S Fuzzy Model with Reconstruction Error

    NASA Astrophysics Data System (ADS)

    Han, Hugang

    In this paper, the reconstruction error between the real system to be controlled and its T-S fuzzy model is considered, and fuzzy approximator is employed to cope with the reconstruction error. As a result, it reaches an adaptive controller that has two parts: one is obtained by solving certain linear matrix inequalities (LMIs) (fixed part) and another one is acquired by the fuzzy approximator in which the related parameters are tuned by adaptive law (variable part). The proposed controller can guarantee the control state to converge and uniformly bounded while maintaining all the signals involved stable. Also, the convergence in terms of relaxing the LMIs conservatism is discussed. An inverted pendulum is provided to demonstrate the effectiveness of the proposed adaptive fuzzy controller.

  6. Flexibility in Animal Signals Facilitates Adaptation to Rapidly Changing Environments

    PubMed Central

    Proppe, Darren S.; Sturdy, Christopher B.; St. Clair, Colleen Cassady

    2011-01-01

    Charles Darwin posited that secondary sexual characteristics result from competition to attract mates. In male songbirds, specialized vocalizations represent secondary sexual characteristics of particular importance because females prefer songs at specific frequencies, amplitudes, and duration. For birds living in human-dominated landscapes, historic selection for song characteristics that convey fitness may compete with novel selective pressures from anthropogenic noise. Here we show that black-capped chickadees (Poecile atricapillus) use shorter, higher-frequency songs when traffic noise is high, and longer, lower-frequency songs when noise abates. We suggest that chickadees balance opposing selective pressures by use low-frequency songs to preserve vocal characteristics of dominance that repel competitors and attract females, and high frequency songs to increase song transmission when their environment is noisy. The remarkable vocal flexibility exhibited by chickadees may be one reason that they thrive in urban environments, and such flexibility may also support subsequent genetic adaptation to an increasingly urbanized world. PMID:21980449

  7. Flexibility in animal signals facilitates adaptation to rapidly changing environments.

    PubMed

    Proppe, Darren S; Sturdy, Christopher B; St Clair, Colleen Cassady

    2011-01-01

    Charles Darwin posited that secondary sexual characteristics result from competition to attract mates. In male songbirds, specialized vocalizations represent secondary sexual characteristics of particular importance because females prefer songs at specific frequencies, amplitudes, and duration. For birds living in human-dominated landscapes, historic selection for song characteristics that convey fitness may compete with novel selective pressures from anthropogenic noise. Here we show that black-capped chickadees (Poecile atricapillus) use shorter, higher-frequency songs when traffic noise is high, and longer, lower-frequency songs when noise abates. We suggest that chickadees balance opposing selective pressures by use low-frequency songs to preserve vocal characteristics of dominance that repel competitors and attract females, and high frequency songs to increase song transmission when their environment is noisy. The remarkable vocal flexibility exhibited by chickadees may be one reason that they thrive in urban environments, and such flexibility may also support subsequent genetic adaptation to an increasingly urbanized world.

  8. Stability and Performance Metrics for Adaptive Flight Control

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

    2009-01-01

    This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

  9. Adaptive Array for Weak Interfering Signals: Geostationary Satellite Experiments. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Steadman, Karl

    1989-01-01

    The performance of an experimental adaptive array is evaluated using signals from an existing geostationary satellite interference environment. To do this, an earth station antenna was built to receive signals from various geostationary satellites. In these experiments the received signals have a frequency of approximately 4 GHz (C-band) and have a bandwidth of over 35 MHz. These signals are downconverted to a 69 MHz intermediate frequency in the experimental system. Using the downconverted signals, the performance of the experimental system for various signal scenarios is evaluated. In this situation, due to the inherent thermal noise, qualitative instead of quantitative test results are presented. It is shown that the experimental system can null up to two interfering signals well below the noise level. However, to avoid the cancellation of the desired signal, the use a steering vector is needed. Various methods to obtain an estimate of the steering vector are proposed.

  10. Nucleo-olivary inhibition balances the interaction between the reactive and adaptive layers in motor control.

    PubMed

    Herreros, Ivan; Verschure, Paul F M J

    2013-11-01

    In the acquisition of adaptive motor reflexes to aversive stimuli, the cerebellar output fulfills a double purpose: it controls a motor response and it relays a sensory prediction. However, the question of how these two apparently incompatible goals might be achieved by the same cerebellar area remains open. Here we propose a solution where the inhibition of the Inferior Olive (IO) by the cerebellar Deep Nuclei (DN) translates the motor command signal into a sensory prediction allowing a single cerebellar area to simultaneously tackle both aspects of the problem: execution and prediction. We demonstrate that having a graded error signal, the gain of the Nucleo-Olivary Inhibition (NOI) balances the generation of the response between the cerebellar and the reflexive controllers or, in other words, between the adaptive and the reactive layers of behavior. Moreover, we show that the resulting system is fully autonomous and can either acquire or erase adaptive responses according to their utility.

  11. Adaptive Importance Sampling for Control and Inference

    NASA Astrophysics Data System (ADS)

    Kappen, H. J.; Ruiz, H. C.

    2016-03-01

    Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.

  12. Control System with Two Stages Using Adaptive Controller for a Serial Rotary-Type Double Inverted Pendulum

    NASA Astrophysics Data System (ADS)

    Hirata, Hiroshi; Nakayama, Yusuke; Ouchi, Shigeto

    Inverted pendulums are very often used to verify many control theories, because they are typical unstable systems and also are interesting objects. However, few innovative methods with respect to the adaptive control of inverted pendulum (IP) are reported. This paper presents a stabilization method by using the adaptive control for a serial rotary-type double inverted pendulum (SRDIP) whose whole basic parameters are unknown. The control system of a SRDIP is achieved by separating the control mode to two stages. The first stage is an adaptive control mode of the single IP placing the second IP in downward directions and another stage is a LQ control mode of the SRDIP. The control system prepares two kinds of adaptive controllers, which are a variable structure system (VSS) robust adaptive control and a self-tuning control (STC). The rotational angle of the first IP is stabilized by the VSS adaptive control, and the stability of the rotary arm is also achieved by constructing the STC that guarantees the boundary reference angle of the first IP. It is then difficult to construct the STC by only adjustable parameters of the VSS adaptive control system. Whole basic parameters of a SRDIP are estimated by adopting the recursive least squares (RLS) estimation method in order to accomplish both of the STC system and the LQ design of a SRDIP. The RLS algorithm is performed by superposing an available perturbation signal to the adaptive manipulated variable on a limited short interval. The STC system updates a LQ controller based on the QR methods devised for the real time operation. Before completing the first stage, a LQ controller for the SRDIP is obtained through a state space description from the estimated basic parameters. The control law is changed to a LQ control for the SRDIP from an adaptive control mode in the second stage. Finally, it is verified by simulation studies and practical experiments that the proposed system is useful as a control strategy of the SRDIP

  13. Inverse Modelling to Obtain Head Movement Controller Signal

    NASA Technical Reports Server (NTRS)

    Kim, W. S.; Lee, S. H.; Hannaford, B.; Stark, L.

    1984-01-01

    Experimentally obtained dynamics of time-optimal, horizontal head rotations have previously been simulated by a sixth order, nonlinear model driven by rectangular control signals. Electromyography (EMG) recordings have spects which differ in detail from the theoretical rectangular pulsed control signal. Control signals for time-optimal as well as sub-optimal horizontal head rotations were obtained by means of an inverse modelling procedures. With experimentally measured dynamical data serving as the input, this procedure inverts the model to produce the neurological control signals driving muscles and plant. The relationships between these controller signals, and EMG records should contribute to the understanding of the neurological control of movements.

  14. 49 CFR 236.205 - Signal control circuits; requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Signal control circuits; requirements. 236.205... Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so... fouling point derail equipped with switch circuit controller is not in derailing position, (d) When...

  15. 49 CFR 236.205 - Signal control circuits; requirements.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 49 Transportation 4 2012-10-01 2012-10-01 false Signal control circuits; requirements. 236.205... Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so... fouling point derail equipped with switch circuit controller is not in derailing position, (d) When...

  16. 49 CFR 236.205 - Signal control circuits; requirements.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 49 Transportation 4 2014-10-01 2014-10-01 false Signal control circuits; requirements. 236.205... Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so... fouling point derail equipped with switch circuit controller is not in derailing position, (d) When...

  17. 49 CFR 236.205 - Signal control circuits; requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 4 2011-10-01 2011-10-01 false Signal control circuits; requirements. 236.205... Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so... fouling point derail equipped with switch circuit controller is not in derailing position, (d) When...

  18. Missile guidance law design using adaptive cerebellar model articulation controller.

    PubMed

    Lin, Chih-Min; Peng, Ya-Fu

    2005-05-01

    An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law.

  19. Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

    PubMed

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme.

  20. Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

    PubMed

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. PMID:26892402

  1. Mountain chickadees from different elevations sing different songs: acoustic adaptation, temporal drift or signal of local adaptation?

    PubMed

    Branch, Carrie L; Pravosudov, Vladimir V

    2015-04-01

    Song in songbirds is widely thought to function in mate choice and male-male competition. Song is also phenotypically plastic and typically learned from local adults; therefore, it varies across geographical space and can serve as a cue for an individual's location of origin, with females commonly preferring males from their respective location. Geographical variation in song dialect may reflect acoustic adaptation to different environments and/or serve as a signal of local adaptation. In montane environments, environmental differences can occur over an elevation gradient, favouring local adaptations across small spatial scales. We tested whether food caching mountain chickadees, known to exhibit elevation-related differences in food caching intensity, spatial memory and the hippocampus, also sing different dialects despite continuous distribution and close proximity. Male songs were collected from high and low elevations at two different mountains (separated by 35 km) to test whether song differs between elevations and/or between adjacent populations at each mountain. Song structure varied significantly between high and low elevation adjacent populations from the same mountain and between populations from different mountains at the same elevations, despite a continuous distribution across each mountain slope. These results suggest that elevation-related differences in song structure in chickadees might serve as a signal for local adaptation.

  2. Mountain chickadees from different elevations sing different songs: acoustic adaptation, temporal drift or signal of local adaptation?

    PubMed Central

    Branch, Carrie L.; Pravosudov, Vladimir V.

    2015-01-01

    Song in songbirds is widely thought to function in mate choice and male–male competition. Song is also phenotypically plastic and typically learned from local adults; therefore, it varies across geographical space and can serve as a cue for an individual's location of origin, with females commonly preferring males from their respective location. Geographical variation in song dialect may reflect acoustic adaptation to different environments and/or serve as a signal of local adaptation. In montane environments, environmental differences can occur over an elevation gradient, favouring local adaptations across small spatial scales. We tested whether food caching mountain chickadees, known to exhibit elevation-related differences in food caching intensity, spatial memory and the hippocampus, also sing different dialects despite continuous distribution and close proximity. Male songs were collected from high and low elevations at two different mountains (separated by 35 km) to test whether song differs between elevations and/or between adjacent populations at each mountain. Song structure varied significantly between high and low elevation adjacent populations from the same mountain and between populations from different mountains at the same elevations, despite a continuous distribution across each mountain slope. These results suggest that elevation-related differences in song structure in chickadees might serve as a signal for local adaptation. PMID:26064641

  3. Adaptive hybrid position/force control of robotic manipulators

    NASA Technical Reports Server (NTRS)

    Pourboghrat, F.

    1987-01-01

    The problem of position and force control for the compliant motion of the manipulators is considered. The external force and the position of the end-effector are related by a second order impedance function. The force control problem is then translated into a position control problem. For that, an adaptive controller is designed to achieve the compliant motion. The design uses the Liapunov's direct method to derive the adaptation law. The stability of the process is guaranteed from the Liapunov's stability theory. The controller does not require the knowledge of the system parameters for the implementation, and hence is easy for applications.

  4. Digital adaptive controllers for VTOL vehicles. Volume 1: Concept evaluation

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.; Pratt, S. G.

    1979-01-01

    A digital self-adaptive flight control system was developed for flight test in the VTOL approach and landing technology (VALT) research aircraft (a modified CH-47 helicopter). The control laws accept commands from an automatic on-board guidance system. The primary objective of the control laws is to provide good command-following with a minimum cross-axis response. Three attitudes and vertical velocity are separately commanded. Adaptation of the control laws is based on information from rate and attitude gyros and a vertical velocity measurement. The final design resulted from a comparison of two different adaptive concepts--one based on explicit parameter estimates from a real-time maximum-likelihood estimation algorithm, the other based on an implicit model reference adaptive system. The two designs were compared on the basis of performance and complexity.

  5. Adaptive Wavefront Calibration and Control for the Gemini Planet Imager

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-02-02

    Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering.

  6. Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.

    PubMed

    Peng, Jinzhu; Yu, Jie; Wang, Jie

    2014-07-01

    In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. PMID:24917071

  7. Reduced error signalling in medication-naive children with ADHD: associations with behavioural variability and post-error adaptations

    PubMed Central

    Plessen, Kerstin J.; Allen, Elena A.; Eichele, Heike; van Wageningen, Heidi; Høvik, Marie Farstad; Sørensen, Lin; Worren, Marius Kalsås; Hugdahl, Kenneth; Eichele, Tom

    2016-01-01

    Background We examined the blood-oxygen level–dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). Methods We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8–12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations. Results We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. Limitations Our study was limited by the modest sample size and imperfect matching across groups. Conclusion Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD. PMID:26441332

  8. Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2012-01-01

    This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

  9. To adapt or not to adapt: the question of domain-general cognitive control.

    PubMed

    Kan, Irene P; Teubner-Rhodes, Susan; Drummey, Anna B; Nutile, Lauren; Krupa, Lauren; Novick, Jared M

    2013-12-01

    What do perceptually bistable figures, sentences vulnerable to misinterpretation and the Stroop task have in common? Although seemingly disparate, they all contain elements of conflict or ambiguity. Consequently, in order to monitor a fluctuating percept, reinterpret sentence meaning, or say "blue" when the word RED is printed in blue ink, individuals must regulate attention and engage cognitive control. According to the Conflict Monitoring Theory (Botvinick, Braver, Barch, Carter, & Cohen, 2001), the detection of conflict automatically triggers cognitive control mechanisms, which can enhance resolution of subsequent conflict, namely, "conflict adaptation." If adaptation reflects the recruitment of domain-general processes, then conflict detection in one domain should facilitate conflict resolution in an entirely different domain. We report two novel findings: (i) significant conflict adaptation from a syntactic to a non-syntactic domain and (ii) from a perceptual to a verbal domain, providing strong evidence that adaptation is mediated by domain-general cognitive control. PMID:24103774

  10. Membrane transporters mediating root signalling and adaptive responses to oxygen deprivation and soil flooding.

    PubMed

    Shabala, Sergey; Shabala, Lana; Barcelo, Juan; Poschenrieder, Charlotte

    2014-10-01

    This review provides a comprehensive assessment of a previously unexplored topic: elucidating the role that plasma- and organelle-based membrane transporters play in plant-adaptive responses to flooding. We show that energy availability and metabolic shifts under hypoxia and anoxia are critical in regulating membrane-transport activity. We illustrate the high tissue and time dependence of this regulation, reveal the molecular identity of transporters involved and discuss the modes of their regulation. We show that both reduced oxygen availability and accumulation of transition metals in flooded roots result in a reduction in the cytosolic K(+) pool, ultimately determining the cell's fate and transition to programmed cell death (PCD). This process can be strongly affected by hypoxia-induced changes in the amino acid pool profile and, specifically, ϒ-amino butyric acid (GABA) accumulation. It is suggested that GABA plays an important regulatory role, allowing plants to proceed with H2 O2 signalling to activate a cascade of genes that mediate plant adaptation to flooding while at the same time, preventing the cell from entering a 'suicide program'. We conclude that progress in crop breeding for flooding tolerance can only be achieved by pyramiding the numerous physiological traits that confer efficient energy maintenance, cytosolic ion homeostasis, and reactive oxygen species (ROS) control and detoxification.

  11. Membrane transporters mediating root signalling and adaptive responses to oxygen deprivation and soil flooding.

    PubMed

    Shabala, Sergey; Shabala, Lana; Barcelo, Juan; Poschenrieder, Charlotte

    2014-10-01

    This review provides a comprehensive assessment of a previously unexplored topic: elucidating the role that plasma- and organelle-based membrane transporters play in plant-adaptive responses to flooding. We show that energy availability and metabolic shifts under hypoxia and anoxia are critical in regulating membrane-transport activity. We illustrate the high tissue and time dependence of this regulation, reveal the molecular identity of transporters involved and discuss the modes of their regulation. We show that both reduced oxygen availability and accumulation of transition metals in flooded roots result in a reduction in the cytosolic K(+) pool, ultimately determining the cell's fate and transition to programmed cell death (PCD). This process can be strongly affected by hypoxia-induced changes in the amino acid pool profile and, specifically, ϒ-amino butyric acid (GABA) accumulation. It is suggested that GABA plays an important regulatory role, allowing plants to proceed with H2 O2 signalling to activate a cascade of genes that mediate plant adaptation to flooding while at the same time, preventing the cell from entering a 'suicide program'. We conclude that progress in crop breeding for flooding tolerance can only be achieved by pyramiding the numerous physiological traits that confer efficient energy maintenance, cytosolic ion homeostasis, and reactive oxygen species (ROS) control and detoxification. PMID:24689809

  12. Nutrient-dependent/pheromone-controlled adaptive evolution: a model

    PubMed Central

    Kohl, James Vaughn

    2013-01-01

    Background The prenatal migration of gonadotropin-releasing hormone (GnRH) neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors. Methods This model details how chemical ecology drives adaptive evolution via: (1) ecological niche construction, (2) social niche construction, (3) neurogenic niche construction, and (4) socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH) and systems biology. Results Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man. Conclusion An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively fit individuals

  13. Adaptive Robotic Control Driven by a Versatile Spiking Cerebellar Network

    PubMed Central

    Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A.; Carrillo, Richard R.; Luque, Niceto R.; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

    2014-01-01

    The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions. PMID:25390365

  14. Adaptive robotic control driven by a versatile spiking cerebellar network.

    PubMed

    Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

    2014-01-01

    The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions. PMID:25390365

  15. Adaptive control with an expert system based supervisory level. Thesis

    NASA Technical Reports Server (NTRS)

    Sullivan, Gerald A.

    1991-01-01

    Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up

  16. Short-term adaptation of the VOR: non-retinal-slip error signals and saccade substitution

    NASA Technical Reports Server (NTRS)

    Eggers, Sscott D Z.; De Pennington, Nick; Walker, Mark F.; Shelhamer, Mark; Zee, David S.

    2003-01-01

    We studied short-term (30 min) adaptation of the vestibulo-ocular reflex (VOR) in five normal humans using a "position error" stimulus without retinal image motion. Both before and after adaptation a velocity gain (peak slow-phase eye velocity/peak head velocity) and a position gain (total eye movement during chair rotation/amplitude of chair motion) were measured in darkness using search coils. The vestibular stimulus was a brief ( approximately 700 ms), 15 degrees chair rotation in darkness (peak velocity 43 degrees /s). To elicit adaptation, a straight-ahead fixation target disappeared during chair movement and when the chair stopped the target reappeared at a new location in front of the subject for gain-decrease (x0) adaptation, or 10 degrees opposite to chair motion for gain-increase (x1.67) adaptation. This position-error stimulus was effective at inducing VOR adaptation, though for gain-increase adaptation the primary strategy was to substitute augmenting saccades during rotation while for gain-decrease adaptation both corrective saccades and a decrease in slow-phase velocity occurred. Finally, the presence of the position-error signal alone, at the end of head rotation, without any attempt to fix upon it, was not sufficient to induce adaptation. Adaptation did occur, however, if the subject did make a saccade to the target after head rotation, or even if the subject paid attention to the new location of the target without actually looking at it.

  17. Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

    NASA Technical Reports Server (NTRS)

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  18. Adaptive process control using fuzzy logic and genetic algorithms

    NASA Technical Reports Server (NTRS)

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  19. Adaptive pitch control for load mitigation of wind turbines

    NASA Astrophysics Data System (ADS)

    Yuan, Yuan; Tang, J.

    2015-04-01

    In this research, model reference adaptive control is examined for the pitch control of wind turbines that may suffer from reduced life owing to extreme loads and fatigue when operated under a high wind speed. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to track the optimal generator speed and at the same time to mitigate component loads under turbulent wind field and other uncertainties. The proposed algorithm is tested on the NREL offshore 5-MW baseline wind turbine, and its performance is compared with that those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC). The results show that the blade root flapwise load can be reduced at a slight expense of optimal power output. The generator speed regulation under adaptive controller is better than DAC.

  20. An adaptive learning control system for aircraft

    NASA Technical Reports Server (NTRS)

    Mekel, R.; Nachmias, S.

    1978-01-01

    A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.

  1. Lymphotoxin Signaling in Immune Homeostasis and the Control of Microorganisms

    PubMed Central

    Upadhyay, Vaibhav; Fu, Yang-Xin

    2014-01-01

    Lymphotoxin (LT) is a member of the tumour necrosis factor (TNF) superfamily that was originally thought to be functionally redundant to TNF, but these proteins were later found to have independent roles in driving lymphoid organogenesis. More recently, LT mediated signalling has been shown to actively contribute to effector immune responses. LT regulates dendritic cell and CD4+ T cell homeostasis in the steady state and determines the functions of these cells during pathogenic challenges. The LT receptor pathway is essential for controlling pathogens and even contributes to the regulation of the intestinal microbiota, with recent data suggesting that LT induced changes in the microbiota promote metabolic disease. In this Review, we discuss these newly defined roles for LT, with a particular focus on how the LT receptor pathway regulates innate and adaptive immune responses to microorganisms. PMID:23524463

  2. Endocannabinoid signaling in the amygdala: anatomy, synaptic signaling, behavior, and adaptations to stress

    PubMed Central

    Ramikie, Teniel S.; Patel, Sachin

    2011-01-01

    The molecular constituents of endogenous cannabinoid (eCB) signaling are abundantly expressed within the mammalian amygdaloid complex, consistent with the robust role of eCB signaling in the modulation of emotional behavior, learning, and stress-response physiology. Here we detail the anatomical distribution of eCB signaling machinery in the amygdala and the role of this system in the modulation of excitatory and inhibitory neuroplasticity in this region. We also summarize recent findings demonstrating dynamic alternations in eCB signaling that occur in response to stress exposure, as well as known behavioral consequences of eCB-mediated modulation of amygdala function. Finally, we discuss how integrating anatomical and physiological data regarding eCB signaling in the amygdala could help elucidate common functional motifs of this system in relation to broader forebrain function. PMID:21884761

  3. Adaptive feed-forward loop connection based on error signal

    NASA Astrophysics Data System (ADS)

    Hidaka, Koichi

    2005-12-01

    In this paper, we investigate effect of changing the connection of feed-forward loop based on error signal. Our motivation of this work is solution to progress of human skill. For the skill model, we study a human simple action such as arm motion. Many models that describe the human arm dynamics have been proposed in recent year. While one type does not need an inverse model of human dynamics, the system based on the model does not include feed-forward loop. On the other hand, another type model has a feed-forward loop and feedback loop systems. This type assumes feed-forward element includes an internal model by repeating action or training and this loop progress our skill. Then we usually have to exercise to get a good performance. This says that we design the internal motion model by training and we move on prediction for motion. Under the assumption, Kawato model is well known. The model proposed that learning of feed-forward element is promoted in brain so that the error of feedback loop decreases. Furthermore, we assume the connections in feedback loop and feed-forward loop are changed. We show numerical simulations and consider that the position error given by our vision changes the skill element and we confirm that the position error is the one of the estimate function for the improvement in our skill.

  4. Interference cancellation in RF signals using adaptive array techniques

    NASA Astrophysics Data System (ADS)

    Brown, Mark E.

    1990-12-01

    This study investigated the effectiveness of the least means squared (LMS) algorithm against various types of common jammers. The LMS algorithm was implemented using the block oriented systems simulator (BOSS). The LMS algorithm was inserted at the output of a two element antenna array. The array was configured so as to have one-half wavelength spacing. A quadrature hybrid signal structure was used. The array was then tested against a barrage and sweep jammer. The barrage jammer testing consisted of varying each of the three available jammer parameters: power, frequency, and angle of arrival individually. The sweep jammer testing consisted of varying each of the three available jammer parameters; power, sweep frequency and angle of arrival individually. The results of the simulation showed the LMS algorithm in combination with the quadrature hybrid was very effective against both the barrage and sweep jammers. It provided a 55 dB null in the barrage jammer cases and a 50 dB null in the sweep jammer case.

  5. Adaptive control of nonlinear systems with actuator failures and uncertainties

    NASA Astrophysics Data System (ADS)

    Tang, Xidong

    2005-11-01

    Actuator failures have damaging effect on the performance of control systems, leading to undesired system behavior or even instability. Actuator failures are unknown in terms of failure time instants, failure patterns, and failure parameters. For system safety and reliability, the compensation of actuator failures is of both theoretical and practical significance. This dissertation is to further the study of adaptive designs for actuator failure compensation to nonlinear systems. In this dissertation a theoretical framework for adaptive control of nonlinear systems with actuator failures and system uncertainties is established. The contributions are the development of new adaptive nonlinear control schemes to handle unknown actuator failures for convergent tracking performance, the specification of conditions as a guideline for applications and system designs, and the extension of the adaptive nonlinear control theory. In the dissertation, adaptive actuator failure compensation is studied for several classes of nonlinear systems. In particular, adaptive state feedback schemes are developed for feedback linearizable systems and parametric strict-feedback systems. Adaptive output feedback schemes are deigned for output-feedback systems and a class of systems with unknown state-dependent nonlinearities. Furthermore, adaptive designs are addressed for MIMO systems with actuator failures, based on two grouping techniques: fixed grouping and virtual grouping. Theoretical issues such as controller structures, actuation schemes, zero dynamics, observation, grouping conditions, closed-loop stability, and tracking performance are extensively investigated. For each scheme, design conditions are clarified, and detailed stability and performance analysis is presented. A variety of applications including a wing-rock model, twin otter aircraft, hypersonic aircraft, and cooperative multiple manipulators are addressed with simulation results showing the effectiveness of the

  6. Non-linear adaptive sliding mode switching control with average dwell-time

    NASA Astrophysics Data System (ADS)

    Yu, Lei; Zhang, Maoqing; Fei, Shumin

    2013-03-01

    In this article, an adaptive integral sliding mode control scheme is addressed for switched non-linear systems in the presence of model uncertainties and external disturbances. The control law includes two parts: a slide mode controller for the reduced model of the plant and a compensation controller to deal with the non-linear systems with parameter uncertainties. The adaptive updated laws have been derived from the switched multiple Lyapunov function method, also an admissible switching signal with average dwell-time technique is given. The simplicity of the proposed control scheme facilitates its implementation and the overall control scheme guarantees the global asymptotic stability in the Lyapunov sense such that the sliding surface of the control system is well reached. Simulation results are presented to demonstrate the effectiveness and the feasibility of the proposed approach.

  7. Investigation of the Multiple Model Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The application was investigated of control theoretic ideas to the design of flight control systems for the F-8 aircraft. The design of an adaptive control system based upon the so-called multiple model adaptive control (MMAC) method is considered. Progress is reported.

  8. Adaptive control of Hammerstein-Wiener nonlinear systems

    NASA Astrophysics Data System (ADS)

    Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong

    2016-07-01

    The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.

  9. Combining human volitional control with intrinsic controller on robotic prosthesis: A case study on adaptive slope walking.

    PubMed

    Chen, Baojun; Wang, Qining

    2015-01-01

    Affording lower-limb amputees the ability to volitionally control robotic prostheses can improve the adaptability to terrain changes as well as enhancing proprioception. However, it also increases amputees' conscious burdens for prosthesis control. Therefore, in this paper, we aim to propose a hybrid controller which combines human volitional control with the intrinsic controller on the robotic transtibial prosthesis, enabling the amputee actively controlling prosthesis with little conscious attention. In this preliminary study, a hybrid controller for adaptive slope walking was designed. A slope estimator was embedded in the intrinsic controller to estimate the ground slope of the previous step using signals measured by prosthetic sensors. And a myoelectric controller allows the amputee subject to convey slope changes to prosthetic controller by volitionally contract his residual muscles, whose electromyography signals were mapped to the slope increment. The hybrid controller combined these two results to obtain the estimated slope. One male transtibial amputee subject was recruited in this research. Experiment results showed that the intrinsic slope estimator produced satisfactory estimation results with an average absolute error of 0.70 ± 0.54 degrees. By adding amputee's volitional control, the hybrid controller is able to predict the upcoming slope changes. PMID:26737362

  10. Robust control of a bimorph mirror for adaptive optics systems.

    PubMed

    Baudouin, Lucie; Prieur, Christophe; Guignard, Fabien; Arzelier, Denis

    2008-07-10

    We apply robust control techniques to an adaptive optics system including a dynamic model of the deformable mirror. The dynamic model of the mirror is a modification of the usual plate equation. We propose also a state-space approach to model the turbulent phase. A continuous time control of our model is suggested, taking into account the frequential behavior of the turbulent phase. An H(infinity) controller is designed in an infinite-dimensional setting. Because of the multivariable nature of the control problem involved in adaptive optics systems, a significant improvement is obtained with respect to traditional single input-single output methods.

  11. Pressure regulation for earth pressure balance control on shield tunneling machine by using adaptive robust control

    NASA Astrophysics Data System (ADS)

    Xie, Haibo; Liu, Zhibin; Yang, Huayong

    2016-05-01

    Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

  12. A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis

    PubMed Central

    Alibeji, Naji A.; Kirsch, Nicholas Andrew; Sharma, Nitin

    2015-01-01

    A hybrid neuroprosthesis that uses an electric motor-based wearable exoskeleton and functional electrical stimulation (FES) has a promising potential to restore walking in persons with paraplegia. A hybrid actuation structure introduces effector redundancy, making its automatic control a challenging task because multiple muscles and additional electric motor need to be coordinated. Inspired by the muscle synergy principle, we designed a low dimensional controller to control multiple effectors: FES of multiple muscles and electric motors. The resulting control system may be less complex and easier to control. To obtain the muscle synergy-inspired low dimensional control, a subject-specific gait model was optimized to compute optimal control signals for the multiple effectors. The optimal control signals were then dimensionally reduced by using principal component analysis to extract synergies. Then, an adaptive feedforward controller with an update law for the synergy activation was designed. In addition, feedback control was used to provide stability and robustness to the control design. The adaptive-feedforward and feedback control structure makes the low dimensional controller more robust to disturbances and variations in the model parameters and may help to compensate for other time-varying phenomena (e.g., muscle fatigue). This is proven by using a Lyapunov stability analysis, which yielded semi-global uniformly ultimately bounded tracking. Computer simulations were performed to test the new controller on a 4-degree of freedom gait model. PMID:26734606

  13. Decentralized adaptive control of manipulators - Theory, simulation, and experimentation

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1989-01-01

    The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.

  14. Online Parameter Estimation and Adaptive Control of Magnetic Wire Actuators

    NASA Astrophysics Data System (ADS)

    Karve, Harshwardhan

    Cantilevered magnetic wires and fibers can be used as actuators in microfluidic applications. The actuator may be unstable in some range of displacements. Precise position control is required for actuation. The goal of this work is to develop position controllers for cantilevered magnetic wires. A simple exact model knowledge (EMK) controller can be used for position control, but the actuator needs to be modeled accurately for the EMK controller to work. Continuum models have been proposed for magnetic wires in literature. Reduced order models have also been proposed. A one degree of freedom model sufficiently describes the dynamics of a cantilevered wire in the field of one magnet over small displacements. This reduced order model is used to develop the EMK controller here. The EMK controller assumes that model parameters are known accurately. Some model parameters depend on the magnetic field. However, the effect of the magnetic field on the wire is difficult to measure in practice. Stability analysis shows that an inaccurate estimate of the magnetic field introduces parametric perturbations in the closed loop system. This makes the system less robust to disturbances. Therefore, the model parameters need to be estimated accurately for the EMK controller to work. An adaptive observer that can estimate system parameters on-line and reduce parametric perturbations is designed here. The adaptive observer only works if the system is stable. The EMK controller is not guaranteed to stabilize the system under perturbations. Precise tuning of parameters is required to stabilize the system using the EMK controller. Therefore, a controller that stabilizes the system using imprecise model parameters is required for the observer to work as intended. The adaptive observer estimates system states and parameters. These states and parameters are used here to implement an indirect adaptive controller. This indirect controller can stabilize the system using imprecise initial

  15. Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

    PubMed Central

    Abbaspour, S; Fallah, A

    2014-01-01

    Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective: Removing electrocardiogram contamination from electromyogram signals. Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction. Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods. Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result. PMID:25505766

  16. Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

    PubMed Central

    Wang, Ruliang; Li, Jie; Zhang, Shanshan; Gao, Dongmei; Sun, Huanlong

    2013-01-01

    We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme. PMID:23853544

  17. [Adaptive de-noising of ECG signal based on stationary wavelet transform].

    PubMed

    Dong, Hong-sheng; Zhang, Ai-hua; Hao, Xiao-hong

    2009-03-01

    According to the limitations of wavelet threshold in de-noising method, we approached a combining algorithm of the stationary wavelet transform with adaptive filter. The stationary wavelet transformation can suppress Gibbs phenomena in traditional DWT effectively, and adaptive filter is introduced at the high scale wavelet coefficient of the stationary wavelet transformation. It would remove baseline wander and keep the shape of low frequency and low amplitude P wave, T wave and ST segment wave of ECG signal well. That is important for analyzing ECG signal of other feature information.

  18. Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

    NASA Technical Reports Server (NTRS)

    Gundy-Burlet, Karen; Krishnakumar, K.; Limes, Greg; Bryant, Don

    2003-01-01

    This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.

  19. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  20. Adaptive measurement control for calorimetric assay

    SciTech Connect

    Glosup, J.G.; Axelrod, M.C.

    1994-10-01

    The performance of a calorimeter is usually evaluated by constructing a Shewhart control chart of its measurement errors for a collection of reference standards. However, Shewhart control charts were developed in a manufacturing setting where observations occur in batches. Additionally, the Shewhart control chart expects the variance of the charted variable to be known or at least well estimated from previous experimentation. For calorimetric assay, observations are collected singly in a time sequence with a (possibly) changing mean, and extensive experimentation to calculate the variance of the measurement errors is seldom feasible. These facts pose problems in constructing a control chart. In this paper, the authors propose using the mean squared successive difference to estimate the variance of measurement errors based solely on prior observations. This procedure reduces or eliminates estimation bias due to a changing mean. However, the use of this estimator requires an adjustment to the definition of the alarm and warning limits for the Shewhart control chart. The authors propose adjusted limits based on an approximate Student`s t-distribution for the measurement errors and discuss the limitations of this approximation. Suggestions for the practical implementation of this method are provided also.

  1. Control of the Adaptive Immune Response by Tumor Vasculature

    PubMed Central

    Mauge, Laetitia; Terme, Magali; Tartour, Eric; Helley, Dominique

    2014-01-01

    The endothelium is nowadays described as an entire organ that regulates various processes: vascular tone, coagulation, inflammation, and immune cell trafficking, depending on the vascular site and its specific microenvironment as well as on endothelial cell-intrinsic mechanisms like epigenetic changes. In this review, we will focus on the control of the adaptive immune response by the tumor vasculature. In physiological conditions, the endothelium acts as a barrier regulating cell trafficking by specific expression of adhesion molecules enabling adhesion of immune cells on the vessel, and subsequent extravasation. This process is also dependent on chemokine and integrin expression, and on the type of junctions defining the permeability of the endothelium. Endothelial cells can also regulate immune cell activation. In fact, the endothelial layer can constitute immunological synapses due to its close interactions with immune cells, and the delivery of co-stimulatory or co-inhibitory signals. In tumor conditions, the vasculature is characterized by an abnormal vessel structure and permeability, and by a specific phenotype of endothelial cells. All these abnormalities lead to a modulation of intra-tumoral immune responses and contribute to the development of intra-tumoral immunosuppression, which is a major mechanism for promoting the development, progression, and treatment resistance of tumors. The in-depth analysis of these various abnormalities will help defining novel targets for the development of anti-tumoral treatments. Furthermore, eventual changes of the endothelial cell phenotype identified by plasma biomarkers could secondarily be selected to monitor treatment efficacy. PMID:24734218

  2. AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal

    PubMed Central

    Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

    2015-01-01

    An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665

  3. AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.

    PubMed

    Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

    2015-10-23

    An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal.

  4. Simulation of a Reconfigurable Adaptive Control Architecture

    NASA Astrophysics Data System (ADS)

    Rapetti, Ryan John

    A set of algorithms and software components are developed to investigate the use of a priori models of damaged aircraft to improve control of similarly damaged aircraft. An addition to Model Predictive Control called state trajectory extrapolation is also developed to deliver good handling qualities in nominal an off-nominal aircraft. System identification algorithms are also used to improve model accuracy after a damage event. Simulations were run to demonstrate the efficacy of the algorithms and software components developed herein. The effect of model order on system identification convergence and performance is also investigated. A feasibility study for flight testing is also conducted. A preliminary hardware prototype was developed, as was the necessary software to integrate the avionics and ground station systems. Simulation results show significant improvement in both tracking and cross-coupling performance when a priori control models are used, and further improvement when identified models are used.

  5. An experimental SMI adaptive antenna array simulator for weak interfering signals

    NASA Technical Reports Server (NTRS)

    Dilsavor, Ronald S.; Gupta, Inder J.

    1991-01-01

    An experimental sample matrix inversion (SMI) adaptive antenna array for suppressing weak interfering signals is described. The experimental adaptive array uses a modified SMI algorithm to increase the interference suppression. In the modified SMI algorithm, the sample covariance matrix is redefined to reduce the effect of thermal noise on the weights of an adaptive array. This is accomplished by subtracting a fraction of the smallest eigenvalue of the original covariance matrix from its diagonal entries. The test results obtained using the experimental system are compared with theoretical results. The two show a good agreement.

  6. Adaptive control system for pulsed megawatt klystrons

    DOEpatents

    Bolie, Victor W.

    1992-01-01

    The invention provides an arrangement for reducing waveform errors such as errors in phase or amplitude in output pulses produced by pulsed power output devices such as klystrons by generating an error voltage representing the extent of error still present in the trailing edge of the previous output pulse, using the error voltage to provide a stored control voltage, and applying the stored control voltage to the pulsed power output device to limit the extent of error in the leading edge of the next output pulse.

  7. Design of smart composite platforms for adaptive trust vector control and adaptive laser telescope for satellite applications

    NASA Astrophysics Data System (ADS)

    Ghasemi-Nejhad, Mehrdad N.

    2013-04-01

    This paper presents design of smart composite platforms for adaptive trust vector control (TVC) and adaptive laser telescope for satellite applications. To eliminate disturbances, the proposed adaptive TVC and telescope systems will be mounted on two analogous smart composite platform with simultaneous precision positioning (pointing) and vibration suppression (stabilizing), SPPVS, with micro-radian pointing resolution, and then mounted on a satellite in two different locations. The adaptive TVC system provides SPPVS with large tip-tilt to potentially eliminate the gimbals systems. The smart composite telescope will be mounted on a smart composite platform with SPPVS and then mounted on a satellite. The laser communication is intended for the Geosynchronous orbit. The high degree of directionality increases the security of the laser communication signal (as opposed to a diffused RF signal), but also requires sophisticated subsystems for transmission and acquisition. The shorter wavelength of the optical spectrum increases the data transmission rates, but laser systems require large amounts of power, which increases the mass and complexity of the supporting systems. In addition, the laser communication on the Geosynchronous orbit requires an accurate platform with SPPVS capabilities. Therefore, this work also addresses the design of an active composite platform to be used to simultaneously point and stabilize an intersatellite laser communication telescope with micro-radian pointing resolution. The telescope is a Cassegrain receiver that employs two mirrors, one convex (primary) and the other concave (secondary). The distance, as well as the horizontal and axial alignment of the mirrors, must be precisely maintained or else the optical properties of the system will be severely degraded. The alignment will also have to be maintained during thruster firings, which will require vibration suppression capabilities of the system as well. The innovative platform has been

  8. Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

    PubMed Central

    Zhao, Guoliang; Li, Hongxing

    2013-01-01

    This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model. PMID:24453897

  9. Tensor product model transformation based adaptive integral-sliding mode controller: equivalent control method.

    PubMed

    Zhao, Guoliang; Sun, Kaibiao; Li, Hongxing

    2013-01-01

    This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  10. Application of Feedforward Adaptive Active-Noise Control for Reducing Blade Passing Noise in Centrifugal Fans

    NASA Astrophysics Data System (ADS)

    WU, J.-D.; BAI, M. R.

    2001-02-01

    This paper describes two configurations of feedforward adaptive active-noise control (ANC) technique for reducing blade passing noise in centrifugal fans. In one configuration, the control speaker is installed at the cut-off region of the fan, while in the other configuration at the exit duct. The proposed ANC system is based on the filtered-x least-mean-squares (FXLMS) algorithm with multi-sine synthesized reference signal and frequency counting and is implemented by using a digital signal processor (DSP). Experiments are carried out to evaluate the proposed system for reducing the noise at the blade passing frequency (BPF) and its harmonics at various flow speeds. The results of the experiment indicated that the ANC technique is effective in reducing the blade passing noise for two configurations by using the feedforward adaptive control.

  11. Embedded intelligent adaptive PI controller for an electromechanical system.

    PubMed

    El-Nagar, Ahmad M

    2016-09-01

    In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. PMID:27342993

  12. Adaptive Identification and Control of Flow-Induced Cavity Oscillations

    NASA Technical Reports Server (NTRS)

    Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

    2002-01-01

    Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

  13. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    NASA Astrophysics Data System (ADS)

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-06-01

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller.

  14. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    SciTech Connect

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-06-12

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller.

  15. Adaptive fuzzy backstepping control for a class of switched nonlinear systems with actuator faults

    NASA Astrophysics Data System (ADS)

    Hou, Yingxue; Tong, Shaocheng; Li, Yongming

    2016-11-01

    This paper investigates the problem of fault-tolerant control (FTC) for a class of switched nonlinear systems. These systems are under arbitrary switchings and are subject to both lock-in-place and loss-of-effectiveness actuator faults. In the control design, fuzzy logic systems are used to identify the unknown switched nonlinear systems. Under the framework of the backstepping control design, FTC, fuzzy adaptive control and common Lyapunov function stability theory, an adaptive fuzzy control approach is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop switched system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error remains an adjustable neighbourhood of the origin. Two simulation examples are provided to illustrate the effectiveness of the proposed approach.

  16. Adaptive Power Control for Space Communications

    NASA Technical Reports Server (NTRS)

    Thompson, Willie L., II; Israel, David J.

    2008-01-01

    This paper investigates the implementation of power control techniques for crosslinks communications during a rendezvous scenario of the Crew Exploration Vehicle (CEV) and the Lunar Surface Access Module (LSAM). During the rendezvous, NASA requires that the CEV supports two communication links: space-to-ground and crosslink simultaneously. The crosslink will generate excess interference to the space-to-ground link as the distances between the two vehicles decreases, if the output power is fixed and optimized for the worst-case link analysis at the maximum distance range. As a result, power control is required to maintain the optimal power level for the crosslink without interfering with the space-to-ground link. A proof-of-concept will be described and implemented with Goddard Space Flight Center (GSFC) Communications, Standard, and Technology Lab (CSTL).

  17. Quality control agent: Self-adaptive laser vibrometry for on-line diagnostics

    NASA Astrophysics Data System (ADS)

    Serafini, S.; Paone, N.; Castellini, P.

    2012-06-01

    It is presented the development of a self-adaptive diagnostic system based on laser vibrometry for production line quality control. The vibration measurement system consists of a laser Doppler vibrometer, equipped with scanning mirrors and a smart camera, which implements self-adaptivity for compensating target mis-positioning under guidance by a vision system and for the achievement of the best condition for measurement by optimizing the Doppler signal level. This system is designed as a Quality Control Agent (QCA) and it is part of a Multi Agent System (MAS) that supervises all the production line. The QCA behavior is defined so to perform a minimization of measurement uncertainty during the on line tests; for this purpose the QCA exhibits a self-adaptive behavior. Best measurement conditions are defined in terms of amplitude of the optical Doppler beat signal (signal quality - SQ). In this paper, the optimization strategy for measurement enhancement achieved by the down-hill algorithm (Nelder-Mead algorithm) and its effect on signal quality improvement is discussed. Tests on a washing machine in controlled operating conditions allow to evaluate the efficacy of the method; significant reduction of noise on vibration velocity spectra is observed.

  18. Adapting Inspection Data for Computer Numerical Control

    NASA Technical Reports Server (NTRS)

    Hutchison, E. E.

    1986-01-01

    Machining time for repetitive tasks reduced. Program converts measurements of stub post locations by coordinate-measuring machine into form used by numerical-control computer. Work time thus reduced by 10 to 15 minutes for each post. Since there are 600 such posts on each injector, time saved per injector is 100 to 150 hours. With modifications this approach applicable to machining of many precise holes on large machine frames and similar objects.

  19. Adaptive neural network motion control of manipulators with experimental evaluations.

    PubMed

    Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910

  20. Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations

    PubMed Central

    Puga-Guzmán, S.; Moreno-Valenzuela, J.; Santibáñez, V.

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910

  1. Adaptive neural network motion control of manipulators with experimental evaluations.

    PubMed

    Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller.

  2. Adaptive control experiment with a large flexible structure

    NASA Technical Reports Server (NTRS)

    Ih, Che-Hang Charles; Bayard, David S.; Wang, Shyh Jong; Eldred, Daniel B.

    1988-01-01

    A large space antenna-like ground experiment structure has been developed for conducting research and validation of advanced control technology. A set of proof-of-concept adaptive control experiments for transient and initial deflection regulation with a small set of sensors and actuators were conducted. Very limited knowledge of the plant dynamics and its environment was used in the design of the adaptive controller so that performance could be demonstrated under conditions of gross underlying uncertainties. High performance has been observed under such stringent conditions. These experiments have established a baseline for future studies involving more complex hardware and environmental conditions, and utilizing additional sets of sensors and actuators.

  3. Real-time control system for adaptive resonator

    SciTech Connect

    Flath, L; An, J; Brase, J; Hurd, R; Kartz, M; Sawvel, R; Silva, D

    2000-07-24

    Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

  4. Adaptive Transmission Control Method for Communication-Broadcasting Integrated Services

    NASA Astrophysics Data System (ADS)

    Koto, Hideyuki; Furuya, Hiroki; Nakamura, Hajime

    This paper proposes an adaptive transmission control method for massive and intensive telecommunication traffic generated by communication-broadcasting integrated services. The proposed method adaptively controls data transmissions from viewers depending on the congestion states, so that severe congestion can be effectively avoided. Furthermore, it utilizes the broadcasting channel which is not only scalable, but also reliable for controlling the responses from vast numbers of viewers. The performance of the proposed method is evaluated through experiments on a test bed where approximately one million viewers are emulated. The obtained results quantitatively demonstrate the performance of the proposed method and its effectiveness under massive and intensive traffic conditions.

  5. Adaptive Control of Truss Structures for Gossamer Spacecraft

    NASA Technical Reports Server (NTRS)

    Yang Bong-Jun; Calise, anthony J.; Craig, James I.; Whorton, Mark S.

    2007-01-01

    Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.

  6. A Decentralized Adaptive Approach to Fault Tolerant Flight Control

    NASA Technical Reports Server (NTRS)

    Wu, N. Eva; Nikulin, Vladimir; Heimes, Felix; Shormin, Victor

    2000-01-01

    This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.

  7. On Using Exponential Parameter Estimators with an Adaptive Controller

    NASA Technical Reports Server (NTRS)

    Patre, Parag; Joshi, Suresh M.

    2011-01-01

    Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.

  8. Adaptive PIF Control for Permanent Magnet Synchronous Motors Based on GPC

    PubMed Central

    Lu, Shaowu; Tang, Xiaoqi; Song, Bao

    2013-01-01

    To enhance the control performance of permanent magnet synchronous motors (PMSMs), a generalized predictive control (GPC)-based proportional integral feedforward (PIF) controller is proposed for the speed control system. In this new approach, firstly, based on the online identification of controlled model parameters, a simplified GPC law supplies the PIF controller with suitable control parameters according to the uncertainties in the operating conditions. Secondly, the speed reference curve for PMSMs is usually required to be continuous and continuously differentiable according to the general servo system design requirements, so the adaptation of the speed reference is discussed in details in this paper. Hence, the performance of the speed control system using a GPC-based PIF controller is improved for tracking some specified signals. The main motivation of this paper is the extension of GPC law to replace the traditional PI or PIF controllers in industrial applications. The efficacy and usefulness of the proposed controller are verified through experimental results. PMID:23262481

  9. Signalling and obfuscation for congestion control

    NASA Astrophysics Data System (ADS)

    Mareček, Jakub; Shorten, Robert; Yu, Jia Yuan

    2015-10-01

    We aim to reduce the social cost of congestion in many smart city applications. In our model of congestion, agents interact over limited resources after receiving signals from a central agent that observes the state of congestion in real time. Under natural models of agent populations, we develop new signalling schemes and show that by introducing a non-trivial amount of uncertainty in the signals, we reduce the social cost of congestion, i.e., improve social welfare. The signalling schemes are efficient in terms of both communication and computation, and are consistent with past observations of the congestion. Moreover, the resulting population dynamics converge under reasonable assumptions.

  10. Adaptive control and orbit determination for elliptical rendezvous

    NASA Astrophysics Data System (ADS)

    Xu, Lijia; Hu, Yong; Jiang, Tiantian

    2016-10-01

    In this paper, we study the control and orbit determination problems for elliptical rendezvous. Autonomous rendezvous is achieved by the proposed adaptive control based on the measurements of relative position and velocity between the chaser and target spacecraft. Moreover, the target orbital elements can be estimated during the rendezvous process. Finally, the effectiveness of the method is illustrated by simulations.

  11. Study on rule-based adaptive fuzzy excitation control technology

    NASA Astrophysics Data System (ADS)

    Zhao, Hui; Wang, Hong-jun; Liu, Lu-yuan; Yue, You-jun

    2008-10-01

    Power system is a kind of typical non-linear system, it is hard to achieve excellent control performance with conventional PID controller under different operating conditions. Fuzzy parameter adaptive PID exciting controller is very efficient to overcome the influence of tiny disturbances, but the performance of the control system will be worsened when operating conditions of the system change greatly or larger disturbances occur. To solve this problem, this article presents a rule adaptive fuzzy control scheme for synchronous generator exciting system. In this scheme the control rule adaptation is implemented by regulating the value of parameter di under the given proportional divisors K1, K2 and K3 of fuzzy sets Ai and Bi. This rule adaptive mechanism is constituted by two groups of original rules about the self-generation and self-correction of the control rule. Using two groups of rules, the control rule activated by status 1 and 2 in figure 2 system can be regulated automatically and simultaneously at the time instant k. The results from both theoretical analysis and simulation show that the presented scheme is effective and feasible and possesses good performance.

  12. Comparability of naturalistic and controlled observation assessment of adaptive behavior.

    PubMed

    Millham, J; Chilcutt, J; Atkinson, B L

    1978-07-01

    The comparability of retrospective naturalistic and controlled observation assessment of adaptive behavior was evaluated. The number, degree, and direction of discrepancies were evaluated with respect to level of retardation of the client, rater differences, behavior domain sampled, and prior observational base for the ratings. Generally poor comparability between the procedures was found and questions were raised concerning the types of generalizability that can be made from adaptive behavior assessment obtained under the two procedures.

  13. Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

    NASA Technical Reports Server (NTRS)

    Baer-Riedhart, Jennifer L.; Landy, Robert J.

    1987-01-01

    The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.

  14. Adapting End Host Congestion Control for Mobility

    NASA Technical Reports Server (NTRS)

    Eddy, Wesley M.; Swami, Yogesh P.

    2005-01-01

    Network layer mobility allows transport protocols to maintain connection state, despite changes in a node's physical location and point of network connectivity. However, some congestion-controlled transport protocols are not designed to deal with these rapid and potentially significant path changes. In this paper we demonstrate several distinct problems that mobility-induced path changes can create for TCP performance. Our premise is that mobility events indicate path changes that require re-initialization of congestion control state at both connection end points. We present the application of this idea to TCP in the form of a simple solution (the Lightweight Mobility Detection and Response algorithm, that has been proposed in the IETF), and examine its effectiveness. In general, we find that the deficiencies presented are both relatively easily and painlessly fixed using this solution. We also find that this solution has the counter-intuitive property of being both more friendly to competing traffic, and simultaneously more aggressive in utilizing newly available capacity than unmodified TCP.

  15. Adaptive mass expulsion attitude control system

    NASA Technical Reports Server (NTRS)

    Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Carrou, Stephane (Inventor)

    2001-01-01

    An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.

  16. Adaptive Divergence in the Thyroid Hormone Signaling Pathway in the Stickleback Radiation

    PubMed Central

    Kitano, Jun; Lema, Sean C.; Luckenbach, J. Adam; Mori, Seiichi; Kawagishi, Yui; Kusakabe, Makoto; Swanson, Penny; Peichel, Catherine L.

    2010-01-01

    Summary During adaptive radiations, animals colonize diverse environments, which requires adaptation in multiple phenotypic traits [1]. Because hormones mediate the dynamic regulation of suites of phenotypic traits [2–4], evolutionary changes in hormonal signaling pathways might contribute to adaptation to new environments. Here, we report changes in the thyroid hormone signaling pathway in stream-resident ecotypes of threespine stickleback fish (Gasterosteus aculeatus), which have repeatedly evolved from ancestral marine ecotypes [5–8]. Stream-resident fish exhibit a lower plasma concentration of thyroid hormone and a lower metabolic rate, which is likely adaptive for permanent residency in small streams. The thyroid stimulating hormone-β2 (TSHβ2) gene exhibited significantly lower mRNA expression in pituitary glands of stream-resident sticklebacks relative to marine sticklebacks. Some of the difference in TSHβ2 transcript levels can be explained by cis-regulatory differences at the TSHβ2 gene locus. Consistent with these expression differences, a strong signature of divergent natural selection was found at the TSHβ2 genomic locus. By contrast, there were no differences between the marine and stream-resident ecotypes in mRNA levels or genomic sequence in the paralogous TSHβ1 gene. Our data indicate that evolutionary changes in hormonal signaling have played an important role in the postglacial adaptive radiation of sticklebacks. PMID:21093265

  17. Light adaptation alters inner retinal inhibition to shape OFF retinal pathway signaling.

    PubMed

    Mazade, Reece E; Eggers, Erika D

    2016-06-01

    The retina adjusts its signaling gain over a wide range of light levels. A functional result of this is increased visual acuity at brighter luminance levels (light adaptation) due to shifts in the excitatory center-inhibitory surround receptive field parameters of ganglion cells that increases their sensitivity to smaller light stimuli. Recent work supports the idea that changes in ganglion cell spatial sensitivity with background luminance are due in part to inner retinal mechanisms, possibly including modulation of inhibition onto bipolar cells. To determine how the receptive fields of OFF cone bipolar cells may contribute to changes in ganglion cell resolution, the spatial extent and magnitude of inhibitory and excitatory inputs were measured from OFF bipolar cells under dark- and light-adapted conditions. There was no change in the OFF bipolar cell excitatory input with light adaptation; however, the spatial distributions of inhibitory inputs, including both glycinergic and GABAergic sources, became significantly narrower, smaller, and more transient. The magnitude and size of the OFF bipolar cell center-surround receptive fields as well as light-adapted changes in resting membrane potential were incorporated into a spatial model of OFF bipolar cell output to the downstream ganglion cells, which predicted an increase in signal output strength with light adaptation. We show a prominent role for inner retinal spatial signals in modulating the modeled strength of bipolar cell output to potentially play a role in ganglion cell visual sensitivity and acuity.

  18. Light adaptation alters inner retinal inhibition to shape OFF retinal pathway signaling.

    PubMed

    Mazade, Reece E; Eggers, Erika D

    2016-06-01

    The retina adjusts its signaling gain over a wide range of light levels. A functional result of this is increased visual acuity at brighter luminance levels (light adaptation) due to shifts in the excitatory center-inhibitory surround receptive field parameters of ganglion cells that increases their sensitivity to smaller light stimuli. Recent work supports the idea that changes in ganglion cell spatial sensitivity with background luminance are due in part to inner retinal mechanisms, possibly including modulation of inhibition onto bipolar cells. To determine how the receptive fields of OFF cone bipolar cells may contribute to changes in ganglion cell resolution, the spatial extent and magnitude of inhibitory and excitatory inputs were measured from OFF bipolar cells under dark- and light-adapted conditions. There was no change in the OFF bipolar cell excitatory input with light adaptation; however, the spatial distributions of inhibitory inputs, including both glycinergic and GABAergic sources, became significantly narrower, smaller, and more transient. The magnitude and size of the OFF bipolar cell center-surround receptive fields as well as light-adapted changes in resting membrane potential were incorporated into a spatial model of OFF bipolar cell output to the downstream ganglion cells, which predicted an increase in signal output strength with light adaptation. We show a prominent role for inner retinal spatial signals in modulating the modeled strength of bipolar cell output to potentially play a role in ganglion cell visual sensitivity and acuity. PMID:26912599

  19. Guidelines for Assessing the Need for Adaptive Devices for Visually Impaired Pedestrians at Signalized Intersections.

    ERIC Educational Resources Information Center

    Gallagher, Brian R.; de Oca, Patricia Montes

    1998-01-01

    Presents guidelines for orientation and mobility instructors and traffic engineers to assess the need for adaptive devices to make crosswalks at signalized intersections accessible to pedestrians with visual impairments. The discussions of audible and tactile pedestrian devices, along with case examples, distinguish when each device should be…

  20. Analysis of leptin signalling in hematopoietic cells using an adapted MAPPIT strategy.

    PubMed

    Montoye, T; Piessevaux, J; Lavens, D; Wauman, J; Catteeuw, D; Vandekerckhove, J; Lemmens, I; Tavernier, J

    2006-05-29

    The adipocyte-secreted hormone leptin participates in the regulation of hematopoiesis and enhances proliferation of hematopoietic cells. We used an adaptation of the MAPPIT mammalian two-hybrid method to study leptin signalling in a hematopoietic setting. We confirmed the known interactions of suppressor of cytokine signalling 3 (SOCS3) and STAT5 with the Y985 and Y1077 motifs of the leptin receptor, respectively. We also provide evidence for novel interactions at the Y1077 motif, including phospholipase C gamma and several members of the SOCS protein family, further underscoring the important role of the Y1077 motif in leptin signalling. PMID:16698021

  1. Spatial and temporal control of signaling through lipid rafts.

    PubMed

    Golub, Tamara; Wacha, Stefan; Caroni, Pico

    2004-10-01

    Sphingolipid- and cholesterol-dependent microdomains (rafts) order proteins at biological membranes and have been implicated in most signaling processes at the cell surface, but the principles and mechanisms through which lipid rafts influence signaling are not well understood. Recent studies have revealed how lipid rafts are rapidly redistributed and assembled locally in response to extracellular signals, and how components of raft-based signaling domains undergo rapid and regulated rearrangements influencing signal quality, duration, and strength. These findings highlight the exquisitely dynamic properties of signaling domains based on lipid rafts, and suggest that processes of raft trafficking and assembly take central roles in mediating spatial and temporal control of signaling.

  2. Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

    PubMed

    Zhang, Yanjun; Tao, Gang; Chen, Mou

    2016-09-01

    This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

  3. Signalling and the control of skeletal muscle size

    SciTech Connect

    Otto, Anthony; Patel, Ketan

    2010-11-01

    Skeletal muscle is highly adaptive to environmental stimuli and can alter its mass accordingly. This tissue is almost unique in that it can increase its size through two distinct mechanisms. It can grow through a cellular process mediated by cell fusion, or it can increase its size simply by increasing its protein content. Understanding how these processes are regulated is crucial for the development of potential therapies against debilitating skeletal muscle wasting diseases. Two key signalling molecules, Insulin like Growth Factor (IGF) and GDF-8/myostatin, have emerged in recent years to be potent regulators of skeletal muscle size. In this review we bring together recent data highlighting the important and novel aspects of both molecules and their signalling pathways, culminating in a discussion of the cellular and tissue phenotypic outcomes of their stimulation or antagonism. We emphasise the complex regulatory mechanisms and discuss the temporal and spatial differences that control their action, understanding of which is crucial to further their use as potential therapeutic targets.

  4. Neuro adaptive control for aerospace and distributed systems

    NASA Astrophysics Data System (ADS)

    Das, Abhijit

    Nonlinear and adaptive control is generally considered one of the most effective techniques for stabilizing complex nonlinear systems, where linear control techniques may fail completely. Thousands of research papers are published on either theory or applications of nonlinear and adaptive control. But often one obvious question arises how to implement these techniques in real life model? The best answer that one can think of is to develop simple nonlinear control laws which are easy to implement. Moreover for controlling multi-agent systems, it is often required to distribute the control laws based on limited information available among the agents. This research provides some of these issues in the following way. a) Autopilot design for Aerospace systems: this research developes adaptive backstepping and dynamic inversion methods with internal dynamics stabilization for the quadrotor. Quadrotor helicopter models usually show two main characteristics. First, strong coupling among the system states and second, under-actuation where many states are to be controlled with few control inputs. Due to these unique characteristics, the design of stabilizing control inputs is always challenging for quadrotor models. To confront these problems, first, a dynamic inversion technique with zero dynamics stabilization loop is introduced to a practical quadrotor model, second, an adaptive-backstepping technique is developed to a lagrangian quadrotor model. The stabilizing control laws for both of these techniques are developed using on Lyapunov based method; and b) Coordination of multi-agent systems: coordination among multiple agents is generally done based on balanced or bi-directed communication graph models. If the agents are nonlinear and passive then for a balanced graph model synchronization is possible. But, for other than balanced and bi-directed graph models, it is difficult to synchronize nonlinear systems. Moreover, the performance of synchronization is normally

  5. Effect of the luminance signal on adaptation-based time compression.

    PubMed

    Ayhan, Inci; Bruno, Aurelio; Nishida, Shin'ya; Johnston, Alan

    2011-01-01

    Traditionally, time perception has been considered the product of a central, generic, cognitive mechanism. Recent evidence, however, has shown that high temporal frequency adaptation induces local reductions in the apparent duration of brief intervals suggesting a distributive system with modality-specific sensory components. Here, we examine the effect of the luminance signal on these adaptation-based temporal distortions. Our results show that the luminance signal is crucial to generate duration compression as the effect disappears at isoluminance and that low visibility and task difficulty at isoluminance cannot explain the discrepancy. We also demonstrate that the effects of adaptation on perceived duration are dissociable from those on apparent temporal frequency. These results provide further evidence for the involvement of the magnocellular system in the neural encoding and representation of visual time.

  6. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    Neural networks are developed for controlling a robot-arm and camera system and for processing images. The networks are based upon computational schemes that may be found in the brain. In the first network, a neural map algorithm is employed to control a five-joint pneumatic robot arm and gripper through feedback from two video cameras. The pneumatically driven robot arm employed shares essential mechanical characteristics with skeletal muscle systems. To control the position of the arm, 200 neurons formed a network representing the three-dimensional workspace embedded in a four-dimensional system of coordinates from the two cameras, and learned a set of pressures corresponding to the end effector positions, as well as a set of Jacobian matrices for interpolating between these positions. Because of the properties of the rubber-tube actuators of the arm, the position as a function of supplied pressure is nonlinear, nonseparable, and exhibits hysteresis. Nevertheless, through the neural network learning algorithm the position could be controlled to an accuracy of about one pixel (~3 mm) after two hundred learning steps. Applications of repeated corrections in each step via the Jacobian matrices leads to a very robust control algorithm since the Jacobians learned by the network have to satisfy the weak requirement that they yield a reduction of the distance between gripper and target. The second network is proposed as a model for the mammalian vision system in which backward connections from the primary visual cortex (V1) to the lateral geniculate nucleus play a key role. The application of hebbian learning to the forward and backward connections causes the formation of receptive fields which are sensitive to edges, bars, and spatial frequencies of preferred orientations. The receptive fields are learned in such a way as to maximize the rate of transfer of information from the LGN to V1. Orientational preferences are organized into a feature map in the primary visual

  7. Development of a scalable generic platform for adaptive optics real time control

    NASA Astrophysics Data System (ADS)

    Surendran, Avinash; Burse, Mahesh P.; Ramaprakash, A. N.; Parihar, Padmakar

    2015-06-01

    The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an Adaptive Optics (AO) system, the generation of the Deformable Mirror (DM) control voltages from the Wavefront Sensor (WFS) measurements is usually through the multiplication of the wavefront slopes with a predetermined reconstructor matrix. The ability to access several hundred hard multipliers and memories concurrently in an FPGA allows performance far beyond that of a modern CPU or GPU for tasks with a well-defined structure such as Adaptive Optics control. The target of the current project is to generate a signal for a real time wavefront correction, from the signals coming from a Wavefront Sensor, wherein the system would be flexible to accommodate all the current Wavefront Sensing techniques and also the different methods which are used for wavefront compensation. The system should also accommodate for different data transmission protocols (like Ethernet, USB, IEEE 1394 etc.) for transmitting data to and from the FPGA device, thus providing a more flexible platform for Adaptive Optics control. Preliminary simulation results for the formulation of the platform, and a design of a fully scalable slope computer is presented.

  8. Adaptive Performance Seeking Control Using Fuzzy Model Reference Learning Control and Positive Gradient Control

    NASA Technical Reports Server (NTRS)

    Kopasakis, George

    1997-01-01

    Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.

  9. Adaptive NN Control of a Class of Nonlinear Systems With Asymmetric Saturation Actuators.

    PubMed

    Ma, Jianjun; Ge, Shuzhi Sam; Zheng, Zhiqiang; Hu, Dewen

    2015-07-01

    In this note, adaptive neural network (NN) control is investigated for a class of uncertain nonlinear systems with asymmetric saturation actuators and external disturbances. To handle the effect of nonsmooth asymmetric saturation nonlinearity, a Gaussian error function-based continuous differentiable asymmetric saturation model is employed such that the backstepping technique can be used in the control design. The explosion of complexity in traditional backstepping design is avoided using dynamic surface control. Using radial basis function NN, adaptive control is developed to guarantee that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of origin by appropriately choosing design constants. The effectiveness of the proposed control is demonstrated in the simulation study.

  10. Adaptive independent joint control of manipulators - Theory and experiment

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1988-01-01

    The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

  11. Adaptive control of large space structures using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.

  12. Autonomous and Adaptive Voltage Control using Multiple Distributed Energy Resources

    SciTech Connect

    Li, Huijuan; Li, Fangxing; Xu, Yan; Rizy, D Tom

    2012-01-01

    Voltage regulation using distributed energy resources (DE) or distributed generators (DG) with power electronics interfaces and logic control has drawn increasing interests. This paper addresses the challenges of controlling multiple DEs to regulate voltages in distribution systems using an autonomous and adaptive control approach. Theoretical analysis shows that there exists a corresponding formulation of the dynamic control parameters with multiple DEs. Hence, the proposed control method is theoretically solid. Simulation results confirm that this method is capable of satisfying the fast response requirement for operational use without causing oscillation or inefficiency. This method is autonomous based on local information and the other DEs input without the instructions from any control center, is widely adaptive to variable power system operational situations, and has a high tolerance to data shortage of systems parameter. Hence, it is suitable for broad utility application

  13. Subcellular optogenetics – controlling signaling and single-cell behavior

    PubMed Central

    Karunarathne, W. K. Ajith; O'Neill, Patrick R.; Gautam, Narasimhan

    2015-01-01

    ABSTRACT Variation in signaling activity across a cell plays a crucial role in processes such as cell migration. Signaling activity specific to organelles within a cell also likely plays a key role in regulating cellular functions. To understand how such spatially confined signaling within a cell regulates cell behavior, tools that exert experimental control over subcellular signaling activity are required. Here, we discuss the advantages of using optogenetic approaches to achieve this control. We focus on a set of optical triggers that allow subcellular control over signaling through the activation of G-protein-coupled receptors (GPCRs), receptor tyrosine kinases and downstream signaling proteins, as well as those that inhibit endogenous signaling proteins. We also discuss the specific insights with regard to signaling and cell behavior that these subcellular optogenetic approaches can provide. PMID:25433038

  14. An adaptable Boolean net trainable to control a computing robot

    SciTech Connect

    Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.

    1999-03-22

    We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits.

  15. Parallel computation of geometry control in adaptive truss structures

    NASA Technical Reports Server (NTRS)

    Ramesh, A. V.; Utku, S.; Wada, B. K.

    1992-01-01

    The fast computation of geometry control in adaptive truss structures involves two distinct parts: the efficient integration of the inverse kinematic differential equations that govern the geometry control and the fast computation of the Jacobian, which appears on the right-hand-side of the inverse kinematic equations. This paper present an efficient parallel implementation of the Jacobian computation on an MIMD machine. Large speedup from the parallel implementation is obtained, which reduces the Jacobian computation to an O(M-squared/n) procedure on an n-processor machine, where M is the number of members in the adaptive truss. The parallel algorithm given here is a good candidate for on-line geometry control of adaptive structures using attached processors.

  16. Adaptive bioinspired landmark identification for navigation control

    NASA Astrophysics Data System (ADS)

    Arena, Paolo; Cruse, Holk; Fortuna, Luigi; Lombardo, Davide; Patané, Luca; Rapisarda, Rosa

    2007-05-01

    In this paper a new methodology for landmark navigation will be introduced. Either for animals or for artificial agents, the whole problem of landmark navigation can be divided into two parts: first, the agent has to recognize, from the dynamic environment, space invariant objects which can be considered as suitable landmarks for driving the motion towards a goal position; second, it has to use the information on the landmarks to effectively navigate within the environment. Here, the problem of determining landmarks has been addressed by processing the external information through a spiking network with dynamic synapses plastically tuned by an STDP algorithm. The learning processes establish correlations between the incoming stimuli, allowing the system to extract from the scenario important features which can play the role of landmarks. Once established the landmarks, the agent acquires geometric relationships between them and the goal position. This process defines the parameters of a recurrent neural network (RNN). This in turn drives the agent navigation, filtering the information about landmarks given within an absolute reference system (e.g the North). When the absolute reference is not available, a safety mechanism acts to control the motion maintaining a correct heading. Simulation results showed the potentiality of the proposed architecture: this is able to drive an agent towards the desired position in presence of stimuli subject to noise and also in the case of partially obscured landmarks.

  17. Loss and re-adaptation of lumbar intervertebral disc water signal intensity after prolonged bedrest.

    PubMed

    Kordi, M; Belavý, D L; Armbrecht, G; Sheikh, A; Felsenberg, D; Trudel, G

    2015-09-01

    The adaptation and re-adaptation process of the intervertebral disc (IVD) to prolonged bedrest is important for understanding IVD physiology and IVD herniations in astronauts. Little information is available on changes in IVD composition. In this study, 24 male subjects underwent 60-day bedrest and In/Out Phase magnetic resonance imaging sequences were performed to evaluate IVD shape and water signal intensity. Scanning was performed before bedrest (baseline), twice during bedrest, and three, six and twenty-four months after bedrest. Area, signal intensity, average height, and anteroposterior diameter of the lumbar L3/4 and L4/5 IVDs were measured. At the end of bedrest, disc height and area were significantly increased with no change in water signal intensity. After bedrest, we observed reduced IVD signal intensity three months (p=0.004 versus baseline), six months (p=0.003 versus baseline), but not twenty-four months (p=0.25 versus baseline) post-bedrest. At these same time points post-bedrest, IVD height and area remained increased. The reduced lumbar IVD water signal intensity in the first months after bedrest implies a reduction of glycosaminoglycans and/or free water in the IVD. Subsequently, at two years after bedrest, IVD hydration status returned towards pre-bedrest levels, suggesting a gradual, but slow, re-adaptation process of the IVD after prolonged bedrest. PMID:26350949

  18. Frequency domain synthesis of optimal inputs for adaptive identification and control

    NASA Technical Reports Server (NTRS)

    Fu, Li-Chen; Sastry, Shankar

    1987-01-01

    The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

  19. IIR filtering based adaptive active vibration control methodology with online secondary path modeling using PZT actuators

    NASA Astrophysics Data System (ADS)

    Boz, Utku; Basdogan, Ipek

    2015-12-01

    Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.

  20. Active Pneumatic Vibration Control by Using Pressure and Velocity Measurements and Adaptive Fuzzy Sliding-Mode Controller

    PubMed Central

    Chen, Hung-Yi; Liang, Jin-Wei; Wu, Jia-Wei

    2013-01-01

    This paper presents an intelligent control strategy to overcome nonlinear and time-varying characteristics of a diaphragm-type pneumatic vibration isolator (PVI) system. By combining an adaptive rule with fuzzy and sliding-mode control, the method has online learning ability when it faces the system's nonlinear and time-varying behaviors during an active vibration control process. Since the proposed scheme has a simple structure, it is easy to implement. To validate the proposed scheme, a composite control which adopts both chamber pressure and payload velocity as feedback signal is implemented. During experimental investigations, sinusoidal excitation at resonance and random-like signal are input on a floor base to simulate ground vibration. Performances obtained from the proposed scheme are compared with those obtained from passive system and PID scheme to illustrate the effectiveness of the proposed intelligent control. PMID:23820746

  1. Adaptive technique for P and T wave delineation in electrocardiogram signals.

    PubMed

    Bayasi, Nourhan; Tekeste, Temesghen; Saleh, Hani; Khandoker, Ahsan; Mohammad, Baker; Ismail, Mohammed

    2014-01-01

    The T and P waves of electrocardiogram signals are excellent indicators in the analysis and interpretation of cardiac arrhythmia. As such, the need to address and develop an accurate delineation technique for the detection of these waves is necessary. In this paper, we present a novel robust and adaptive T and P wave delineation method for real-time analysis and nonstandard ECG morphologies. The proposed method is based on ECG signal filtering, value estimation of different fiducial points, applying backward and forward search windows as well as adaptive thresholds. Simulations and evaluations prove the accuracy of the proposed technique in comparison to those proposed techniques in the literature. The mean error for the T peak, T offset, P peak and P offset values are found to be 9.8, 2.3, 7.3 and 3.5 milliseconds, respectively, based on the Physionet QT database, rendering our algorithm as an excellent candidate for ECG signal analysis. PMID:25569904

  2. Co-evolution of Hormone Metabolism and Signaling Networks Expands Plant Adaptive Plasticity.

    PubMed

    Weng, Jing-Ke; Ye, Mingli; Li, Bin; Noel, Joseph P

    2016-08-11

    Classically, hormones elicit specific cellular responses by activating dedicated receptors. Nevertheless, the biosynthesis and turnover of many of these hormone molecules also produce chemically related metabolites. These molecules may also possess hormonal activities; therefore, one or more may contribute to the adaptive plasticity of signaling outcomes in host organisms. Here, we show that a catabolite of the plant hormone abscisic acid (ABA), namely phaseic acid (PA), likely emerged in seed plants as a signaling molecule that fine-tunes plant physiology, environmental adaptation, and development. This trait was facilitated by both the emergence-selection of a PA reductase that modulates PA concentrations and by the functional diversification of the ABA receptor family to perceive and respond to PA. Our results suggest that PA serves as a hormone in seed plants through activation of a subset of ABA receptors. This study demonstrates that the co-evolution of hormone metabolism and signaling networks can expand organismal resilience.

  3. Co-evolution of Hormone Metabolism and Signaling Networks Expands Plant Adaptive Plasticity.

    PubMed

    Weng, Jing-Ke; Ye, Mingli; Li, Bin; Noel, Joseph P

    2016-08-11

    Classically, hormones elicit specific cellular responses by activating dedicated receptors. Nevertheless, the biosynthesis and turnover of many of these hormone molecules also produce chemically related metabolites. These molecules may also possess hormonal activities; therefore, one or more may contribute to the adaptive plasticity of signaling outcomes in host organisms. Here, we show that a catabolite of the plant hormone abscisic acid (ABA), namely phaseic acid (PA), likely emerged in seed plants as a signaling molecule that fine-tunes plant physiology, environmental adaptation, and development. This trait was facilitated by both the emergence-selection of a PA reductase that modulates PA concentrations and by the functional diversification of the ABA receptor family to perceive and respond to PA. Our results suggest that PA serves as a hormone in seed plants through activation of a subset of ABA receptors. This study demonstrates that the co-evolution of hormone metabolism and signaling networks can expand organismal resilience. PMID:27518563

  4. Powerline interference reduction in ECG signals using empirical wavelet transform and adaptive filtering.

    PubMed

    Singh, Omkar; Sunkaria, Ramesh Kumar

    2015-01-01

    Separating an information-bearing signal from the background noise is a general problem in signal processing. In a clinical environment during acquisition of an electrocardiogram (ECG) signal, The ECG signal is corrupted by various noise sources such as powerline interference (PLI), baseline wander and muscle artifacts. This paper presents novel methods for reduction of powerline interference in ECG signals using empirical wavelet transform (EWT) and adaptive filtering. The proposed methods are compared with the empirical mode decomposition (EMD) based PLI cancellation methods. A total of six methods for PLI reduction based on EMD and EWT are analysed and their results are presented in this paper. The EWT-based de-noising methods have less computational complexity and are more efficient as compared with the EMD-based de-noising methods. PMID:25412942

  5. Performance of a modified feedback loop adaptive array with TVRO satellite signals

    NASA Technical Reports Server (NTRS)

    Steadman, K.; Gupta, I. J.; Walton, E. K.

    1990-01-01

    The performance of an experimental adaptive antenna array system is evaluated using television-receive-only (TVRO) satellite signals. The experimental system is a sidelobe canceler with two auxiliary channels. Modified feedback loops are used to enhance the suppression of weak interfering signals. The modified feedback loops use two spatially separate antennas, each with an individual amplifier for each auxiliary channel. Thus, the experimental system uses five antenna elements. Instead of using five separate antennas, a reflector antenna with multiple feeds is used to receive signals from various TVRO satellites. The details of the earth station are given. It is shown that the experimental system can null up to two signals originating from interfering TVRO satellites while receiving the signals from a desired TVRO satellite.

  6. Increasing autonomy of precision spacecraft using neural network adaptive control

    NASA Astrophysics Data System (ADS)

    Denoyer, Keith K.; Ninneman, R. Rory

    1999-01-01

    In recent years, there has been a significant interest in the use of adaptive methods for controlling structures in high precision aerospace applications. This is because adaptive methods offer the potential to autonomously adjust to system characteristics different from those modeled or seen in qualification testing. This is especially true of spacecraft, which are generally tested in a 1-g environment. Despite extensive research, it remains extremely difficult to predict on-orbit 0-g behavior. In addition, system dynamics often tend to be time varying. This can take the form of slow changes due to degradation of materials and aging of the spacecraft or sudden failures such as the loss of a sensor or actuator. These events become increasingly likely as spacecraft become more and more complex. By decreasing modeling and testing requirements, lowering operations and maintenance activities that require human intervention, and increasing reliability, adaptive methods have the potential to significantly reduce cost and increase performance of these systems. One class of adaptive control methods are those which utilize artificial neural networks. The use of neural networks has become increasingly mature in a number of areas such as image processing and speech recognition. However, despite a number of publications on the subject, very few instances exist where neural networks have actually been used in control and in particular, structural control applications. The United States Air Force Research Laboratory (AFRL) is currently engaged in advancing adaptive neural control technologies for application to precision space systems. This paper gives an overview of several past and current ground and space based adaptive neural control experiments.

  7. Mechanisms of motor adaptation in reactive balance control.

    PubMed

    Welch, Torrence D J; Ting, Lena H

    2014-01-01

    Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM) excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations. PMID:24810991

  8. Active Attenuation of Acoustic Noise Using Adaptive Armax Control.

    NASA Astrophysics Data System (ADS)

    Swanson, David Carl

    An adaptive auxiliary input autoregressive moving average (ARMAX) control system using the recursive least -squares lattice for system identification is developed for active control of dynamic systems. The closed-loop adaptive ARMAX control system is applied to active acoustic noise reduction in three-dimensional spaces. The structure of the ARMAX system is compared to that for duct cancellation systems, model-reference control systems, and the general field solution and is seen as a reasonable approach for active field control in the general case. The ARMAX system is derived for multiple inputs and outputs where the measured outputs are to be driven to desired waveforms with least -squares error using a multi-channel ARMAX lattice for recursive system identification. A significant reduction in complexity is obtained by neglecting the ARMAX zeros for the special case of active attenuation of non-dispersive acoustic waves. It is shown that using the least-squares lattice requires fewer multiplies, divides, additions, and subtractions than the recursive least-squares algorithm which is based on the matrix inversion lemma. Computational complexity is seen as an important issue in the application of adaptive ARMAX systems to active field control because the system must control relatively higher numbers of modes and frequencies in real time than are seen in industrial process plants for which the adaptive ARMAX systems were first developed using recursive least squares. Convergence requirements using the lattice system identification algorithm are the same as that for the recursive least squares algorithm in adaptive ARMAX system and are verified in numerical simulations using known ARMAX parameters. A real-time simulation of active attenuation of acoustic noise is presented using the blade-excited harmonics from a small axial flow fan. The adaptive ARMAX controller provides active attenuation for correlated spectral peaks but not for uncorrelated noise from turbulence

  9. Adaptive mechanism-based congestion control for networked systems

    NASA Astrophysics Data System (ADS)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  10. Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics.

    PubMed

    Yin, Shen; Shi, Peng; Yang, Hongyan

    2016-08-01

    In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme.

  11. Adaptive inverse control for rotorcraft vibration reduction. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Jacklin, S. A.

    1985-01-01

    The Least Mean Square (LMS) algorithm is extended to solve the multiple-input, multiple-output problem of alleviating N/Rev helicopter fuselage vibration by means of adaptive inverse control. A frequency domain locally linear model is used to represent the transfer matrix relating the high harmonic pitch control inputs to the harmonic vibration outputs to be controlled. By using the inverse matrix as the controller gain matrix, an adaptive inverse regulator is formed to alleviate the N/Rev vibration. The stability and rate of convergence properties of the extended LMS algorithm are discussed. It is shown that the stability ranges for the elements of the stability gain matrix are directly related to the eigenvalues of the vibration signal information matrix for the learning phase, but not for the control phase. The overall conclusion is that the LMS adaptive inverse control method can form a robust vibration control system, but will require some tuning of the input sensor gains, the stability gain matrix, and the amount of control relaxation to be used. The learning curve of the controller during the learning phase is shown to be quantitatively close to that predicted by averaging the learning curves of the normal modes. It is shown that the best selections of the stability gain matrix elements and the amount of control relaxation is basically a compromise between slow, stable convergence and fast convergence with increased possibility of unstable identification.

  12. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    NASA Technical Reports Server (NTRS)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  13. 3D positional control of magnetic levitation system using adaptive control: improvement of positioning control in horizontal plane

    NASA Astrophysics Data System (ADS)

    Nishino, Toshimasa; Fujitani, Yasuhiro; Kato, Norihiko; Tsuda, Naoaki; Nomura, Yoshihiko; Matsui, Hirokazu

    2012-01-01

    The objective of this paper is to establish a technique that levitates and conveys a hand, a kind of micro-robot, by applying magnetic forces: the hand is assumed to have a function of holding and detaching the objects. The equipment to be used in our experiments consists of four pole-pieces of electromagnets, and is expected to work as a 4DOF drive unit within some restricted range of 3D space: the three DOF are corresponding to 3D positional control and the remaining one DOF, rotational oscillation damping control. Having used the same equipment, Khamesee et al. had manipulated the impressed voltages on the four electric magnetics by a PID controller by the use of the feedback signal of the hand's 3D position, the controlled variable. However, in this system, there were some problems remaining: in the horizontal direction, when translating the hand out of restricted region, positional control performance was suddenly degraded. The authors propose a method to apply an adaptive control to the horizontal directional control. It is expected that the technique to be presented in this paper contributes not only to the improvement of the response characteristic but also to widening the applicable range in the horizontal directional control.

  14. The design of digital-adaptive controllers for VTOL aircraft

    NASA Technical Reports Server (NTRS)

    Stengel, R. F.; Broussard, J. R.; Berry, P. W.

    1976-01-01

    Design procedures for VTOL automatic control systems have been developed and are presented. Using linear-optimal estimation and control techniques as a starting point, digital-adaptive control laws have been designed for the VALT Research Aircraft, a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. These control laws are designed to interface with velocity-command and attitude-command guidance logic, which could be used in short-haul VTOL operations. Developments reported here include new algorithms for designing non-zero-set-point digital regulators, design procedures for rate-limited systems, and algorithms for dynamic control trim setting.

  15. Model-free adaptive control of advanced power plants

    SciTech Connect

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  16. Ground adaptive standing controller for a powered transfemoral prosthesis.

    PubMed

    Lawson, Brian E; Varol, Huseyin Atakan; Goldfarb, Michael

    2011-01-01

    The scope of this work is the design and verification of a new standing controller for a powered knee and ankle prosthesis. The controller is based upon a finite-state impedance control approach previously developed by the authors. The controller provides a comprehensive standing behavior that incorporates ground adaptation for unlevel terrain. An amputee subject tested the controller with a powered prosthesis for a variety of standing conditions. Results indicate that the powered prosthesis can estimate the ground slope within ±1 degree over a range of ±15 degrees, and that it can provide appropriate joint impedances for standing on slopes within this range.

  17. Adaptive-Control Experiments On A Large Flexible Structure

    NASA Technical Reports Server (NTRS)

    Ih, Che-Hang C.; Bayard, David S.; Wang, Shyh J.; Eldred, Daniel B.

    1990-01-01

    Antennalike flexible structure built for research in advanced technology including suppression of vibrations and control of initial deflections. Structure instrumented with sensors and actuators connected to digital electronic control system, programmed with control algorithms to be tested. Particular attention in this research focused on direct model-reference adaptive-control algorithm based on command generator tracker theory. Built to exhibit multiple vibrational modes, low modal frequencies, and low structural damping. Made three-dimensional so complicated interactions among components of structure and control system investigated.

  18. Applications of active adaptive noise control to jet engines

    NASA Technical Reports Server (NTRS)

    Shoureshi, Rahmat; Brackney, Larry

    1993-01-01

    During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

  19. Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses

    PubMed Central

    Baddeley, Michelle; Tobler, Philippe N.; Schultz, Wolfram

    2016-01-01

    Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment. SIGNIFICANCE STATEMENT Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result

  20. Evolutionary genomics reveals conserved structural determinants of signaling and adaptation in microbial chemoreceptors

    SciTech Connect

    Alexander, Roger P; Jouline, Igor B

    2007-01-01

    As an important model for transmembrane signaling, methyl-accepting chemotaxis proteins (MCPs) have been extensively studied by using genetic, biochemical, and structural techniques. However, details of the molecular mechanism of signaling are still not well understood. The availability of genomic information for hundreds of species enables the identification of features in protein sequences that are conserved over long evolutionary distances and thus are critically important for function. We carried out a large-scale comparative genomic analysis of the MCP signaling and adaptation domain family and identified features that appear to be critical for receptor structure and function. Based on domain length and sequence conservation, we identified seven major MCP classes and three distinct structural regions within the cytoplasmic domain: signaling, methylation, and flexible bundle subdomains. The flexible bundle subdomain, not previously recognized in MCPs, is a conserved element that appears to be important for signal transduction. Remarkably, the N- and C-terminal helical arms of the cytoplasmic domain maintain symmetry in length and register despite dramatic variation, from 24 to 64 7-aa heptads in overall domain length. Loss of symmetry is observed in some MCPs, where it is concomitant with specific changes in the sensory module. Each major MCP class has a distinct pattern of predicted methylation sites that is well supported by experimental data. Our findings indicate that signaling and adaptation functions within the MCP cytoplasmic domain are tightly coupled, and that their coevolution has contributed to the significant diversity in chemotaxis mechanisms among different organisms.

  1. Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis

    PubMed Central

    Mulkidjanian, Armen Y.; Shaitan, Konstantin V.; Engelhard, Martin; Klare, Johann P.; Steinhoff, Heinz-Jürgen

    2015-01-01

    Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors. PMID:26496122

  2. Adaptive filtering of ECG interference on surface EEnGs based on signal averaging.

    PubMed

    Garcia-Casado, Javier; Martinez-de-Juan, Jose L; Ponce, Jose L

    2006-06-01

    An external electroenterogram (EEnG) is the recording of the small bowel myoelectrical signal using contact electrodes placed on the abdominal surface. It is a weak signal affected by possible movements and by the interferences of respiration and, principally, of the cardiac signal. In this paper an adaptive filtering technique was proposed to identify and subsequently cancel ECG interference on canine surface EEnGs by means of a signal averaging process time-locked with the R-wave. Twelve recording sessions were carried out on six conscious dogs in the fasting state. The adaptive filtering technique used increases the signal-to-interference ratio of the raw surface EEnG from 16.7 +/- 6.5 dB up to 31.9 +/- 4.0 dB. In addition to removing ECG interference, this technique has been proven to respect intestinal SB activity, i.e. the EEnG component associated with bowel contractions, despite the fact that they overlap in the frequency domain. In this way, more robust non-invasive intestinal motility indicators can be obtained with correlation coefficients of 0.68 +/- 0.09 with internal intestinal activity. The method proposed here may also be applied to other biological recordings affected by cardiac interference and could be a very helpful tool for future applications of non-invasive recordings of gastrointestinal signals.

  3. Adaptive responses of androgen receptor signaling in castration-resistant prostate cancer

    PubMed Central

    2015-01-01

    Prostate Cancer (PCa) is an important age-related disease being the most common cancer malignancy and the second leading cause of cancer mortality in men in Western countries. Initially, PCa progression is androgen receptor (AR)- and androgen-dependent. Eventually advanced PCa reaches the stage of Castration-Resistant Prostate Cancer (CRPC), but remains dependent on AR, which indicates the importance of AR activity also for CRPC. Here, we discuss various pathways that influence the AR activity in CRPC, which indicates an adaptation of the AR signaling in PCa to overcome the treatment of PCa. The adaptation pathways include interferences of the normal regulation of the AR protein level, the expression of AR variants, the crosstalk of the AR with cytokine tyrosine kinases, the Src-Akt-, the MAPK-signaling pathways and AR corepressors. Furthermore, we summarize the current treatment options with regard to the underlying molecular basis of the common adaptation processes of AR signaling that may arise after the treatment with AR antagonists, androgen deprivation therapy (ADT) as well as for CRPC, and point towards novel therapeutic strategies. The understanding of individualized adaptation processes in PCa will lead to individualized treatment options in the future. PMID:26325261

  4. An adaptive segment method for smoothing lidar signal based on noise estimation

    NASA Astrophysics Data System (ADS)

    Wang, Yuzhao; Luo, Pingping

    2014-10-01

    An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

  5. Adaptation to Environmental Stimuli within the Host: Two-Component Signal Transduction Systems of Mycobacterium tuberculosis

    PubMed Central

    Bretl, Daniel J.; Demetriadou, Chrystalla; Zahrt, Thomas C.

    2011-01-01

    Summary: Pathogenic microorganisms encounter a variety of environmental stresses following infection of their respective hosts. Mycobacterium tuberculosis, the etiological agent of tuberculosis, is an unusual bacterial pathogen in that it is able to establish lifelong infections in individuals within granulomatous lesions that are formed following a productive immune response. Adaptation to this highly dynamic environment is thought to be mediated primarily through transcriptional reprogramming initiated in response to recognition of stimuli, including low-oxygen tension, nutrient depletion, reactive oxygen and nitrogen species, altered pH, toxic lipid moieties, cell wall/cell membrane-perturbing agents, and other environmental cues. To survive continued exposure to these potentially adverse factors, M. tuberculosis encodes a variety of regulatory factors, including 11 complete two-component signal transduction systems (TCSSs) and several orphaned response regulators (RRs) and sensor kinases (SKs). This report reviews our current knowledge of the TCSSs present in M. tuberculosis. In particular, we discuss the biochemical and functional characteristics of individual RRs and SKs, the environmental stimuli regulating their activation, the regulons controlled by the various TCSSs, and the known or postulated role(s) of individual TCSSs in the context of M. tuberculosis physiology and/or pathogenesis. PMID:22126994

  6. Adaptive support vector regression for UAV flight control.

    PubMed

    Shin, Jongho; Jin Kim, H; Kim, Youdan

    2011-01-01

    This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model.

  7. Cocaine-induced adaptations in metabotropic inhibitory signaling in the mesocorticolimbic system

    PubMed Central

    Hearing, Matthew C.; Zink, Anastasia N.; Wickman, Kevin

    2013-01-01

    The addictive properties of psychostimulants such as cocaine are rooted in their ability to activate the mesocorticolimbic dopamine (DA) system. This system consists primarily of dopaminergic projections arising from the ventral tegmental area (VTA) and projecting to limbic and cortical brain regions such as the nucleus accumbens (NAc) and prefrontal cortex (PFC). While the basic anatomy and functional relevance of the mesocorticolimbic DA system is relatively well-established, a key challenge remaining in addiction research is to understand where and how molecular adaptations and corresponding changes in function of this system facilitate a pathological desire to seek and take drugs. Several lines of evidence indicate that inhibitory signaling, particularly signaling mediated by the Gi/o class of heterotrimeric GTP-binding proteins (G proteins), plays a key role in the acute and persistent effects of drugs of abuse. Moreover, recent evidence argues that these signaling pathways are targets of drug-induced adaptations. Here, we discuss inhibitory signaling pathways involving DA and the inhibitory neurotransmitter GABA in two brain regions, the VTA and PFC, which are central to the effects of acute and repeated cocaine exposure and represent sites of adaptations linked to addiction-related behaviors including sensitization, craving, and relapse. PMID:22944653

  8. Adaptive Fuzzy Tracking Control of Nonlinear Systems With Asymmetric Actuator Backlash Based on a New Smooth Inverse.

    PubMed

    Lai, Guanyu; Liu, Zhi; Zhang, Yun; Philip Chen, C L

    2016-06-01

    This paper is concentrated on the problem of adaptive fuzzy tracking control for an uncertain nonlinear system whose actuator is encountered by the asymmetric backlash behavior. First, we propose a new smooth inverse model which can approximate the asymmetric actuator backlash arbitrarily. By applying it, two adaptive fuzzy control scenarios, namely, the compensation-based control scheme and nonlinear decomposition-based control scheme, are then developed successively. It is worth noticing that the first fuzzy controller exhibits a better tracking control performance, although it recourses to a known slope ratio of backlash nonlinearity. The second one further removes the restriction, and also gets a desirable control performance. By the strict Lyapunov argument, both adaptive fuzzy controllers guarantee that the output tracking error is convergent to an adjustable region of zero asymptotically, while all the signals remain semiglobally uniformly ultimately bounded. Lastly, two comparative simulations are conducted to verify the effectiveness of the proposed fuzzy controllers. PMID:27187937

  9. Application of Model Reference Adaptive Control System to Instrument Pointing System /IPS/

    NASA Technical Reports Server (NTRS)

    Waites, H. B.

    1979-01-01

    A Model Reference Adaptive Controller (MRAC) is derived for a Shuttle payload called the Instrument Pointing System (IPS). The unique features of this MRAC design are that total state feedback is not required, that the internal structure of the model is independent of the internal structure of the IPS, and that the model input is of bounded variation and not required a priori. An application of Liapunov's stability theorems is used to synthesize a control signal which assures MRAC asymptotic stability. Exponential observers are used to obtain the necessary state information to implement the control synthesis. Results are presented which show how effectively the MRAC can maneuver the IPS.

  10. An adaptive robust controller for time delay maglev transportation systems

    NASA Astrophysics Data System (ADS)

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  11. Adaptive backstepping slide mode control of pneumatic position servo system

    NASA Astrophysics Data System (ADS)

    Ren, Haipeng; Fan, Juntao

    2016-06-01

    With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.

  12. A Conditional Exposure Control Method for Multidimensional Adaptive Testing

    ERIC Educational Resources Information Center

    Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A.

    2009-01-01

    In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…

  13. Controlling Item Exposure Rates in a Realistic Adaptive Testing Paradigm.

    ERIC Educational Resources Information Center

    Stocking, Martha L.

    In the context of paper and pencil testing, the frequency of the exposure of items is usually controlled through policies that regulate both the reuse of test forms and the frequency with which a candidate may retake the test. In the context of computerized adaptive testing, where item pools are large and expensive to produce and testing can be on…

  14. Adaptive Insecure Attachment and Resource Control Strategies during Middle Childhood

    ERIC Educational Resources Information Center

    Chen, Bin-Bin; Chang, Lei

    2012-01-01

    By integrating the life history theory of attachment with resource control theory, the current study examines the hypothesis that insecure attachment styles reorganized in middle childhood are alternative adaptive strategies used to prepare for upcoming competition with the peer group. A sample of 654 children in the second through seventh grades…

  15. Rapid inversion of velocity map images for adaptive femtosecond control

    NASA Astrophysics Data System (ADS)

    Rallis, C.; Andrews, P.; Averin, R.; Jochim, B.; Gregerson, N.; Wells, E.; Zohrabi, M.; de, S.; Gaire, B.; Carnes, K. D.; Ben-Itzhak, I.; Bergues, B.; Kling, M. F.

    2011-05-01

    We report techniques developed to utilize three dimensional momentum information as feedback in adaptive femtosecond control of molecular systems. Velocity map imaging of the dissociating ions following interaction with an intense ultrafast laser pulse provides raw data. In order to recover momentum information, however, the two-dimensional image must be inverted to reconstruct the three-dimensional photofragment distribution. Using a variation of the onion-peeling technique, we invert 1054 × 1040 pixel images in under 1 second. This rapid inversion allows a slice of the momentum distribution to be used as feedback in a closed-loop adaptive control scheme. We report techniques developed to utilize three dimensional momentum information as feedback in adaptive femtosecond control of molecular systems. Velocity map imaging of the dissociating ions following interaction with an intense ultrafast laser pulse provides raw data. In order to recover momentum information, however, the two-dimensional image must be inverted to reconstruct the three-dimensional photofragment distribution. Using a variation of the onion-peeling technique, we invert 1054 × 1040 pixel images in under 1 second. This rapid inversion allows a slice of the momentum distribution to be used as feedback in a closed-loop adaptive control scheme. This work supported by National Science Foundation award PHY-0969687 and the Chemical Sciences, Geosciences, and Biosciences Division, Office of Basic Energy Science, Office of Science, US Department of Energy.

  16. Variable Neural Adaptive Robust Control: A Switched System Approach

    SciTech Connect

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  17. Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems

    NASA Technical Reports Server (NTRS)

    Esogbue, Augustine O.

    1998-01-01

    The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of

  18. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    PubMed Central

    Quagliotti, Fulvia

    2014-01-01

    The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. Moreover, if the controller parameters are tuned for a specific gust model, even if the gust frequency changes, no parameter retuning is required. PMID:24688411

  19. Adaptive second-order sliding mode control with uncertainty compensation

    NASA Astrophysics Data System (ADS)

    Bartolini, G.; Levant, A.; Pisano, A.; Usai, E.

    2016-09-01

    This paper endows the second-order sliding mode control (2-SMC) approach with additional capabilities of learning and control adaptation. We present a 2-SMC scheme that estimates and compensates for the uncertainties affecting the system dynamics. It also adjusts the discontinuous control effort online, so that it can be reduced to arbitrarily small values. The proposed scheme is particularly useful when the available information regarding the uncertainties is conservative, and the classical `fixed-gain' SMC would inevitably lead to largely oversized discontinuous control effort. Benefits from the viewpoint of chattering reduction are obtained, as confirmed by computer simulations.

  20. Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain

    SciTech Connect

    Luo, Shaohua

    2014-09-01

    This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

  1. Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain.

    PubMed

    Luo, Shaohua

    2014-09-01

    This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

  2. F-8C adaptive control law refinement and software development

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.

    1981-01-01

    An explicit adaptive control algorithm based on maximum likelihood estimation of parameters was designed. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm was implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer, surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software.

  3. Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.

    PubMed

    Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan

    2016-02-22

    We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved.

  4. Multiple Model-Informed Open-Loop Control of Uncertain Intracellular Signaling Dynamics

    PubMed Central

    Perley, Jeffrey P.; Mikolajczak, Judith; Harrison, Marietta L.; Buzzard, Gregery T.; Rundell, Ann E.

    2014-01-01

    Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex nonlinear systems typically involve the application of control theory to a descriptive mathematical model. For cellular processes, however, measurement assays tend to be too time consuming for real-time feedback control and models offer rough approximations of the biological reality, thus limiting their utility when considered in isolation. We overcome these problems by combining nonlinear model predictive control with a novel adaptive weighting algorithm that blends predictions from multiple models to derive a compromise open-loop control sequence. The proposed strategy uses weight maps to inform the controller of the tendency for models to differ in their ability to accurately reproduce the system dynamics under different experimental perturbations (i.e. control inputs). These maps, which characterize the changing model likelihoods over the admissible control input space, are constructed using preexisting experimental data and used to produce a model-based open-loop control framework. In effect, the proposed method designs a sequence of control inputs that force the signaling dynamics along a predefined temporal response without measurement feedback while mitigating the effects of model uncertainty. We demonstrate this technique on the well-known Erk/MAPK signaling pathway in T cells. In silico assessment demonstrates that this approach successfully reduces target tracking error by 52% or better when compared with single model-based controllers and non-adaptive multiple model-based controllers. In vitro implementation of the proposed approach in Jurkat cells confirms a 63% reduction in tracking error when compared with the best of the single-model controllers. This study provides an experimentally

  5. Multiple model-informed open-loop control of uncertain intracellular signaling dynamics.

    PubMed

    Perley, Jeffrey P; Mikolajczak, Judith; Harrison, Marietta L; Buzzard, Gregery T; Rundell, Ann E

    2014-04-01

    Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex nonlinear systems typically involve the application of control theory to a descriptive mathematical model. For cellular processes, however, measurement assays tend to be too time consuming for real-time feedback control and models offer rough approximations of the biological reality, thus limiting their utility when considered in isolation. We overcome these problems by combining nonlinear model predictive control with a novel adaptive weighting algorithm that blends predictions from multiple models to derive a compromise open-loop control sequence. The proposed strategy uses weight maps to inform the controller of the tendency for models to differ in their ability to accurately reproduce the system dynamics under different experimental perturbations (i.e. control inputs). These maps, which characterize the changing model likelihoods over the admissible control input space, are constructed using preexisting experimental data and used to produce a model-based open-loop control framework. In effect, the proposed method designs a sequence of control inputs that force the signaling dynamics along a predefined temporal response without measurement feedback while mitigating the effects of model uncertainty. We demonstrate this technique on the well-known Erk/MAPK signaling pathway in T cells. In silico assessment demonstrates that this approach successfully reduces target tracking error by 52% or better when compared with single model-based controllers and non-adaptive multiple model-based controllers. In vitro implementation of the proposed approach in Jurkat cells confirms a 63% reduction in tracking error when compared with the best of the single-model controllers. This study provides an experimentally

  6. Molecular identification of rapidly adapting mechanoreceptors and their developmental dependence on ret signaling.

    PubMed

    Luo, Wenqin; Enomoto, Hideki; Rice, Frank L; Milbrandt, Jeffrey; Ginty, David D

    2009-12-24

    In mammals, the first step in the perception of form and texture is the activation of trigeminal or dorsal root ganglion (DRG) mechanosensory neurons, which are classified as either rapidly (RA) or slowly adapting (SA) according to their rates of adaptation to sustained stimuli. The molecular identities and mechanisms of development of RA and SA mechanoreceptors are largely unknown. We found that the "early Ret(+)" DRG neurons are RA mechanoreceptors, which form Meissner corpuscles, Pacinian corpuscles, and longitudinal lanceolate endings. The central projections of these RA mechanoreceptors innervate layers III through V of the spinal cord and terminate within discrete subdomains of the dorsal column nuclei. Moreover, mice lacking Ret signaling components are devoid of Pacinian corpuscles and exhibit a dramatic disruption of RA mechanoreceptor projections to both the spinal cord and medulla. Thus, the early Ret(+) neurons are RA mechanoreceptors and Ret signaling is required for the assembly of neural circuits underlying touch perception.

  7. The role of prediction and outcomes in adaptive cognitive control.

    PubMed

    Schiffer, Anne-Marike; Waszak, Florian; Yeung, Nick

    2015-01-01

    Humans adaptively perform actions to achieve their goals. This flexible behaviour requires two core abilities: the ability to anticipate the outcomes of candidate actions and the ability to select and implement actions in a goal-directed manner. The ability to predict outcomes has been extensively researched in reinforcement learning paradigms, but this work has often focused on simple actions that are not embedded in hierarchical and sequential structures that are characteristic of goal-directed human behaviour. On the other hand, the ability to select actions in accordance with high-level task goals, particularly in the presence of alternative responses and salient distractors, has been widely researched in cognitive control paradigms. Cognitive control research, however, has often paid less attention to the role of action outcomes. The present review attempts to bridge these accounts by proposing an outcome-guided mechanism for selection of extended actions. Our proposal builds on constructs from the hierarchical reinforcement learning literature, which emphasises the concept of reaching and evaluating informative states, i.e., states that constitute subgoals in complex actions. We develop an account of the neural mechanisms that allow outcome-guided action selection to be achieved in a network that relies on projections from cortical areas to the basal ganglia and back-projections from the basal ganglia to the cortex. These cortico-basal ganglia-thalamo-cortical 'loops' allow convergence - and thus integration - of information from non-adjacent cortical areas (for example between sensory and motor representations). This integration is essential in action sequences, for which achieving an anticipated sensory state signals the successful completion of an action. We further describe how projection pathways within the basal ganglia allow selection between representations, which may pertain to movements, actions, or extended action plans. The model lastly envisages

  8. Robust observer-based adaptive fuzzy sliding mode controller

    NASA Astrophysics Data System (ADS)

    Oveisi, Atta; Nestorović, Tamara

    2016-08-01

    In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

  9. Adaptive nonlinear control of missiles using neural networks

    NASA Astrophysics Data System (ADS)

    McFarland, Michael Bryan

    Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear

  10. Adaptive boundary control of a flexible manipulator with input saturation

    NASA Astrophysics Data System (ADS)

    Liu, Zhijie; Liu, Jinkun; He, Wei

    2016-06-01

    In this study, we consider the anti-windup design as one of the approaches for the boundary control problem of a flexible manipulator in the presence of system parametric uncertainties, external disturbances and bounded inputs. The dynamics of the system are represented by partial differential equations (PDEs). Using the singular perturbation approach, the PDE model is divided into two simpler subsystems. With the Lyapunov's direct method, an adaptive boundary control scheme is developed to regulate the angular position and suppress the elastic vibration simultaneously and the adaptive laws are designed to compensate for the system parametric uncertainties and the disturbances. The proposed control scheme allows the application of smooth hyperbolic functions, which satisfy physical conditions and input restrictions, be easily realised. Numerical simulations demonstrate the effectiveness of the proposed scheme.

  11. Fixed gain and adaptive techniques for rotorcraft vibration control

    NASA Technical Reports Server (NTRS)

    Roy, R. H.; Saberi, H. A.; Walker, R. A.

    1985-01-01

    The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

  12. Network Adaptive Deadband: NCS Data Flow Control for Shared Networks

    PubMed Central

    Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín

    2012-01-01

    This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556

  13. Adaptive Control of a Transport Aircraft Using Differential Thrust

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan

    2009-01-01

    The paper presents an adaptive control technique for a damaged large transport aircraft subject to unknown atmospheric disturbances such as wind gust or turbulence. It is assumed that the damage results in vertical tail loss with no rudder authority, which is replaced with a differential thrust input. The proposed technique uses the adaptive prediction based control design in conjunction with the time scale separation principle, based on the singular perturbation theory. The application of later is necessitated by the fact that the engine response to a throttle command is substantially slow that the angular rate dynamics of the aircraft. It is shown that this control technique guarantees the stability of the closed-loop system and the tracking of a given reference model. The simulation example shows the benefits of the approach.

  14. A Robot Manipulator with Adaptive Fuzzy Controller in Obstacle Avoidance

    NASA Astrophysics Data System (ADS)

    Sreekumar, Muthuswamy

    2016-07-01

    Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.

  15. Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation.

    PubMed

    Li, Yongming; Tong, Shaocheng; Li, Tieshan

    2015-10-01

    In this paper, a composite adaptive fuzzy output-feedback control approach is proposed for a class of single-input and single-output strict-feedback nonlinear systems with unmeasured states and input saturation. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states. By utilizing the designed fuzzy state observer, a serial-parallel estimation model is established. Based on adaptive backstepping dynamic surface control technique and utilizing the prediction error between the system states observer model and the serial-parallel estimation model, a new fuzzy controller with the composite parameters adaptive laws are developed. It is proved that all the signals of the closed-loop system are bounded and the system output can follow the given bounded reference signal. A numerical example and simulation comparisons with previous control methods are provided to show the effectiveness of the proposed approach.

  16. Adaptive data rate control TDMA systems as a rain attenuation compensation technique

    NASA Technical Reports Server (NTRS)

    Sato, Masaki; Wakana, Hiromitsu; Takahashi, Takashi; Takeuchi, Makoto; Yamamoto, Minoru

    1993-01-01

    Rainfall attenuation has a severe effect on signal strength and impairs communication links for future mobile and personal satellite communications using Ka-band and millimeter wave frequencies. As rain attenuation compensation techniques, several methods such as uplink power control, site diversity, and adaptive control of data rate or forward error correction have been proposed. In this paper, we propose a TDMA system that can compensate rain attenuation by adaptive control of transmission rates. To evaluate the performance of this TDMA terminal, we carried out three types of experiments: experiments using a Japanese CS-3 satellite with Ka-band transponders, in house IF loop-back experiments, and computer simulations. Experimental results show that this TDMA system has advantages over the conventional constant-rate TDMA systems, as resource sharing technique, in both bit error rate and total TDMA burst lengths required for transmitting given information.

  17. Beaconless adaptive-optics technique for HEL beam control

    NASA Astrophysics Data System (ADS)

    Khizhnyak, Anatoliy; Markov, Vladimir

    2016-05-01

    Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.

  18. PID-Type Fuzzy Control for Anti-Lock Brake Systems with Parameter Adaptation

    NASA Astrophysics Data System (ADS)

    Chen, Chih-Keng; Shih, Ming-Chang

    In this research, a platform is built to accomplish a series of experiments to control the Antilock Brake System (ABS). A commercial ABS module controlled by a controller is installed and tested on the platform. The vehicle and tire models are deduced and simulated by a personal computer for real time control. An adaptive PID-type fuzzy control scheme is used. Two on-off conversion methods: pulse width modulation (PWM) and conditional on-off, are used to control the solenoid valves in the ABS module. With the pressure signal feedbacks in the caliper, vehicle dynamics and wheel speeds are computed during braking. Road surface conditions, vehicle weight and control schemes are varied in the experiments to study braking properties.

  19. Adaptive control of Space Station during nominal operations with CMGs. [Control Moment Gyroscopes

    NASA Technical Reports Server (NTRS)

    Bishop, R. H.; Paynter, S. J.; Sunkel, J. W.

    1991-01-01

    An adaptive control approach is investigated for the Space Station. The main components of the adaptive controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is the Space Station baseline control law. The control gain calculation is based on linear quadratic regulator theory with eigenvalue placement in a vertical strip. The parameter identification scheme is a real-time recursive extended Kalman filter which estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to compute accurate estimates of the Space Station inertias during nominal CMG (control moment gyro) operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.

  20. Sequence amplification via cell passaging creates spurious signals of positive adaptation in influenza virus H3N2 hemagglutinin

    PubMed Central

    McWhite, Claire D.; Meyer, Austin G.; Wilke, Claus O.

    2016-01-01

    Clinical influenza A virus isolates are frequently not sequenced directly. Instead, a majority of these isolates (~70% in 2015) are first subjected to passaging for amplification, most commonly in non-human cell culture. Here, we find that this passaging leaves distinct signals of adaptation, which can confound evolutionary analyses of the viral sequences. We find distinct patterns of adaptation to Madin-Darby (MDCK) and monkey cell culture absent from unpassaged hemagglutinin sequences. These patterns also dominate pooled datasets not separated by passaging type, and they increase in proportion to the number of passages performed. By contrast, MDCK-SIAT1 passaged sequences seem mostly (but not entirely) free of passaging adaptations. Contrary to previous studies, we find that using only internal branches of influenza virus phylogenetic trees is insufficient to correct for passaging artifacts. These artifacts can only be safely avoided by excluding passaged sequences entirely from subsequent analysis. We conclude that future influenza virus evolutionary analyses should appropriately control for potentially confounding effects of passaging adaptations. PMID:27713835

  1. Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

    1979-01-01

    The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

  2. Adaptive Strategies for Controls of Flexible Arms. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Yuan, Bau-San

    1989-01-01

    An adaptive controller for a modern manipulator has been designed based on asymptotical stability via the Lyapunov criterion with the output error between the system and a reference model used as the actuating control signal. Computer simulations were carried out to test the design. The combination of the adaptive controller and a system vibration and mode shape estimator show that the flexible arm should move along a pre-defined trajectory with high-speed motion and fast vibration setting time. An existing computer-controlled prototype two link manipulator, RALF (Robotic Arm, Large Flexible), with a parallel mechanism driven by hydraulic actuators was used to verify the mathematical analysis. The experimental results illustrate that assumed modes found from finite element techniques can be used to derive the equations of motion with acceptable accuracy. The robust adaptive (modal) control is implemented to compensate for unmodelled modes and nonlinearities and is compared with the joint feedback control in additional experiments. Preliminary results show promise for the experimental control algorithm.

  3. Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control

    NASA Astrophysics Data System (ADS)

    Eshak, Peter B.

    Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to

  4. Robust adaptive backstepping control for reentry reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Wu, Zhong; Du, Yijiang

    2016-09-01

    During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.

  5. Adaptive suboptimal second-order sliding mode control for microgrids

    NASA Astrophysics Data System (ADS)

    Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella

    2016-09-01

    This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

  6. An adaptive fuzzy controller for permanent-magnet AC servo drives

    SciTech Connect

    Le-Huy, H.

    1995-12-31

    This paper presents a theoretical study on a model-reference adaptive fuzzy logic controller for vector-controlled permanent-magnet ac servo drives. In the proposed system, fuzzy logic is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The results are compared with that provided by a non-adaptive fuzzy controller. The implementation of proposed adaptive fuzzy controller is discussed.

  7. Towards feasible and effective predictive wavefront control for adaptive optics

    SciTech Connect

    Poyneer, L A; Veran, J

    2008-06-04

    We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.

  8. Robust adaptive integrated translation and rotation control of a rigid spacecraft with control saturation and actuator misalignment

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Duan, Guangren

    2013-05-01

    This paper handles the integrated translation and rotation tracking control problem of a rigid spacecraft with unknown mass property, actuator misalignment and control saturation. In view of the system natural coupling, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment is taken into account. By using anti-windup technique and backstepping philosophy, a robust adaptive integrated control scheme is proposed such that the spacecraft is able to track the command position and attitude signals in the presence of external disturbance, unknown mass property, thruster misalignment and control saturation. Within the Lyapunov framework, the uniformly ultimate boundedness of the system states is guaranteed. In particular, given the nominal case, the asymptotic convergence of the system states can be further ensured by the proposed control scheme. Finally, numerical simulation demonstrates the effect of the designed control strategy.

  9. PLI cancellation in ECG signal based on adaptive filter by using Wiener-Hopf equation for providing initial condition.

    PubMed

    Manosueb, Anchalee; Koseeyaporn, Jeerasuda; Wardkein, Paramote

    2014-01-01

    This paper presents a technique for finding the optimal initial weight for adaptive filter by using difference equation. The obtained analytical response of the system identifies the appropriate weights for the system and shows that the MSE depends on the initial weight. The proposed technique is applied to eliminate the known frequency power line interference (PLI) signal in the electrocardiogram (ECG) signal. The PLI signal is considered as a combination of cosine and sine signals. The adaptive filter, therefore, attempts to adjust the amplitude of cosine and sine signals to synthesize a reference signal very similar to the contaminated PLI signal. To compare the potential of the proposed technique to other techniques, the system is simulated by using the Matlab program and the TMS320C6713 digital board. The simulation results demonstrate that the proposed technique enables the system to eliminate the PLI signal with the fastest time and gains the superior results of the recovered ECG signal.

  10. Visuomotor Control of Human Adaptive Locomotion: Understanding the Anticipatory Nature

    PubMed Central

    Higuchi, Takahiro

    2013-01-01

    To maintain balance during locomotion, the central nervous system (CNS) accommodates changes in the constraints of spatial environment (e.g., existence of an obstacle or changes in the surface properties). Locomotion while modifying the basic movement patterns in response to such constraints is referred to as adaptive locomotion. The most powerful means of ensuring balance during adaptive locomotion is to visually perceive the environmental properties at a distance and modify the movement patterns in an anticipatory manner to avoid perturbation altogether. For this reason, visuomotor control of adaptive locomotion is characterized, at least in part, by its anticipatory nature. The purpose of the present article is to review the relevant studies which revealed the anticipatory nature of the visuomotor control of adaptive locomotion. The anticipatory locomotor adjustments for stationary and changeable environment, as well as the spatio-temporal patterns of gaze behavior to support the anticipatory locomotor adjustments are described. Such description will clearly show that anticipatory locomotor adjustments are initiated when an object of interest (e.g., a goal or obstacle) still exists in far space. This review also show that, as a prerequisite of anticipatory locomotor adjustments, environmental properties are accurately perceived from a distance in relation to individual’s action capabilities. PMID:23720647

  11. Effect of prism adaptation on thermoregulatory control in humans.

    PubMed

    Calzolari, Elena; Gallace, Alberto; Moseley, G Lorimer; Vallar, Giuseppe

    2016-01-01

    The physiological regulation of skin temperature can be modulated not only by autonomic brain regions, but also by a network of higher-level cortical areas involved in the maintenance of a coherent representation of the body. In this study we assessed in healthy participants if the sensorimotor changes taking place during motor adaptation to the lateral displacement of the visual scene induced by wearing prismatic lenses (prism adaptation, PA), and the aftereffects, after prisms' removal, on the ability to process spatial coordinates, were associated with skin temperature regulation changes. We found a difference in thermoregulatory control as a function of the direction of the prism-induced displacement of the visual scene, and the subsequent sensorimotor adaptation. After PA to rightward displacing lenses, with leftward aftereffects (the same directional procedure efficaciously used for ameliorating left spatial neglect in right-brain-damaged patients) the hands' temperature decreased. Conversely, after adaptation to neutral lenses, and PA to leftward displacing lenses, with rightward aftereffects, the temperature of both hands increased. These results suggest a lateral asymmetry in the effects of PA on skin temperature regulation, and a relationship between body spatial representations and homeostatic control in humans.

  12. Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

    NASA Astrophysics Data System (ADS)

    Engel, E.; Kovalev, I. V.; Karandeev, D.

    2015-10-01

    The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

  13. Minimal control synthesis adaptive control of nonlinear systems: utilizing the properties of chaos.

    PubMed

    di Bernardo, M; Stoten, D P

    2006-09-15

    This paper discusses a novel approach to the control of chaos based on the use of the adaptive minimal control synthesis algorithm. The strategies presented are based on the explicit exploitation of different properties of chaotic systems including the boundedness of the chaotic attractors and their topological transitivity (or ergodicity). It is shown that chaos can be exploited to synthesize more efficient control techniques for nonlinear systems. For instance, by using the ergodicity of the chaotic trajectory, we show that a local adaptive control strategy can be used to synthesize a global controller. An application is to the swing-up control of a double inverted pendulum. PMID:16893794

  14. Geometry adaptive control of a composite reflector using PZT actuator

    NASA Astrophysics Data System (ADS)

    Lan, Lan; Jiang, Shuidong; Zhou, Yang; Fang, Houfei; Tan, Shujun; Wu, Zhigang

    2015-04-01

    Maintaining geometrical high precision for a graphite fiber reinforced composite (GFRC) reflector is a challenging task. Although great efforts have been placed to improve the fabrication precision, geometry adaptive control for a reflector is becoming more and more necessary. This paper studied geometry adaptive control for a GFRC reflector with piezoelectric ceramic transducer (PZT) actuators assembled on the ribs. In order to model the piezoelectric effect in finite element analysis (FEA), a thermal analogy was used in which the temperature was applied to simulate the actuation voltage, and the piezoelectric constant was mimicked by a Coefficient of Thermal Expansion (CTE). PZT actuator's equivalent model was validated by an experiment. The deformations of a triangular GFRC specimen with three PZT actuators were also measured experimentally and compared with that of simulation. This study developed a multidisciplinary analytical model, which includes the composite structure, thermal, thermal deformation and control system, to perform an optimization analysis and design for the adaptive GFRC reflector by considering the free vibration, gravity deformation and geometry controllability.

  15. An adaptive learning control system for large flexible structures

    NASA Technical Reports Server (NTRS)

    Thau, F. E.

    1985-01-01

    The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

  16. Application of network control systems for adaptive optics

    NASA Astrophysics Data System (ADS)

    Eager, Robert J.

    2008-04-01

    The communication architecture for most pointing, tracking, and high order adaptive optics control systems has been based on a centralized point-to-point and bus based approach. With the increased use of larger arrays and multiple sensors, actuators and processing nodes, these evolving systems require decentralized control, modularity, flexibility redundancy, integrated diagnostics, dynamic resource allocation, and ease of maintenance to support a wide range of experiments. Network control systems provide all of these critical functionalities. This paper begins with a quick overview of adaptive optics as a control system and communication architecture. It then provides an introduction to network control systems, identifying the key design areas that impact system performance. The paper then discusses the performance test results of a fielded network control system used to implement an adaptive optics system comprised of: a 10KHz, 32x32 spatial selfreferencing interferometer wave front sensor, a 705 channel "Tweeter" deformable mirror, a 177 channel "Woofer" deformable mirror, ten processing nodes, and six data acquisition nodes. The reconstructor algorithm utilized a modulo-2pi wave front phase measurement and a least-squares phase un-wrapper with branch point correction. The servo control algorithm is a hybrid of exponential and infinite impulse response controllers, with tweeter-to-woofer saturation offloading. This system achieved a first-pixel-out to last-mirror-voltage latency of 86 microseconds, with the network accounting for 4 microseconds of the measured latency. Finally, the extensibility of this architecture will be illustrated, by detailing the integration of a tracking sub-system into the existing network.

  17. Detection of Convergent Genome-Wide Signals of Adaptation to Tropical Forests in Humans

    PubMed Central

    Amorim, Carlos Eduardo G.; Daub, Josephine T.; Salzano, Francisco M.; Foll, Matthieu; Excoffier, Laurent

    2015-01-01

    Tropical forests are believed to be very harsh environments for human life. It is unclear whether human beings would have ever subsisted in those environments without external resources. It is therefore possible that humans have developed recent biological adaptations in response to specific selective pressures to cope with this challenge. To understand such biological adaptations we analyzed genome-wide SNP data under a Bayesian statistics framework, looking for outlier markers with an overly large extent of differentiation between populations living in a tropical forest, as compared to genetically related populations living outside the forest in Africa and the Americas. The most significant positive selection signals were found in genes related to lipid metabolism, the immune system, body development, and RNA Polymerase III transcription initiation. The results are discussed in the light of putative tropical forest selective pressures, namely food scarcity, high prevalence of pathogens, difficulty to move, and inefficient thermoregulation. Agreement between our results and previous studies on the pygmy phenotype, a putative prototype of forest adaptation, were found, suggesting that a few genetic regions previously described as associated with short stature may be evolving under similar positive selection in Africa and the Americas. In general, convergent evolution was less pervasive than local adaptation in one single continent, suggesting that Africans and Amerindians may have followed different routes to adapt to similar environmental selective pressures. PMID:25849546

  18. Adaptive Helmholtz resonators and passive vibration absorbers for cylinder interior noise control

    NASA Astrophysics Data System (ADS)

    Estève, Simon J.; Johnson, Marty E.

    2005-12-01

    This paper presents an adaptive-passive solution to control the broadband sound transmission into rocket payload fairings. The treatment is composed of passive distributed vibration absorbers (DVAs) and adaptive Helmholtz resonators (HR). Both the frequency domain and time-domain model of a simply supported cylinder excited by an external plane wave are developed. To tune vibration absorbers to tonal excitation, a tuning strategy, based on the phase information between the velocity of the absorber mass and the velocity of the host structure is used here in a new fashion to tune resonators to peaks in the broadband acoustic spectrum of a cavity. This tuning law, called the dot-product method, only uses two microphone signals local to each HR, which allows the adaptive Helmholtz resonator (AHR) to be manufactured as an autonomous device with power supply, sensor, actuator and controller integrated. Numerical simulations corresponding to a 2.8 m long 2.5 m diameter composite cylinder prototype demonstrate that, as long as the structure modes, which strongly couple to the acoustic cavity, are damped with a DVA treatment, the dot-product method tune multiple HRs to a near-optimal solution over a broad frequency range (40-160 Hz). An adaptive HR prototype with variable opening is built and characterized. Experiments conducted on the cylinder prototype with eight AHRs demonstrate the ability of resonators adapted with the dot-product method to converge to near-optimal noise attenuation in a frequency band including multiple resonances.

  19. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  20. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.