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.
Model reference adaptive control with an augmented error signal
NASA Technical Reports Server (NTRS)
Monopoli, R. V.
1974-01-01
It is shown how globally stable model reference adaptive control systems may be designed when one has access to only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Lyapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Derivatives of the plant output are not required, but are replaced by filtered derivative signals. An augmented error signal replaces the error normally used, which is defined as the difference between the model and plant outputs. However, global stability is assured in the sense that the normally used error signal approaches zero asymptotically.
Discrete model reference adaptive control with an augmented error signal
NASA Technical Reports Server (NTRS)
Ionescu, T.; Monopoli, R.
1975-01-01
A method for designing discrete model reference adaptive control systems when one has access to only the plant's input and output signals is given. Controllers for single-input, single-output, nonlinear, nonautonomous plants are developed via Liapunov's second method. Anticipative values of the plant output are not required, but are replaced by signals easily obtained from a low-pass filter operating on the plant's output. The augmented error signal method is employed, ensuring finally that the normally used error signal also approaches zero asymptotically.
Error correction, sensory prediction, and adaptation in motor control.
Shadmehr, Reza; Smith, Maurice A; Krakauer, John W
2010-01-01
Motor control is the study of how organisms make accurate goal-directed movements. Here we consider two problems that the motor system must solve in order to achieve such control. The first problem is that sensory feedback is noisy and delayed, which can make movements inaccurate and unstable. The second problem is that the relationship between a motor command and the movement it produces is variable, as the body and the environment can both change. A solution is to build adaptive internal models of the body and the world. The predictions of these internal models, called forward models because they transform motor commands into sensory consequences, can be used to both produce a lifetime of calibrated movements, and to improve the ability of the sensory system to estimate the state of the body and the world around it. Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors.
Position control of redundant manipulators using an adaptive error-based control scheme
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Zhou, Zhen-Lei
1990-01-01
A Cartesian-space control scheme is developed to control the motion of kinematically redundant manipulators with 7 degrees of freedom (DOF). The control scheme consists mainly of proportional derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories. The adaptation law is derived using the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that the manipulator performs non-compliant and slowly-varying motions. The developed control scheme is computationally efficient because its implementation does not require the computation of the manipulator dynamics. Computer simulation performed to evaluate the control scheme performance is presented and discussed.
NASA Astrophysics Data System (ADS)
Ulrich, Steve
This work addresses the direct adaptive trajectory tracking control problem associated with lightweight space robotic manipulators that exhibit elastic vibrations in their joints, and which are subject to parametric uncertainties and modeling errors. Unlike existing adaptive control methodologies, the proposed flexible-joint control techniques do not require identification of unknown parameters, or mathematical models of the system to be controlled. The direct adaptive controllers developed in this work are based on the model reference adaptive control approach, and manage modeling errors and parametric uncertainties by time-varying the controller gains using new adaptation mechanisms, thereby reducing the errors between an ideal model and the actual robot system. More specifically, new decentralized adaptation mechanisms derived from the simple adaptive control technique and fuzzy logic control theory are considered in this work. Numerical simulations compare the performance of the adaptive controllers with a nonadaptive and a conventional model-based controller, in the context of 12.6 m xx 12.6 m square trajectory tracking. To validate the robustness of the controllers to modeling errors, a new dynamics formulation that includes several nonlinear effects usually neglected in flexible-joint dynamics models is proposed. Results obtained with the adaptive methodologies demonstrate an increased robustness to both uncertainties in joint stiffness coefficients and dynamics modeling errors, as well as highly improved tracking performance compared with the nonadaptive and model-based strategies. Finally, this work considers the partial state feedback problem related to flexible-joint space robotic manipulators equipped only with sensors that provide noisy measurements of motor positions and velocities. An extended Kalman filter-based estimation strategy is developed to estimate all state variables in real-time. The state estimation filter is combined with an adaptive
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
NASA Astrophysics Data System (ADS)
Yucelen, Tansel; De La Torre, Gerardo; Johnson, Eric N.
2014-11-01
Although adaptive control theory offers mathematical tools to achieve system performance without excessive reliance on dynamical system models, its applications to safety-critical systems can be limited due to poor transient performance and robustness. In this paper, we develop an adaptive control architecture to achieve stabilisation and command following of uncertain dynamical systems with improved transient performance. Our framework consists of a new reference system and an adaptive controller. The proposed reference system captures a desired closed-loop dynamical system behaviour modified by a mismatch term representing the high-frequency content between the uncertain dynamical system and this reference system, i.e., the system error. In particular, this mismatch term allows the frequency content of the system error dynamics to be limited, which is used to drive the adaptive controller. It is shown that this key feature of our framework yields fast adaptation without incurring high-frequency oscillations in the transient performance. We further show the effects of design parameters on the system performance, analyse closeness of the uncertain dynamical system to the unmodified (ideal) reference system, discuss robustness of the proposed approach with respect to time-varying uncertainties and disturbances, and make connections to gradient minimisation and classical control theory. A numerical example is provided to demonstrate the efficacy of the proposed architecture.
Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.
Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan
2017-02-01
In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.
Adaptive control of nonlinear system using online error minimum neural networks.
Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei
2016-11-01
In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly.
1984-06-01
space discretization error . 1. I 3 1. INTRODUCTION Reaction- diffusion processes occur in many branches of biology and physical chemistry. Examples...to model reaction- diffusion phenomena. The primary goal of this adaptive method is to keep a particular norm of the space discretization error less...AD-A142 253 AN ADAPTIVE MET6 OFD LNES WITH ERROR CONTROL FOR 1 INST FOR PHYSICAL SCIENCE AND TECH. I BABUSKAAAO C7 EA OH S UMR AN UNVC EEP R
Design implementation and control of MRAS error dynamics. [Model-Reference Adaptive System
NASA Technical Reports Server (NTRS)
Colburn, B. K.; Boland, J. S., III
1974-01-01
Use is made of linearized error characteristic equation for model-reference adaptive systems to determine a parameter adjustment rule for obtaining time-invariant error dynamics. Theoretical justification of error stability is given and an illustrative example included to demonstrate the utility of the proposed technique.
Bio-inspired adaptive feedback error learning architecture for motor control.
Tolu, Silvia; Vanegas, Mauricio; Luque, Niceto R; Garrido, Jesús A; Ros, Eduardo
2012-10-01
This study proposes an adaptive control architecture based on an accurate regression method called Locally Weighted Projection Regression (LWPR) and on a bio-inspired module, such as a cerebellar-like engine. This hybrid architecture takes full advantage of the machine learning module (LWPR kernel) to abstract an optimized representation of the sensorimotor space while the cerebellar component integrates this to generate corrective terms in the framework of a control task. Furthermore, we illustrate how the use of a simple adaptive error feedback term allows to use the proposed architecture even in the absence of an accurate analytic reference model. The presented approach achieves an accurate control with low gain corrective terms (for compliant control schemes). We evaluate the contribution of the different components of the proposed scheme comparing the obtained performance with alternative approaches. Then, we show that the presented architecture can be used for accurate manipulation of different objects when their physical properties are not directly known by the controller. We evaluate how the scheme scales for simulated plants of high Degrees of Freedom (7-DOFs).
Padrão, Gonçalo; Penhune, Virginia; de Diego-Balaguer, Ruth; Marco-Pallares, Josep; Rodriguez-Fornells, Antoni
2014-10-15
The ability to detect and use information from errors is essential during the acquisition of new skills. There is now a wealth of evidence about the brain mechanisms involved in error processing. However, the extent to which those mechanisms are engaged during the acquisition of new motor skills remains elusive. Here we examined rhythm synchronization learning across 12 blocks of practice in musically naïve individuals and tracked changes in ERP signals associated with error-monitoring and error-awareness across distinct learning stages. Synchronization performance improved with practice, and performance improvements were accompanied by dynamic changes in ERP components related to error-monitoring and error-awareness. Early in learning, when performance was poor and the internal representations of the rhythms were weaker we observed a larger error-related negativity (ERN) following errors compared to later learning. The larger ERN during early learning likely results from greater conflict between competing motor responses, leading to greater engagement of medial-frontal conflict monitoring processes and attentional control. Later in learning, when performance had improved, we observed a smaller ERN accompanied by an enhancement of a centroparietal positive component resembling the P3. This centroparietal positive component was predictive of participant's performance accuracy, suggesting a relation between error saliency, error awareness and the consolidation of internal templates of the practiced rhythms. Moreover, we showed that during rhythm learning errors led to larger auditory evoked responses related to attention orientation which were triggered automatically and which were independent of the learning stage. The present study provides crucial new information about how the electrophysiological signatures related to error-monitoring and error-awareness change during the acquisition of new skills, extending previous work on error processing and cognitive
Error-based adaptive non-linear control and regions of feasibility
NASA Technical Reports Server (NTRS)
Teel, Andrew R.
1992-01-01
The nonlinear adaptive algorithm of Kanellakopoulos et al. (1991) was modified to produce an error-based algorithm. This permits global stabilizability for a large subset of pure-feedback nonlinear systems. The algorithm was demonstrated on the single-input stabilization problem, but extends easily to the multiple input tracking problems.
Zaafouri, Abderrahmen; Ben Regaya, Chiheb; Ben Azza, Hechmi; Châari, Abdelkader
2016-01-01
This paper presents a modified structure of the backstepping nonlinear control of the induction motor (IM) fitted with an adaptive backstepping speed observer. The control design is based on the backstepping technique complemented by the introduction of integral tracking errors action to improve its robustness. Unlike other research performed on backstepping control with integral action, the control law developed in this paper does not propose the increase of the number of system state so as not increase the complexity of differential equations resolution. The digital simulation and experimental results show the effectiveness of the proposed control compared to the conventional PI control. The results analysis shows the characteristic robustness of the adaptive control to disturbances of the load, the speed variation and low speed.
Aircraft system modeling error and control error
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh V. (Inventor); Kaneshige, John T. (Inventor); Krishnakumar, Kalmanje S. (Inventor); Burken, John J. (Inventor)
2012-01-01
A method for modeling error-driven adaptive control of an aircraft. Normal aircraft plant dynamics is modeled, using an original plant description in which a controller responds to a tracking error e(k) to drive the component to a normal reference value according to an asymptote curve. Where the system senses that (1) at least one aircraft plant component is experiencing an excursion and (2) the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, neural network (NN) modeling of aircraft plant operation may be changed. However, if (1) is satisfied but the error component is returning toward its reference value according to expected controller characteristics, the NN will continue to model operation of the aircraft plant according to an original description.
Kording, Konrad P.; Hargrove, Levi J.; Sensinger, Jonathon W.
2017-01-01
The objective of this study was to understand how people adapt to errors when using a myoelectric control interface. We compared adaptation across 1) non-amputee subjects using joint angle, joint torque, and myoelectric control interfaces, and 2) amputee subjects using myoelectric control interfaces with residual and intact limbs (five total control interface conditions). We measured trial-by-trial adaptation to self-generated errors and random perturbations during a virtual, single degree-of-freedom task with two levels of feedback uncertainty, and evaluated adaptation by fitting a hierarchical Kalman filter model. We have two main results. First, adaptation to random perturbations was similar across all control interfaces, whereas adaptation to self-generated errors differed. These patterns matched predictions of our model, which was fit to each control interface by changing the process noise parameter that represented system variability. Second, in amputee subjects, we found similar adaptation rates and error levels between residual and intact limbs. These results link prosthesis control to broader areas of motor learning and adaptation and provide a useful model of adaptation with myoelectric control. The model of adaptation will help us understand and solve prosthesis control challenges, such as providing additional sensory feedback. PMID:28301512
Larson, Michael J; Clayson, Peter E; Keith, Cierra M; Hunt, Isaac J; Hedges, Dawson W; Nielsen, Brent L; Call, Vaughn R A
2016-03-01
Older adults display alterations in neural reflections of conflict-related processing. We examined response times (RTs), error rates, and event-related potential (ERP; N2 and P3 components) indices of conflict adaptation (i.e., congruency sequence effects) a cognitive control process wherein previous-trial congruency influences current-trial performance, along with post-error slowing, correct-related negativity (CRN), error-related negativity (ERN) and error positivity (Pe) amplitudes in 65 healthy older adults and 94 healthy younger adults. Older adults showed generalized slowing, had decreased post-error slowing, and committed more errors than younger adults. Both older and younger adults showed conflict adaptation effects; magnitude of conflict adaptation did not differ by age. N2 amplitudes were similar between groups; younger, but not older, adults showed conflict adaptation effects for P3 component amplitudes. CRN and Pe, but not ERN, amplitudes differed between groups. Data support generalized declines in cognitive control processes in older adults without specific deficits in conflict adaptation.
Adaptive control for accelerators
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.
Control by model error estimation
NASA Technical Reports Server (NTRS)
Likins, P. W.; Skelton, R. E.
1976-01-01
Modern control theory relies upon the fidelity of the mathematical model of the system. Truncated modes, external disturbances, and parameter errors in linear system models are corrected by augmenting to the original system of equations an 'error system' which is designed to approximate the effects of such model errors. A Chebyshev error system is developed for application to the Large Space Telescope (LST).
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.
Larson, Michael J.; LeCheminant, James D.; Carbine, Kaylie; Hill, Kyle R.; Christenson, Edward; Masterson, Travis; LeCheminant, Rick
2015-01-01
An increasing trend in the workplace is for employees to walk on treadmills while working to attain known health benefits; however, the effect of walking on a treadmill during cognitive control and executive function tasks is not well known. We compared the cognitive control processes of conflict adaptation (i.e., congruency sequence effects—improved performance following high-conflict relative to low-conflict trials), post-error slowing (i.e., Rabbitt effect), and response inhibition during treadmill walking (1.5 mph) relative to sitting. Understanding the influence of treadmill desks on these cognitive processes may have implications for worker health and productivity. Sixty-nine individuals were randomized to either a sitting (n = 35) or treadmill-walking condition (n = 34). Groups did not differ in age or body mass index. All participants completed a computerized Eriksen flanker task and a response-inhibition go/no-go task in random order while either walking on a treadmill or seated. Response times (RTs) and accuracy were analyzed separately for each task using mixed model analysis of variance. Separate ANOVAs for RTs and accuracy showed the expected conflict adaptation effects, post-error slowing, and response inhibition effects when collapsed across sitting and treadmill groups (all Fs > 78.77, Ps < 0.001). There were no main effects or interactions as a function of group for any analyses (Fs < 0.79, Ps > 0.38), suggesting no decrements or enhancements in conflict-related control and adjustment processes or response inhibition for those walking on a treadmill versus sitting. We conclude that cognitive control performance remains relatively unaffected during slow treadmill walking relative to sitting. PMID:26074861
Larson, Michael J; LeCheminant, James D; Carbine, Kaylie; Hill, Kyle R; Christenson, Edward; Masterson, Travis; LeCheminant, Rick
2015-01-01
An increasing trend in the workplace is for employees to walk on treadmills while working to attain known health benefits; however, the effect of walking on a treadmill during cognitive control and executive function tasks is not well known. We compared the cognitive control processes of conflict adaptation (i.e., congruency sequence effects-improved performance following high-conflict relative to low-conflict trials), post-error slowing (i.e., Rabbitt effect), and response inhibition during treadmill walking (1.5 mph) relative to sitting. Understanding the influence of treadmill desks on these cognitive processes may have implications for worker health and productivity. Sixty-nine individuals were randomized to either a sitting (n = 35) or treadmill-walking condition (n = 34). Groups did not differ in age or body mass index. All participants completed a computerized Eriksen flanker task and a response-inhibition go/no-go task in random order while either walking on a treadmill or seated. Response times (RTs) and accuracy were analyzed separately for each task using mixed model analysis of variance. Separate ANOVAs for RTs and accuracy showed the expected conflict adaptation effects, post-error slowing, and response inhibition effects when collapsed across sitting and treadmill groups (all Fs > 78.77, Ps < 0.001). There were no main effects or interactions as a function of group for any analyses (Fs < 0.79, Ps > 0.38), suggesting no decrements or enhancements in conflict-related control and adjustment processes or response inhibition for those walking on a treadmill versus sitting. We conclude that cognitive control performance remains relatively unaffected during slow treadmill walking relative to sitting.
Sinusoidal error perturbation reveals multiple coordinate systems for sensorymotor adaptation
Hudson, Todd E.; Landy, Michael S.
2016-01-01
A coordinate system is composed of an encoding, defining the dimensions of the space, and an origin. We examine the coordinate encoding used to update motor plans during sensory-motor adaptation to center-out reaches. Adaptation is induced using a novel paradigm in which feedback of reach endpoints is perturbed following a sinewave pattern over trials; the perturbed dimensions of the feedback were the axes of a Cartesian coordinate system in one session and a polar coordinate system in another session. For center-out reaches to randomly chosen target locations, reach errors observed at one target will require different corrections at other targets within Cartesian- and polar-coded systems. The sinewave adaptation technique allowed us to simultaneously adapt both dimensions of each coordinate system (x-y, or reach gain and angle), and identify the contributions of each perturbed dimension by adapting each at a distinct temporal frequency. The efficiency of this technique further allowed us to employ perturbations that were a fraction the size normally used, which avoids confounding automatic adaptive processes with deliberate adjustments made in response to obvious experimental manipulations. Subjects independently corrected errors in each coordinate in both sessions, suggesting that the nervous system encodes both a Cartesian- and polar-coordinate-based internal representation for motor adaptation. The gains and phase lags of the adaptive responses are not readily explained by current theories of sensory-motor adaptation. Motor adaptation is fundamental to the neural control of movement, affording an automatic process to maintain a consistent relationship between motor plans and movement outcomes. That is, adaptation is described as updating an internal mapping between desired motor outcome and motor output (Sanger, 2004; Shadmehr, Smith, & Krakauer, 2010), not a deliberate corrective action. Here, using a method that relies on extremely small perturbations that
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
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.
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
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.
Automatic-repeat-request error control schemes
NASA Technical Reports Server (NTRS)
Lin, S.; Costello, D. J., Jr.; Miller, M. J.
1983-01-01
Error detection incorporated with automatic-repeat-request (ARQ) is widely used for error control in data communication systems. This method of error control is simple and provides high system reliability. If a properly chosen code is used for error detection, virtually error-free data transmission can be attained. Various types of ARQ and hybrid ARQ schemes, and error detection using linear block codes are surveyed.
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.
NASA Astrophysics Data System (ADS)
Winner, Hermann; Danner, Bernd; Steinle, Joachim
Mit Adaptive Cruise Control, abgekürzt ACC, wird eine Fahrgeschwindigkeitsregelung bezeichnet, die sich an die Verkehrssituation anpasst. Synonyme Bezeichnungen sind Aktive Geschwindigkeitsregelung, Automatische Distanzregelung oder Abstandsregeltempomat. Im englischen Sprachraum fnden sich die weiteren Bezeichnungen Active Cruise Control, Automatic Cruise Control oder Autonomous Intelligent Cruise Control. Als markengeschützte Bezeichnungen sind Distronic und Automatische Distanz-Regelung (ADR) eingetragen.
A neural fuzzy controller learning by fuzzy error propagation
NASA Technical Reports Server (NTRS)
Nauck, Detlef; Kruse, Rudolf
1992-01-01
In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.
NASA Technical Reports Server (NTRS)
Narendra, K. S.; Annaswamy, A. M.
1985-01-01
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
A cascaded coding scheme for error control
NASA Technical Reports Server (NTRS)
Shu, L.; Kasami, T.
1985-01-01
A cascade coding scheme for error control is investigated. The scheme employs a combination of hard and soft decisions in decoding. Error performance is analyzed. If the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit-error-rate. Some example schemes are evaluated. They seem to be quite suitable for satellite down-link error control.
Error Argumentation Enhance Adaptability in Adults With Low Motor Ability.
Lee, Chi-Mei; Bo, Jin
2016-01-01
The authors focused on young adults with varying degrees of motor difficulties and examined their adaptability in a visuomotor adaptation task where the visual feedback of participants' movement error was presented with either 1:1 ratio (i.e., regular feedback schedule) or 1:2 ratio (i.e., enhanced feedback schedule). Within-subject design was used with two feedback schedules counter-balanced and separated for 10 days. Results revealed that participants with greater motor difficulties showed less adaptability than those with normal motor abilities in the regular feedback schedule; however, all participants demonstrated similar level of adaptability in the enhanced feedback schedule. The results suggest that error argumentation enhances adaptability in adults with low motor ability.
A concatenated coding scheme for error control
NASA Technical Reports Server (NTRS)
Kasami, T.; Fujiwara, T.; Lin, S.
1986-01-01
In this paper, a concatenated coding scheme for error control in data communications is presented and analyzed. In this scheme, the inner code is used for both error correction and detection; however, the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error (or decoding error) of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughput efficiency of the proposed error control scheme incorporated with a selective-repeat ARQ retransmission strategy is also analyzed. Three specific examples are presented. One of the examples is proposed for error control in the NASA Telecommand System.
Adaptive Decentralized Control
1985-04-01
computational requirements and response time provide strong incentives for the use of distributed control architectures. The basic focus of our research is on...ADCON (for Adaptive Decentralized CONtrol) comes from the following observations about the current status of control theory . An important aspect of...decentralized control of completely known systems still has many unresolved issues and some basic problems are yet to be answered. Under these conditions
A concatenated coding scheme for error control
NASA Technical Reports Server (NTRS)
Lin, S.
1985-01-01
A concatenated coding scheme for error contol in data communications was analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughout efficiency of the proposed error control scheme incorporated with a selective repeat ARQ retransmission strategy is analyzed.
Adaptive hierarchical fuzzy controller
Raju, G.V.S.; Jun Zhou
1993-07-01
A methodology for designing adaptive hierarchical fuzzy controllers is presented. In order to evaluate this concept, several suitable performance indices were developed and converted to linguistic fuzzy variables. Based on those variables, a supervisory fuzzy rule set was constructed and used to change the parameters of a hierarchical fuzzy controller to accommodate the variations of system parameters. The proposed algorithm was used in feedwater flow control to a steam generator. Simulation studies are presented that illustrate the effectiveness of the approach
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.
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.
Advances in Adaptive Control Methods
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2009-01-01
This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.
Adaptive sequential controller
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.
Weinzierl, Christiane; Kerkhoff, Georg; van Eimeren, Lucia; Keller, Ingo; Stenneken, Prisca
2012-10-01
Unilateral spatial neglect frequently involves a lateralised reading disorder, neglect dyslexia (ND). Reading of single words in ND is characterised by left-sided omissions and substitutions of letters. However, it is unclear whether the distribution of error types and positions within a word shows a unique pattern of ND when directly compared to healthy controls. This question has been difficult to answer so far, given the usually low number of reading errors in healthy controls. Therefore, the present study compared single word reading of 18 patients with left-sided neglect, due to right-hemisphere stroke, and 11 age-matched healthy controls, and adjusted individual task difficulty (by varying stimulus presentation times in participants) in order to reach approximately equal error rates between neglect patients and controls. Results showed that, while both omission and substitution errors were frequently produced in neglect patients and controls, only omissions appeared neglect-specific when task difficulty was adapted between groups. Analyses of individual letter positions within words revealed that the spatial distribution of reading errors in the neglect dyslexic patients followed an almost linear increase from the end to the beginning of the word (right-to-left-gradient). Both, the gradient in error positions and the predominance of omission errors presented a neglect-specific pattern. Consistent with current models of visual word processing, these findings suggest that ND reflects sublexical, visuospatial attentional mechanisms in letter string encoding.
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.
A Nonlinear Adaptive Filter for Gyro Thermal Bias Error Cancellation
NASA Technical Reports Server (NTRS)
Galante, Joseph M.; Sanner, Robert M.
2012-01-01
Deterministic errors in angular rate gyros, such as thermal biases, can have a significant impact on spacecraft attitude knowledge. In particular, thermal biases are often the dominant error source in MEMS gyros after calibration. Filters, such as J\\,fEKFs, are commonly used to mitigate the impact of gyro errors and gyro noise on spacecraft closed loop pointing accuracy, but often have difficulty in rapidly changing thermal environments and can be computationally expensive. In this report an existing nonlinear adaptive filter is used as the basis for a new nonlinear adaptive filter designed to estimate and cancel thermal bias effects. A description of the filter is presented along with an implementation suitable for discrete-time applications. A simulation analysis demonstrates the performance of the filter in the presence of noisy measurements and provides a comparison with existing techniques.
Effects of errors on decoupled control systems
NASA Technical Reports Server (NTRS)
Hamer, H. A.; Johnson, K. G.
1978-01-01
Various error sources in a decoupled control system are considered in connection with longitudinal control on a simulated externally blown jet-flap STOL aircraft. The system employed the throttle, horizontal tail, and flaps to decouple the forward velocity, pitch angle, and flight-path angle. The errors considered were: (1) imperfect knowledge of airplane aerodynamic and control characteristics; (2) imperfect measurements of airplane state variables; (3) change in flight conditions, and (4) lag in the airplane controls and in engine response. The effects of the various errors on the decoupling process were generally minor. Significant coupling in flight-path angle was caused by control lag during speed-command maneuvers. However, this coupling could be eliminated by including the control lag in the design of the decoupled system. Other error sources affected primarily the commanded response quantity.
Linearization of Attitude-Control Error Dynamics
NASA Technical Reports Server (NTRS)
Bach, Ralph; Paielli, Russell
1993-01-01
Direction cosines and quaternions are useful for representing rigid-body attitude because they exhibit no kinematic singularities. Each utilizes more variables than the minimum three degrees of freedom required to specify attitude. Therefore, application of a nonlinear inversion procedure to either formulation introduces singularities. Furthermore, in designing an attitude-control system, it is not appropriate to express attitude error as a difference of direction cosines (or quaternions). One should employ a measure of attitude error that not only is minimal but preserves orthogonal rotation properties as well. This note applies an inversion procedure to an appropriate measure of attitude error, so that the singularity occurs when the error reaches +/- 180 deg. This approach leads to the realization of a new model-follower attitude-control system that exhibits exact linear attitude-error dynamics.
Error estimation and adaptivity for transport problems with uncertain parameters
NASA Astrophysics Data System (ADS)
Sahni, Onkar; Li, Jason; Oberai, Assad
2016-11-01
Stochastic partial differential equations (PDEs) with uncertain parameters and source terms arise in many transport problems. In this study, we develop and apply an adaptive approach based on the variational multiscale (VMS) formulation for discretizing stochastic PDEs. In this approach we employ finite elements in the physical domain and generalize polynomial chaos based spectral basis in the stochastic domain. We demonstrate our approach on non-trivial transport problems where the uncertain parameters are such that the advective and diffusive regimes are spanned in the stochastic domain. We show that the proposed method is effective as a local error estimator in quantifying the element-wise error and in driving adaptivity in the physical and stochastic domains. We will also indicate how this approach may be extended to the Navier-Stokes equations. NSF Award 1350454 (CAREER).
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.
Error sensitivity to refinement: a criterion for optimal grid adaptation
NASA Astrophysics Data System (ADS)
Luchini, Paolo; Giannnetti, Flavio; Citro, Vincenzo
2016-11-01
Most indicators used for automatic grid refinement are suboptimal, in the sense that they do not really minimize the global solution error. This paper concerns with a new indicator, related to the sensitivity map of global stability problems, suitable for an optimal grid refinement that minimizes the global solution error. The new criterion is derived from the properties of the adjoint operator and provides a map of the sensitivity of the global error (or its estimate) to a local mesh refinement. Examples are presented for both a scalar partial differential equation and for the system of Navier-Stokes equations. In the last case, we also present a grid-adaptation algorithm based on the new estimator and on the FreeFem++ software that improves the accuracy of the solution of almost two order of magnitude by redistributing the nodes of the initial computational mesh.
Robustness of channel-adapted quantum error correction
Ballo, Gabor; Gurin, Peter
2009-07-15
A quantum channel models the interaction between the system we are interested in and its environment. Such a model can capture the main features of the interaction, but, because of the complexity of the environment, we cannot assume that it is fully accurate. We study the robustness of quantum error correction operations against completely unexpected and subsequently undetermined type of channel uncertainties. We find that a channel-adapted optimal error correction operation does not only give the best possible channel fidelity but it is more robust against channel alterations than any other error correction operation. Our results are valid for Pauli channels and stabilizer codes, but based on some numerical results, we believe that very similar conclusions can be drawn also in the general case.
A posteriori error estimation for hp -adaptivity for fourth-order equations
NASA Astrophysics Data System (ADS)
Moore, Peter K.; Rangelova, Marina
2010-04-01
A posteriori error estimates developed to drive hp-adaptivity for second-order reaction-diffusion equations are extended to fourth-order equations. A C^1 hierarchical finite element basis is constructed from Hermite-Lobatto polynomials. A priori estimates of the error in several norms for both the interpolant and finite element solution are derived. In the latter case this requires a generalization of the well-known Aubin-Nitsche technique to time-dependent fourth-order equations. We show that the finite element solution and corresponding Hermite-Lobatto interpolant are asymptotically equivalent. A posteriori error estimators based on this equivalence for solutions at two orders are presented. Both are shown to be asymptotically exact on grids of uniform order. These estimators can be used to control various adaptive strategies. Computational results for linear steady-state and time-dependent equations corroborate the theory and demonstrate the effectiveness of the estimators in adaptive settings.
Adaptive Error Estimation in Linearized Ocean General Circulation Models
NASA Technical Reports Server (NTRS)
Chechelnitsky, Michael Y.
1999-01-01
Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large
An adaptive strategy for controlling chaotic system.
Cao, Yi-Jia; Hang, Hong-Xian
2003-01-01
This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems: Duffing oscillator and Rössler chaos.
Error Correction, Control Systems and Fuzzy Logic
NASA Technical Reports Server (NTRS)
Smith, Earl B.
2004-01-01
This paper will be a discussion on dealing with errors. While error correction and communication is important when dealing with spacecraft vehicles, the issue of control system design is also important. There will be certain commands that one wants a motion device to execute. An adequate control system will be necessary to make sure that the instruments and devices will receive the necessary commands. As it will be discussed later, the actual value will not always be equal to the intended or desired value. Hence, an adequate controller will be necessary so that the gap between the two values will be closed.
Measurement process error determination and control
Everhart, J.
1992-01-01
Traditional production processes have required repeated inspection activities to assure product quality. A typical production process follows this pattern: production makes product; production inspects product; Quality Control (QC) inspects product to ensure production inspected properly QC then inspects the product on a different gage to ensure the production gage performance; and QC often inspects on a different day to determine environmental effect. All of these costly inspection activities are due to the lack of confidence in the initial production measurement. The Process Measurement Assurance Program (PMAP) is a method of determining and controlling measurement error in design, development, and production. It is a preventive rather than an appraisal method that determines, improves, and controls the error in the measurement process, including measurement equipment, environment, procedure, and personnel. PMAP expands the concept of the Measurement Assurance Program developed in the 1960's by the National Bureau of Standards (NBS), today known as the National Institute of Standards and Technology (NIST). PMAP acts as a bridge in the gap between the Metrology Laboratory and the production environment by introducing standards (or certified parts) into the production process. These certified control standards are then measured as part of the production process. A control system is present to examine the measurement results of the control standards before, during, and after the manufacturing and measuring of the product. The results of the PMAP control charts determine random uncertainty and systematic (bias from the standard) error of the measurement process. The combinations of these uncertainties determine the margin of error of the measurement process. The total measurement process error is determined by combining the margin of error and the uncertainty in the control standard.
Measurement process error determination and control
Everhart, J.
1992-11-01
Traditional production processes have required repeated inspection activities to assure product quality. A typical production process follows this pattern: production makes product; production inspects product; Quality Control (QC) inspects product to ensure production inspected properly QC then inspects the product on a different gage to ensure the production gage performance; and QC often inspects on a different day to determine environmental effect. All of these costly inspection activities are due to the lack of confidence in the initial production measurement. The Process Measurement Assurance Program (PMAP) is a method of determining and controlling measurement error in design, development, and production. It is a preventive rather than an appraisal method that determines, improves, and controls the error in the measurement process, including measurement equipment, environment, procedure, and personnel. PMAP expands the concept of the Measurement Assurance Program developed in the 1960`s by the National Bureau of Standards (NBS), today known as the National Institute of Standards and Technology (NIST). PMAP acts as a bridge in the gap between the Metrology Laboratory and the production environment by introducing standards (or certified parts) into the production process. These certified control standards are then measured as part of the production process. A control system is present to examine the measurement results of the control standards before, during, and after the manufacturing and measuring of the product. The results of the PMAP control charts determine random uncertainty and systematic (bias from the standard) error of the measurement process. The combinations of these uncertainties determine the margin of error of the measurement process. The total measurement process error is determined by combining the margin of error and the uncertainty in the control standard.
Advanced Adaptive Optics Control Techniques
1979-01-01
Optimal estimation and control methods for high energy laser adaptive optics systems are described. Three system types are examined: Active...the adaptive optics approaches and potential system implementations are recommended.
Adaptive Control Of Large Vibrating, Rotating Structures
NASA Technical Reports Server (NTRS)
Bayard, David S.
1991-01-01
Globally convergent theoretical method provides for adaptive set-point control of orientation of, along with suppression of the vibrations of, large structure. Method utilizes inherent passivity properties of structure to attain mathematical condition essential to adaptive convergence on commanded set point. Maintains stability and convergence in presence of errors in mathematical model of dynamics of structure and actuators. Developed for controlling attitudes of large, somewhat flexible spacecraft, also useful in such terrestrial applications as controlling movable bridges or suppressing earthquake vibrations in bridges, buildings, and other large structures.
Acetylcholine mediates behavioral and neural post-error control.
Danielmeier, Claudia; Allen, Elena A; Jocham, Gerhard; Onur, Oezguer A; Eichele, Tom; Ullsperger, Markus
2015-06-01
Humans often commit errors when they are distracted by irrelevant information and no longer focus on what is relevant to the task at hand. Adjustments following errors are essential for optimizing goal achievement. The posterior medial frontal cortex (pMFC), a key area for monitoring errors, has been shown to trigger such post-error adjustments by modulating activity in visual cortical areas. However, the mechanisms by which pMFC controls sensory cortices are unknown. We provide evidence for a mechanism based on pMFC-induced recruitment of cholinergic projections to task-relevant sensory areas. Using fMRI in healthy volunteers, we found that error-related pMFC activity predicted subsequent adjustments in task-relevant visual brain areas. In particular, following an error, activity increased in those visual cortical areas involved in processing task-relevant stimulus features, whereas activity decreased in areas representing irrelevant, distracting features. Following treatment with the muscarinic acetylcholine receptor antagonist biperiden, activity in visual areas was no longer under control of error-related pMFC activity. This was paralleled by abolished post-error behavioral adjustments under biperiden. Our results reveal a prominent role of acetylcholine in cognitive control that has not been recognized thus far. Regaining optimal performance after errors critically depends on top-down control of perception driven by the pMFC and mediated by acetylcholine. This may explain the lack of adaptivity in conditions with reduced availability of cortical acetylcholine, such as Alzheimer's disease.
Error control in the GCF: An information-theoretic model for error analysis and coding
NASA Technical Reports Server (NTRS)
Adeyemi, O.
1974-01-01
The structure of data-transmission errors within the Ground Communications Facility is analyzed in order to provide error control (both forward error correction and feedback retransmission) for improved communication. Emphasis is placed on constructing a theoretical model of errors and obtaining from it all the relevant statistics for error control. No specific coding strategy is analyzed, but references to the significance of certain error pattern distributions, as predicted by the model, to error correction are made.
Multijoint error compensation mediates unstable object control.
Cluff, Tyler; Manos, Aspasia; Lee, Timothy D; Balasubramaniam, Ramesh
2012-08-01
A key feature of skilled object control is the ability to correct performance errors. This process is not straightforward for unstable objects (e.g., inverted pendulum or "stick" balancing) because the mechanics of the object are sensitive to small control errors, which can lead to rapid performance changes. In this study, we have characterized joint recruitment and coordination processes in an unstable object control task. Our objective was to determine whether skill acquisition involves changes in the recruitment of individual joints or distributed error compensation. To address this problem, we monitored stick-balancing performance across four experimental sessions. We confirmed that subjects learned the task by showing an increase in the stability and length of balancing trials across training sessions. We demonstrated that motor learning led to the development of a multijoint error compensation strategy such that after training, subjects preferentially constrained joint angle variance that jeopardized task performance. The selective constraint of destabilizing joint angle variance was an important metric of motor learning. Finally, we performed a combined uncontrolled manifold-permutation analysis to ensure the variance structure was not confounded by differences in the variance of individual joint angles. We showed that reliance on multijoint error compensation increased, whereas individual joint variation (primarily at the wrist joint) decreased systematically with training. We propose a learning mechanism that is based on the accurate estimation of sensory states.
Hanajima, Ritsuko; Shadmehr, Reza; Ohminami, Shinya; Tsutsumi, Ryosuke; Shirota, Yuichiro; Shimizu, Takahiro; Tanaka, Nobuyuki; Terao, Yasuo; Tsuji, Shoji; Ugawa, Yoshikazu; Uchimura, Motoaki; Inoue, Masato; Kitazawa, Shigeru
2015-10-01
Cerebellar damage can profoundly impair human motor adaptation. For example, if reaching movements are perturbed abruptly, cerebellar damage impairs the ability to learn from the perturbation-induced errors. Interestingly, if the perturbation is imposed gradually over many trials, people with cerebellar damage may exhibit improved adaptation. However, this result is controversial, since the differential effects of gradual vs. abrupt protocols have not been observed in all studies. To examine this question, we recruited patients with pure cerebellar ataxia due to cerebellar cortical atrophy (n = 13) and asked them to reach to a target while viewing the scene through wedge prisms. The prisms were computer controlled, making it possible to impose the full perturbation abruptly in one trial, or build up the perturbation gradually over many trials. To control visual feedback, we employed shutter glasses that removed visual feedback during the reach, allowing us to measure trial-by-trial learning from error (termed error-sensitivity), and trial-by-trial decay of motor memory (termed forgetting). We found that the patients benefited significantly from the gradual protocol, improving their performance with respect to the abrupt protocol by exhibiting smaller errors during the exposure block, and producing larger aftereffects during the postexposure block. Trial-by-trial analysis suggested that this improvement was due to increased error-sensitivity in the gradual protocol. Therefore, cerebellar patients exhibited an improved ability to learn from error if they experienced those errors gradually. This improvement coincided with increased error-sensitivity and was present in both groups of subjects, suggesting that control of error-sensitivity may be spared despite cerebellar damage.
Shadmehr, Reza; Ohminami, Shinya; Tsutsumi, Ryosuke; Shirota, Yuichiro; Shimizu, Takahiro; Tanaka, Nobuyuki; Terao, Yasuo; Tsuji, Shoji; Ugawa, Yoshikazu; Uchimura, Motoaki; Inoue, Masato; Kitazawa, Shigeru
2015-01-01
Cerebellar damage can profoundly impair human motor adaptation. For example, if reaching movements are perturbed abruptly, cerebellar damage impairs the ability to learn from the perturbation-induced errors. Interestingly, if the perturbation is imposed gradually over many trials, people with cerebellar damage may exhibit improved adaptation. However, this result is controversial, since the differential effects of gradual vs. abrupt protocols have not been observed in all studies. To examine this question, we recruited patients with pure cerebellar ataxia due to cerebellar cortical atrophy (n = 13) and asked them to reach to a target while viewing the scene through wedge prisms. The prisms were computer controlled, making it possible to impose the full perturbation abruptly in one trial, or build up the perturbation gradually over many trials. To control visual feedback, we employed shutter glasses that removed visual feedback during the reach, allowing us to measure trial-by-trial learning from error (termed error-sensitivity), and trial-by-trial decay of motor memory (termed forgetting). We found that the patients benefited significantly from the gradual protocol, improving their performance with respect to the abrupt protocol by exhibiting smaller errors during the exposure block, and producing larger aftereffects during the postexposure block. Trial-by-trial analysis suggested that this improvement was due to increased error-sensitivity in the gradual protocol. Therefore, cerebellar patients exhibited an improved ability to learn from error if they experienced those errors gradually. This improvement coincided with increased error-sensitivity and was present in both groups of subjects, suggesting that control of error-sensitivity may be spared despite cerebellar damage. PMID:26311179
Adaptive hybrid control of manipulators
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.
Adaptive neural control of spacecraft using control moment gyros
NASA Astrophysics Data System (ADS)
Leeghim, Henzeh; Kim, Donghoon
2015-03-01
An adaptive control technique is applied to reorient spacecraft with uncertainty using control moment gyros. A nonlinear quaternion feedback law is chosen as a baseline controller. An additional adaptive control input supported by neural networks can estimate and eliminate unknown terms adaptively. The normalized input neural networks are considered for reliable computation of the adaptive input. To prove the stability of the closed-loop dynamics with the control law, the Lyapunov stability theory is considered. Accordingly, the proposed approach results in the uniform ultimate boundedness in tracking error. For reorientation maneuvers, control moment gyros are utilized with a well-known singularity problem described in this work investigated by predicting one-step ahead singularity index. A momentum vector recovery approach using magnetic torquers is also introduced to evaluate the avoidance strategies indirectly. Finally, the suggested methods are demonstrated by numerical simulation studies.
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.
The importance of robust error control in data compression applications
NASA Technical Reports Server (NTRS)
Woolley, S. I.
1993-01-01
Data compression has become an increasingly popular option as advances in information technology have placed further demands on data storage capabilities. With compression ratios as high as 100:1 the benefits are clear; however, the inherent intolerance of many compression formats to error events should be given careful consideration. If we consider that efficiently compressed data will ideally contain no redundancy, then the introduction of a channel error must result in a change of understanding from that of the original source. While the prefix property of codes such as Huffman enables resynchronisation, this is not sufficient to arrest propagating errors in an adaptive environment. Arithmetic, Lempel-Ziv, discrete cosine transform (DCT) and fractal methods are similarly prone to error propagating behaviors. It is, therefore, essential that compression implementations provide sufficient combatant error control in order to maintain data integrity. Ideally, this control should be derived from a full understanding of the prevailing error mechanisms and their interaction with both the system configuration and the compression schemes in use.
Direct adaptive impedance control of manipulators
NASA Technical Reports Server (NTRS)
Colbaugh, R.; Seraji, H.; Glass, K.
1991-01-01
An adaptive scheme for controlling the end-effector impedance of robot manipulators is presented. The proposed control system consists of three subsystems: a simple filter which characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller which produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics, and it is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a very general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter.
Error Estimation and h-Adaptivity for Optimal Finite Element Analysis
NASA Technical Reports Server (NTRS)
Cwik, Tom; Lou, John
1997-01-01
The objective of adaptive meshing and automatic error control in finite element analysis is to eliminate the need for the application engineer from re-meshing and re-running design simulations to verify numerical accuracy. The user should only need to enter the component geometry and a coarse finite element mesh. The software will then autonomously and adaptively refine this mesh where needed, reducing the error in the fields to a user prescribed value. The ideal end result of the simulation is a measurable quantity (e.g. scattered field, input impedance), calculated to a prescribed error, in less time and less machine memory than if the user applied typical uniform mesh refinement by hand. It would also allow for the simulation of larger objects since an optimal mesh is created.
Transcoding-Based Error-Resilient Video Adaptation for 3G Wireless Networks
NASA Astrophysics Data System (ADS)
Eminsoy, Sertac; Dogan, Safak; Kondoz, Ahmet M.
2007-12-01
Transcoding is an effective method to provide video adaptation for heterogeneous internetwork video access and communication environments, which require the tailoring (i.e., repurposing) of coded video properties to channel conditions, terminal capabilities, and user preferences. This paper presents a video transcoding system that is capable of applying a suite of error resilience tools on the input compressed video streams while controlling the output rates to provide robust communications over error-prone and bandwidth-limited 3G wireless networks. The transcoder is also designed to employ a new adaptive intra-refresh algorithm, which is responsive to the detected scene activity inherently embedded into the video content and the reported time-varying channel error conditions of the wireless network. Comprehensive computer simulations demonstrate significant improvements in the received video quality performances using the new transcoding architecture without an extra computational cost.
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.
Adaptive control design for hysteretic smart systems
NASA Astrophysics Data System (ADS)
Fan, Xiang; Smith, Ralph C.
2009-03-01
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. One technique for control design is to approximately linearize the actuator dynamics using an adaptive inverse compensator that is also able to accommodate model uncertainties and error introduced by the inverse algorithm. This paper describes the design of an adaptive inverse control technique based on the homogenized energy model for hysteresis. The resulting inverse filter is incorporated in an L1 control theory to provide a robust control algorithm capable of providing high speed, high accuracy tracking in the presence of actuator hysteresis and nonlinearities. Properties of the control design are illustrated through numerical examples.
Adaptive control of linearizable systems
NASA Technical Reports Server (NTRS)
Sastry, S. Shankar; Isidori, Alberto
1989-01-01
Initial results are reported regarding the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback. Parameter adaptation is used as a technique to make robust the exact cancellation of nonlinear terms, which is called for in the linearization technique. The application of the adaptive technique to control of robot manipulators is discussed. Only the continuous-time case is considered; extensions to the discrete-time and sampled-data cases are not obvious.
Error norms for the adaptive solution of the Navier-Stokes equations
NASA Technical Reports Server (NTRS)
Forester, C. K.
1982-01-01
The adaptive solution of the Navier-Stokes equations depends upon the successful interaction of three key elements: (1) the ability to flexibly select grid length scales in composite grids, (2) the ability to efficiently control residual error in composite grids, and (3) the ability to define reliable, convenient error norms to guide the grid adjustment and optimize the residual levels relative to the local truncation errors. An initial investigation was conducted to explore how to approach developing these key elements. Conventional error assessment methods were defined and defect and deferred correction methods were surveyed. The one dimensional potential equation was used as a multigrid test bed to investigate how to achieve successful interaction of these three key elements.
Hellander, Andreas; Lawson, Michael J; Drawert, Brian; Petzold, Linda
2014-06-01
The efficiency of exact simulation methods for the reaction-diffusion master equation (RDME) is severely limited by the large number of diffusion events if the mesh is fine or if diffusion constants are large. Furthermore, inherent properties of exact kinetic-Monte Carlo simulation methods limit the efficiency of parallel implementations. Several approximate and hybrid methods have appeared that enable more efficient simulation of the RDME. A common feature to most of them is that they rely on splitting the system into its reaction and diffusion parts and updating them sequentially over a discrete timestep. This use of operator splitting enables more efficient simulation but it comes at the price of a temporal discretization error that depends on the size of the timestep. So far, existing methods have not attempted to estimate or control this error in a systematic manner. This makes the solvers hard to use for practitioners since they must guess an appropriate timestep. It also makes the solvers potentially less efficient than if the timesteps are adapted to control the error. Here, we derive estimates of the local error and propose a strategy to adaptively select the timestep when the RDME is simulated via a first order operator splitting. While the strategy is general and applicable to a wide range of approximate and hybrid methods, we exemplify it here by extending a previously published approximate method, the Diffusive Finite-State Projection (DFSP) method, to incorporate temporal adaptivity.
Adaptive Wavefront Calibration and Control for the Gemini Planet Imager
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.
Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz
2014-07-01
Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate.
Error-control techniques for digital communication
NASA Astrophysics Data System (ADS)
Michelson, A. M.; Levesque, A. H.
The reliable transmission of digital information is discussed, taking into account the communication system design problem, the elements of a digital communication system, important channel models, information theory and channel capacity, modulation performance on the AWGN channel, and combined modulation and coding for efficient signal design. Other topics studied are related to fundamental and simple block codes, the algebra of linear block codes, binary cyclic codes and BCH codes, decoding techniques for binary BCH codes, nonbinary BCH codes and Reed-Solomon codes, the performance of linear block codes with bounded-distance decoding an introduction to convolutional codes, maximum likelihood decoding of convolutional codes, sequential decoding, and applications of error-control coding. Attention is given to groups, fields, vector spaces, binary linear block codes, the parity-check matrix revisited, dual codes, Hamming distance and the weight distribution, code geometry and error-correction capability, and the representations of finite fields.
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.
Context specificity of post-error and post-conflict cognitive control adjustments.
Forster, Sarah E; Cho, Raymond Y
2014-01-01
There has been accumulating evidence that cognitive control can be adaptively regulated by monitoring for processing conflict as an index of online control demands. However, it is not yet known whether top-down control mechanisms respond to processing conflict in a manner specific to the operative task context or confer a more generalized benefit. While previous studies have examined the taskset-specificity of conflict adaptation effects, yielding inconsistent results, control-related performance adjustments following errors have been largely overlooked. This gap in the literature underscores recent debate as to whether post-error performance represents a strategic, control-mediated mechanism or a nonstrategic consequence of attentional orienting. In the present study, evidence of generalized control following both high conflict correct trials and errors was explored in a task-switching paradigm. Conflict adaptation effects were not found to generalize across tasksets, despite a shared response set. In contrast, post-error slowing effects were found to extend to the inactive taskset and were predictive of enhanced post-error accuracy. In addition, post-error performance adjustments were found to persist for several trials and across multiple task switches, a finding inconsistent with attentional orienting accounts of post-error slowing. These findings indicate that error-related control adjustments confer a generalized performance benefit and suggest dissociable mechanisms of post-conflict and post-error control.
NASA Astrophysics Data System (ADS)
Widayaka, Elfady Satya; Ohmori, Hiromitsu
2016-09-01
This paper shows how to design Multivariable Model Reference Adaptive Control System (MRACS) for “Tokyo University discrete-time engine model” proposed by Yasuda et al (2014). This controller configuration has the structure of “Feedback error learning (FEL)” and adaptive law is based on kernel method. Simulation results indicate that “kernelized” adaptive controllers can improve the tracking performance, the speed of convergence and the robustness to disturbances.
Kinematic markers dissociate error correction from sensorimotor realignment during prism adaptation.
O'Shea, Jacinta; Gaveau, Valérie; Kandel, Matthieu; Koga, Kazuo; Susami, Kenji; Prablanc, Claude; Rossetti, Yves
2014-03-01
This study investigated the motor control mechanisms that enable healthy individuals to adapt their pointing movements during prism exposure to a rightward optical shift. In the prism adaptation literature, two processes are typically distinguished. Strategic motor adjustments are thought to drive the pattern of rapid endpoint error correction typically observed during the early stage of prism exposure. This is distinguished from so-called 'true sensorimotor realignment', normally measured with a different pointing task, at the end of prism exposure, which reveals a compensatory leftward 'prism after-effect'. Here, we tested whether each mode of motor compensation - strategic adjustments versus 'true sensorimotor realignment' - could be distinguished, by analyzing patterns of kinematic change during prism exposure. We hypothesized that fast feedforward versus slower feedback error corrective processes would map onto two distinct phases of the reach trajectory. Specifically, we predicted that feedforward adjustments would drive rapid compensation of the initial (acceleration) phase of the reach, resulting in the rapid reduction of endpoint errors typically observed early during prism exposure. By contrast, we expected visual-proprioceptive realignment to unfold more slowly and to reflect feedback influences during the terminal (deceleration) phase of the reach. The results confirmed these hypotheses. Rapid error reduction during the early stage of prism exposure was achieved by trial-by-trial adjustments of the motor plan, which were proportional to the endpoint error feedback from the previous trial. By contrast, compensation of the terminal reach phase unfolded slowly across the duration of prism exposure. Even after 100 trials of pointing through prisms, adaptation was incomplete, with participants continuing to exhibit a small rightward shift in both the reach endpoints and in the terminal phase of reach trajectories. Individual differences in the degree of
Hansen, M; Haugland, M K
2001-01-01
Adaptive restriction rules based on fuzzy logic have been developed to eliminate errors and to increase stimulation safety in the foot-drop correction application, specifically when using adaptive logic networks to provide a stimulation control signal based on neural activity recorded from peripheral sensory nerve branches. The fuzzy rules were designed to increase flexibility and offer easier customization, compared to earlier versions of restriction rules. The rules developed quantified the duration of swing and stance phases into states of accepting or rejecting new transitions, based on the cyclic nature of gait and statistics on the current gait patterns. The rules were easy to custom design for a specific application, using linguistic terms to model the actions of the rules. The rules were tested using pre-recorded gait data processed through a gait event detector and proved to reduce detection delay and the number of errors, compared to conventional rules.
Zhou, Hui; Kunz, Thomas; Schwartz, Howard
2011-01-01
Traditional oscillators used in timing modules of CDMA and WiMAX base stations are large and expensive. Applying cheaper and smaller, albeit more inaccurate, oscillators in timing modules is an interesting research challenge. An adaptive control algorithm is presented to enhance the oscillators to meet the requirements of base stations during holdover mode. An oscillator frequency stability model is developed for the adaptive control algorithm. This model takes into account the control loop which creates the correction signal when the timing module is in locked mode. A recursive prediction error method is used to identify the system model parameters. Simulation results show that an oscillator enhanced by our adaptive control algorithm improves the oscillator performance significantly, compared with uncorrected oscillators. Our results also show the benefit of explicitly modeling the control loop. Finally, the cumulative time error upper bound of such enhanced oscillators is investigated analytically and comparison results between the analytical and simulated upper bound are provided. The results show that the analytical upper bound can serve as a practical guide for system designers.
Performance analysis of ARQ error controls under Markovian block error pattern
NASA Astrophysics Data System (ADS)
Cho, Young Jong; Un, Chong Kwan
1994-02-01
In this paper, we investigate the effect of forward/backward channel memory (statistical dependence in the occurrence of transmission errors) on ARQ error controls. To take into account the effect of backward channel errors in the performance analysis, we suppose some modified ARQ schemes that have an effective retransmission strategy to prevent the deadlock incurred by the errors on acknowledgments. In the study, we consider two modified go-back-N schemes with timer control and with buffer control.
Type I Error Control for Tree Classification
Jung, Sin-Ho; Chen, Yong; Ahn, Hongshik
2014-01-01
Binary tree classification has been useful for classifying the whole population based on the levels of outcome variable that is associated with chosen predictors. Often we start a classification with a large number of candidate predictors, and each predictor takes a number of different cutoff values. Because of these types of multiplicity, binary tree classification method is subject to severe type I error probability. Nonetheless, there have not been many publications to address this issue. In this paper, we propose a binary tree classification method to control the probability to accept a predictor below certain level, say 5%. PMID:25452689
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.
Adaptive and Nonlinear Control
1992-02-29
in [22], we also applied the concept of zero dynamics to the problem of exact linearization of a nonlinear control system by dynamic feedback. Exact ...nonlinear systems, although it was well-known that the conditions for exact linearization are very stringent and consequently do not apply to a broad...29th IEEE Conference n Decision and Control, Invited Paper delivered by Dr. Gilliam. Exact Linearization of Zero Dynamics, 29th IEEE Conference on
Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum
Ziauddeen, Hisham; Vestergaard, Martin D.; Spencer, Tom
2017-01-01
Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness. SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that
Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum.
Diederen, Kelly M J; Ziauddeen, Hisham; Vestergaard, Martin D; Spencer, Tom; Schultz, Wolfram; Fletcher, Paul C
2017-02-15
Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness.SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that
Synthesis of nonlinear adaptive controller for a batch distillation.
Jana, Amiya K
2007-02-01
A nonlinear adaptive control strategy is proposed for a binary batch distillation column. The hybrid control algorithm comprises a generic model controller (GMC) and a nonlinear adaptive state estimator (ASE). The adaptive observation scheme mainly estimates the imprecisely known parameters based on the available tray temperature measurements. The sensitivity of the proposed estimator is investigated with respect to the effect of initialization error, unmeasured disturbance and uncertainty. Then, a comparative study is carried out between the derived nonlinear GMC-ASE controller and a traditional proportional integral law in terms of set point tracking and disturbance rejection performance. The study also includes the effect of measurement noise and parametric uncertainty on the closed-loop performance. The proposed adaptive control algorithm is shown to be quite promising due to the exponential error convergence capability of the ASE estimator in addition to the high-quality control action provided by the GMC controller.
Geometric view of adaptive optics control
NASA Astrophysics Data System (ADS)
Wiberg, Donald M.; Max, Claire E.; Gavel, Donald T.
2005-05-01
The objective of an astronomical adaptive optics control system is to minimize the residual wave-front error remaining on the science-object wave fronts after being compensated for atmospheric turbulence and telescope aberrations. Minimizing the mean square wave-front residual maximizes the Strehl ratio and the encircled energy in pointlike images and maximizes the contrast and resolution of extended images. We prove the separation principle of optimal control for application to adaptive optics so as to minimize the mean square wave-front residual. This shows that the residual wave-front error attributable to the control system can be decomposed into three independent terms that can be treated separately in design. The first term depends on the geometry of the wave-front sensor(s), the second term depends on the geometry of the deformable mirror(s), and the third term is a stochastic term that depends on the signal-to-noise ratio. The geometric view comes from understanding that the underlying quantity of interest, the wave-front phase surface, is really an infinite-dimensional vector within a Hilbert space and that this vector space is projected into subspaces we can control and measure by the deformable mirrors and wave-front sensors, respectively. When the control and estimation algorithms are optimal, the residual wave front is in a subspace that is the union of subspaces orthogonal to both of these projections. The method is general in that it applies both to conventional (on-axis, ground-layer conjugate) adaptive optics architectures and to more complicated multi-guide-star- and multiconjugate-layer architectures envisaged for future giant telescopes. We illustrate the approach by using a simple example that has been worked out previously [J. Opt. Soc. Am. A73, 1171 (1983)] for a single-conjugate, static atmosphere case and follow up with a discussion of how it is extendable to general adaptive optics architectures.
Neural signatures of adaptive post-error adjustments in visual search.
Steinhauser, Robert; Maier, Martin E; Steinhauser, Marco
2017-02-22
Errors in speeded choice tasks can lead to post-error adjustments both on the behavioral and on the neural level. There is an ongoing debate whether such adjustments result from adaptive processes that serve to optimize performance or whether they reflect interference from error monitoring or attentional orientation. The present study aimed at identifying adaptive adjustments in a two-stage visual search task, in which participants had to select and subsequently identify a target stimulus presented to the left or right visual hemifield. Target selection and identification can be measured by two distinct event-related potentials, the N2pc and the SPCN. Using a decoder analysis based on multivariate pattern analysis, we were able to isolate the processing stages related to error sources and post-error adjustments. Whereas errors were linked to deviations in the N2pc and the SPCN, only for the N2pc we identified a post-error adjustment, which exhibits key features of source-specific adaptivity. While errors were associated with an increased N2pc, post-error adjustments consisted in an N2pc decrease. We interpret this as an adaptive adjustment of target selection to prevent errors due to disproportionate processing of the task-irrelevant target location. Our study thus provides evidence for adaptive post-error adjustments in visual search.
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
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
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.
2014-06-01
Document Number: SET 2014-0039 412TW-PA-14271 Adaptive Modulation Schemes for OFDM and SOQPSK Using Error Vector Magnitude (EVM...4. TITLE AND SUBTITLE Adaptive Modulation Schemes for OFDM and SOQPSK Using Error Vector Magnitude (EVM) and Godard Dispersion 5a. CONTRACT NUMBER...multiplexing ( OFDM ) and shaped-offset quadrature phased-shift keying (SOQPSK). We present the error vector magnitude (EVM) for OFDM and second-order Godard
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.
Eldred, Michael Scott; Subia, Samuel Ramirez; Neckels, David; Hopkins, Matthew Morgan; Notz, Patrick K.; Adams, Brian M.; Carnes, Brian; Wittwer, Jonathan W.; Bichon, Barron J.; Copps, Kevin D.
2006-10-01
This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.
Adaptive integral robust control and application to electromechanical servo systems.
Deng, Wenxiang; Yao, Jianyong
2017-03-01
This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers.
Bagce, Hamid F.; Saleh, Soha; Adamovich, Sergei V.; Krakauer, John W.
2013-01-01
We used adaptation to high and low gains in a virtual reality setup of the hand to test competing hypotheses about the excitability changes that accompany motor learning. Excitability was assayed through changes in amplitude of motor evoked potentials (MEPs) in relevant hand muscles elicited with single-pulse transcranial magnetic stimulation (TMS). One hypothesis is that MEPs will either increase or decrease, directly reflecting the effect of low or high gain on motor output. The alternative hypothesis is that MEP changes are not sign dependent but rather serve as a marker of visuomotor learning, independent of performance or visual-to-motor mismatch (i.e., error). Subjects were required to make flexion movements of a virtual forefinger to visual targets. A gain of 1 meant that the excursions of their real finger and virtual finger matched. A gain of 0.25 (“low gain”) indicated a 75% reduction in visual versus real finger displacement, a gain of 1.75 (“high gain”) the opposite. MEP increases (>40%) were noted in the tonically activated task-relevant agonist muscle for both high- and low-gain perturbations after adaptation reached asymptote with kinematics matched to veridical levels. Conversely, only small changes in excitability occurred in a control task of pseudorandom gains that required adjustments to large errors but in which learning could not accumulate. We conclude that changes in corticospinal excitability are related to learning rather than performance or error. PMID:23197454
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.
The reduced order model problem in distributed parameter systems adaptive identification and control
NASA Technical Reports Server (NTRS)
Johnson, C. R., Jr.
1980-01-01
The research concerning the reduced order model problem in distributed parameter systems is reported. The adaptive control strategy was chosen for investigation in the annular momentum control device. It is noted, that if there is no observation spill over, and no model errors, an indirect adaptive control strategy can be globally stable. Recent publications concerning adaptive control are included.
Global error estimation based on the tolerance proportionality for some adaptive Runge-Kutta codes
NASA Astrophysics Data System (ADS)
Calvo, M.; González-Pinto, S.; Montijano, J. I.
2008-09-01
Modern codes for the numerical solution of Initial Value Problems (IVPs) in ODEs are based in adaptive methods that, for a user supplied tolerance [delta], attempt to advance the integration selecting the size of each step so that some measure of the local error is [similar, equals][delta]. Although this policy does not ensure that the global errors are under the prescribed tolerance, after the early studies of Stetter [Considerations concerning a theory for ODE-solvers, in: R. Burlisch, R.D. Grigorieff, J. Schröder (Eds.), Numerical Treatment of Differential Equations, Proceedings of Oberwolfach, 1976, Lecture Notes in Mathematics, vol. 631, Springer, Berlin, 1978, pp. 188-200; Tolerance proportionality in ODE codes, in: R. März (Ed.), Proceedings of the Second Conference on Numerical Treatment of Ordinary Differential Equations, Humbold University, Berlin, 1980, pp. 109-123] and the extensions of Higham [Global error versus tolerance for explicit Runge-Kutta methods, IMA J. Numer. Anal. 11 (1991) 457-480; The tolerance proportionality of adaptive ODE solvers, J. Comput. Appl. Math. 45 (1993) 227-236; The reliability of standard local error control algorithms for initial value ordinary differential equations, in: Proceedings: The Quality of Numerical Software: Assessment and Enhancement, IFIP Series, Springer, Berlin, 1997], it has been proved that in many existing explicit Runge-Kutta codes the global errors behave asymptotically as some rational power of [delta]. This step-size policy, for a given IVP, determines at each grid point tn a new step-size hn+1=h(tn;[delta]) so that h(t;[delta]) is a continuous function of t. In this paper a study of the tolerance proportionality property under a discontinuous step-size policy that does not allow to change the size of the step if the step-size ratio between two consecutive steps is close to unity is carried out. This theory is applied to obtain global error estimations in a few problems that have been solved with
An error control system with multiple-stage forward error corrections
NASA Technical Reports Server (NTRS)
Takata, Toyoo; Fujiwara, Toru; Kasami, Tadao; Lin, Shu
1990-01-01
A robust error-control coding system is presented. This system is a cascaded FEC (forward error control) scheme supported by parity retransmissions for further error correction in the erroneous data words. The error performance and throughput efficiency of the system are analyzed. Two specific examples of the error-control system are studied. The first example does not use an inner code, and the outer code, which is not interleaved, is a shortened code of the NASA standard RS code over GF(28). The second example, as proposed for NASA, uses the same shortened RS code as the base outer code C2, except that it is interleaved to a depth of 2. It is shown that both examples provide high reliability and throughput efficiency even for high channel bit-error rates in the range of 0.01.
On fractional order composite model reference adaptive control
NASA Astrophysics Data System (ADS)
Wei, Yiheng; Sun, Zhenyuan; Hu, Yangsheng; Wang, Yong
2016-08-01
This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.
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.
Application of Interval Analysis to Error Control.
1976-09-01
We give simple examples of ways in which interval arithmetic can be used to alert instabilities in computer algorithms , roundoff error accumulation, and even the effects of hardware inadequacies. This paper is primarily tutorial. (Author)
Direct Adaptive Control Of An Industrial Robot
NASA Technical Reports Server (NTRS)
Seraji, Homayoun; Lee, Thomas; Delpech, Michel
1992-01-01
Decentralized direct adaptive control scheme for six-jointed industrial robot eliminates part of overall computational burden imposed by centralized controller and degrades performance of robot by reducing sampling rate. Control and controller-adaptation laws based on observed performance of manipulator: no need to model dynamics of robot. Adaptive controllers cope with uncertainties and variations in robot and payload.
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.
Adaptive controller for hyperthermia robot
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).
An hp-adaptivity and error estimation for hyperbolic conservation laws
NASA Technical Reports Server (NTRS)
Bey, Kim S.
1995-01-01
This paper presents an hp-adaptive discontinuous Galerkin method for linear hyperbolic conservation laws. A priori and a posteriori error estimates are derived in mesh-dependent norms which reflect the dependence of the approximate solution on the element size (h) and the degree (p) of the local polynomial approximation. The a posteriori error estimate, based on the element residual method, provides bounds on the actual global error in the approximate solution. The adaptive strategy is designed to deliver an approximate solution with the specified level of error in three steps. The a posteriori estimate is used to assess the accuracy of a given approximate solution and the a priori estimate is used to predict the mesh refinements and polynomial enrichment needed to deliver the desired solution. Numerical examples demonstrate the reliability of the a posteriori error estimates and the effectiveness of the hp-adaptive strategy.
Digital adaptive flight controller development
NASA Technical Reports Server (NTRS)
Kaufman, H.; Alag, G.; Berry, P.; Kotob, S.
1974-01-01
A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Two designs are described for an example aircraft. Each of these designs uses a weighted least squares procedure to identify parameters defining the dynamics of the aircraft. The two designs differ in the way in which control law parameters are determined. One uses the solution of an optimal linear regulator problem to determine these parameters while the other uses a procedure called single stage optimization. Extensive simulation results and analysis leading to the designs are presented.
Adaptive support vector regression for UAV flight control.
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.
A Java Applet for Illustrating Internet Error Control
ERIC Educational Resources Information Center
Holliday, Mark A.
2004-01-01
This paper discusses the author's experiences developing a Java applet that illustrates how error control is implemented in the Transmission Control Protocol (TCP). One section discusses the concepts which the TCP error control Java applet is intended to convey, while the nature of the Java applet is covered in another section. The author…
Attitude control with realization of linear error dynamics
NASA Technical Reports Server (NTRS)
Paielli, Russell A.; Bach, Ralph E.
1993-01-01
An attitude control law is derived to realize linear unforced error dynamics with the attitude error defined in terms of rotation group algebra (rather than vector algebra). Euler parameters are used in the rotational dynamics model because they are globally nonsingular, but only the minimal three Euler parameters are used in the error dynamics model because they have no nonlinear mathematical constraints to prevent the realization of linear error dynamics. The control law is singular only when the attitude error angle is exactly pi rad about any eigenaxis, and a simple intuitive modification at the singularity allows the control law to be used globally. The forced error dynamics are nonlinear but stable. Numerical simulation tests show that the control law performs robustly for both initial attitude acquisition and attitude control.
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.
Keck adaptive optics: control subsystem
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.
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.
Frontal theta links prediction errors to behavioral adaptation in reinforcement learning.
Cavanagh, James F; Frank, Michael J; Klein, Theresa J; Allen, John J B
2010-02-15
Investigations into action monitoring have consistently detailed a frontocentral voltage deflection in the event-related potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the feedback-related negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single-trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single-trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Mediofrontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single-trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations, with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice.
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.
Error estimation and adaptive mesh refinement for parallel analysis of shell structures
NASA Technical Reports Server (NTRS)
Keating, Scott C.; Felippa, Carlos A.; Park, K. C.
1994-01-01
The formulation and application of element-level, element-independent error indicators is investigated. This research culminates in the development of an error indicator formulation which is derived based on the projection of element deformation onto the intrinsic element displacement modes. The qualifier 'element-level' means that no information from adjacent elements is used for error estimation. This property is ideally suited for obtaining error values and driving adaptive mesh refinements on parallel computers where access to neighboring elements residing on different processors may incur significant overhead. In addition such estimators are insensitive to the presence of physical interfaces and junctures. An error indicator qualifies as 'element-independent' when only visible quantities such as element stiffness and nodal displacements are used to quantify error. Error evaluation at the element level and element independence for the error indicator are highly desired properties for computing error in production-level finite element codes. Four element-level error indicators have been constructed. Two of the indicators are based on variational formulation of the element stiffness and are element-dependent. Their derivations are retained for developmental purposes. The second two indicators mimic and exceed the first two in performance but require no special formulation of the element stiffness mesh refinement which we demonstrate for two dimensional plane stress problems. The parallelizing of substructures and adaptive mesh refinement is discussed and the final error indicator using two-dimensional plane-stress and three-dimensional shell problems is demonstrated.
Adaptive control system for pulsed megawatt klystrons
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.
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.
Robust adaptive kinematic control of redundant robots
NASA Technical Reports Server (NTRS)
Tarokh, M.; Zuck, D. D.
1992-01-01
The paper presents a general method for the resolution of redundancy that combines the Jacobian pseudoinverse and augmentation approaches. A direct adaptive control scheme is developed to generate joint angle trajectories for achieving desired end-effector motion as well as additional user defined tasks. The scheme ensures arbitrarily small errors between the desired and the actual motion of the manipulator. Explicit bounds on the errors are established that are directly related to the mismatch between actual and estimated pseudoinverse Jacobian matrix, motion velocity and the controller gain. It is shown that the scheme is tolerant of the mismatch and consequently only infrequent pseudoinverse computations are needed during a typical robot motion. As a result, the scheme is computationally fast, and can be implemented for real-time control of redundant robots. A method is incorporated to cope with the robot singularities allowing the manipulator to get very close or even pass through a singularity while maintaining a good tracking performance and acceptable joint velocities. Computer simulations and experimental results are provided in support of the theoretical developments.
NASA Astrophysics Data System (ADS)
Ferreira, F.; Gendron, E.; Rousset, G.; Gratadour, D.
2016-07-01
The future European Extremely Large Telescope (E-ELT) adaptive optics (AO) systems will aim at wide field correction and large sky coverage. Their performance will be improved by using post processing techniques, such as point spread function (PSF) deconvolution. The PSF estimation involves characterization of the different error sources in the AO system. Such error contributors are difficult to estimate: simulation tools are a good way to do that. We have developed in COMPASS (COMputing Platform for Adaptive opticS Systems), an end-to-end simulation tool using GPU (Graphics Processing Unit) acceleration, an estimation tool that provides a comprehensive error budget by the outputs of a single simulation run.
Adaptive-feedback control algorithm.
Huang, Debin
2006-06-01
This paper is motivated by giving the detailed proofs and some interesting remarks on the results the author obtained in a series of papers [Phys. Rev. Lett. 93, 214101 (2004); Phys. Rev. E 71, 037203 (2005); 69, 067201 (2004)], where an adaptive-feedback algorithm was proposed to effectively stabilize and synchronize chaotic systems. This note proves in detail the strictness of this algorithm from the viewpoint of mathematics, and gives some interesting remarks for its potential applications to chaos control & synchronization. In addition, a significant comment on synchronization-based parameter estimation is given, which shows some techniques proposed in literature less strict and ineffective in some cases.
Field-balanced adaptive optics error function for wide field-of-view space-based systems
NASA Astrophysics Data System (ADS)
McComas, Brian K.; Friedman, Edward J.
2002-03-01
Adaptive optics are regularly used in ground-based astronomical telescopes. These applications are characterized by a very narrow (approximately 1 arcmin) field of view. For economic reasons, commercial space-based earth-observing optical systems must have a field of view as large as possible. We develop a new error function that is an extension of conventional adaptive optics for wide field-of-view optical systems and show that this new error function enables diffraction-limited performance across a large field of view with only one deformable mirror. This new error function allows for reprogramming of aberration control algorithms for particular applications by the use of an addressable weighting function.
Adaptive Flight Control for Aircraft Safety Enhancements
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Gregory, Irene M.; Joshi, Suresh M.
2008-01-01
This poster presents the current adaptive control research being conducted at NASA ARC and LaRC in support of the Integrated Resilient Aircraft Control (IRAC) project. The technique "Approximate Stability Margin Analysis of Hybrid Direct-Indirect Adaptive Control" has been developed at NASA ARC to address the needs for stability margin metrics for adaptive control that potentially enables future V&V of adaptive systems. The technique "Direct Adaptive Control With Unknown Actuator Failures" is developed at NASA LaRC to deal with unknown actuator failures. The technique "Adaptive Control with Adaptive Pilot Element" is being researched at NASA LaRC to investigate the effects of pilot interactions with adaptive flight control that can have implications of stability and performance.
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.
Adaptive neural networks for mobile robotic control
NASA Astrophysics Data System (ADS)
Burnett, Jeff R.; Dagli, Cihan H.
2001-03-01
Movement of a differential drive robot has non-linear dependence on the current position and orientation. A controller must be able to deal with the non-linearity of the plant. The controller must either linearize the plant and deal with special cases, or be non-linear itself. Once the controller is designed, implementation on a real robotic platform presents challenges due to the varying parameters of the plant. Robots of the same model may have different motor frictions. The surface the robot maneuvers on may change e.g. carpet to tile. Batteries will drain, providing less power over time. A feed-forward neural network controller could overcome these challenges. The network could learn the non- linearities of the plant and monitor the error for parameter changes and adapt to them. In this manner, a single controller can be designed for an ideal robot, and then used to populate a multi-robot colony without manually fine tuning the controller for each robot. This paper shall demonstrate such a controller, outlining design in simulation and implementation on Khepera robotic platforms.
Adjoint-Based, Three-Dimensional Error Prediction and Grid Adaptation
NASA Technical Reports Server (NTRS)
Park, Michael A.
2002-01-01
Engineering computational fluid dynamics (CFD) analysis and design applications focus on output functions (e.g., lift, drag). Errors in these output functions are generally unknown and conservatively accurate solutions may be computed. Computable error estimates can offer the possibility to minimize computational work for a prescribed error tolerance. Such an estimate can be computed by solving the flow equations and the linear adjoint problem for the functional of interest. The computational mesh can be modified to minimize the uncertainty of a computed error estimate. This robust mesh-adaptation procedure automatically terminates when the simulation is within a user specified error tolerance. This procedure for estimating and adapting to error in a functional is demonstrated for three-dimensional Euler problems. An adaptive mesh procedure that links to a Computer Aided Design (CAD) surface representation is demonstrated for wing, wing-body, and extruded high lift airfoil configurations. The error estimation and adaptation procedure yielded corrected functions that are as accurate as functions calculated on uniformly refined grids with ten times as many grid points.
ZZ-Type a posteriori error estimators for adaptive boundary element methods on a curve☆
Feischl, Michael; Führer, Thomas; Karkulik, Michael; Praetorius, Dirk
2014-01-01
In the context of the adaptive finite element method (FEM), ZZ-error estimators named after Zienkiewicz and Zhu (1987) [52] are mathematically well-established and widely used in practice. In this work, we propose and analyze ZZ-type error estimators for the adaptive boundary element method (BEM). We consider weakly singular and hyper-singular integral equations and prove, in particular, convergence of the related adaptive mesh-refining algorithms. Throughout, the theoretical findings are underlined by numerical experiments. PMID:24748725
Adaptive data assimilation including the effect of spatial variations in observation error
NASA Astrophysics Data System (ADS)
Frehlich, Rod
2006-04-01
An optimal adaptive data assimilation algorithm is derived using the maximum likelihood method based on a conditional Gaussian probability density function for the first-guess and direct observations of the state variables but including local estimates of the observation and first-guess error statistics. An interpolation of the first-guess field to the observation coordinates is not required under the assumption of locally homogeneous statistics for the random atmosphere. However, the definition of observation error requires a definition of model 'truth' which is defined as a spatial average of the continuous random atmospheric variables. Then the total observation error consists of two independent components: an instrument error and an observation sampling error defined by the spatial average of the observation and the statistics of the local turbulence. Estimates of the observation sampling error statistics are determined from an ensemble of background or first-guess fields or from the analysis of the raw data from instrumented aircraft, Doppler lidars, or radar profilers. The spatial variations of the sampling error are referenced to the local turbulence conditions at each analysis coordinate and therefore each observation can have a different observation error for each nearby analysis coordinate. The extension of the adaptive assimilation concept to include the spatial variations in observation error for statistical interpolation, 3D-Var, 4D-Var, extended Kalman filtering, and ensemble Kalman filtering is also presented for the traditional meaning of observation error, i.e. each observation is assigned a single error. The conditional analysis error is derived for a single observation at the analysis coordinate and multiple observations around the analysis point. Example calculations of the conditional analysis error are presented for a few simple set of observation and measurement geometries to demonstrate the impact of the spatially variable observation errors
Designing to Control Flight Crew Errors
NASA Technical Reports Server (NTRS)
Schutte, Paul C.; Willshire, Kelli F.
1997-01-01
It is widely accepted that human error is a major contributing factor in aircraft accidents. There has been a significant amount of research in why these errors occurred, and many reports state that the design of flight deck can actually dispose humans to err. This research has led to the call for changes in design according to human factors and human-centered principles. The National Aeronautics and Space Administration's (NASA) Langley Research Center has initiated an effort to design a human-centered flight deck from a clean slate (i.e., without constraints of existing designs.) The effort will be based on recent research in human-centered design philosophy and mission management categories. This design will match the human's model of the mission and function of the aircraft to reduce unnatural or non-intuitive interfaces. The product of this effort will be a flight deck design description, including training and procedures, and a cross reference or paper trail back to design hypotheses, and an evaluation of the design. The present paper will discuss the philosophy, process, and status of this design effort.
Servo control booster system for minimizing following error
Wise, William L.
1985-01-01
A closed-loop feedback-controlled servo system is disclosed which reduces command-to-response error to the system's position feedback resolution least increment, .DELTA.S.sub.R, on a continuous real-time basis for all operating speeds. The servo system employs a second position feedback control loop on a by exception basis, when the command-to-response error .gtoreq..DELTA.S.sub.R, to produce precise position correction signals. When the command-to-response error is less than .DELTA.S.sub.R, control automatically reverts to conventional control means as the second position feedback control loop is disconnected, becoming transparent to conventional servo control means. By operating the second unique position feedback control loop used herein at the appropriate clocking rate, command-to-response error may be reduced to the position feedback resolution least increment. The present system may be utilized in combination with a tachometer loop for increased stability.
Real-time error detection but not error correction drives automatic visuomotor adaptation.
Hinder, Mark R; Riek, Stephan; Tresilian, James R; de Rugy, Aymar; Carson, Richard G
2010-03-01
We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion-extension, forearm pronation-supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60 degrees visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.
Steady-state error of a system with fuzzy controller.
Butkiewicz, B S
1998-01-01
We consider the problem of control error of a fuzzy system with feedback. The system consists of a plant, linear or nonlinear, fuzzy controller, and feedback loop. As controller we use both PD and PI fuzzy type controllers. We apply different t-norm and co-norm: logic, algebraic, Yager, Hamacher, bounded, drastic, etc. in the process of fuzzy reasoning. Triangular shape of membership functions is supposed, but we generalize the results obtained. Steady-state error of a system is calculated. We have obtained very interesting results. The steady-state error is identical for pairs of triangular t- and co-norms.
Adaptive error covariances estimation methods for ensemble Kalman filters
Zhen, Yicun; Harlim, John
2015-08-01
This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.
Error control for reliable digital data transmission and storage systems
NASA Technical Reports Server (NTRS)
Costello, D. J., Jr.; Deng, R. H.
1985-01-01
A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256K-bit DRAM's are organized in 32Kx8 bit-bytes. Byte oriented codes such as Reed Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. In this paper we present some special decoding techniques for extended single-and-double-error-correcting RS codes which are capable of high speed operation. These techniques are designed to find the error locations and the error values directly from the syndrome without having to use the iterative alorithm to find the error locator polynomial. Two codes are considered: (1) a d sub min = 4 single-byte-error-correcting (SBEC), double-byte-error-detecting (DBED) RS code; and (2) a d sub min = 6 double-byte-error-correcting (DBEC), triple-byte-error-detecting (TBED) RS code.
Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments
Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne
2015-01-01
In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916
Adaptive filter design using recurrent cerebellar model articulation controller.
Lin, Chih-Min; Chen, Li-Yang; Yeung, Daniel S
2010-07-01
A novel adaptive filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so the stability of the filtering error can be guaranteed. To demonstrate the performance of the proposed adaptive RCMAC filter, it is applied to a nonlinear channel equalization system and an adaptive noise cancelation system. The advantages of the proposed filter over other adaptive filters are verified through simulations.
Gilchrist, Michael A.; Shah, Premal; Zaretzki, Russell
2009-01-01
Codon usage bias (CUB) has been documented across a wide range of taxa and is the subject of numerous studies. While most explanations of CUB invoke some type of natural selection, most measures of CUB adaptation are heuristically defined. In contrast, we present a novel and mechanistic method for defining and contextualizing CUB adaptation to reduce the cost of nonsense errors during protein translation. Using a model of protein translation, we develop a general approach for measuring the protein production cost in the face of nonsense errors of a given allele as well as the mean and variance of these costs across its coding synonyms. We then use these results to define the nonsense error adaptation index (NAI) of the allele or a contiguous subset thereof. Conceptually, the NAI value of an allele is a relative measure of its elevation on a specific and well-defined adaptive landscape. To illustrate its utility, we calculate NAI values for the entire coding sequence and across a set of nonoverlapping windows for each gene in the Saccharomyces cerevisiae S288c genome. Our results provide clear evidence of adaptation to reduce the cost of nonsense errors and increasing adaptation with codon position and expression. The magnitude and nature of this adaptation are also largely consistent with simulation results in which nonsense errors are the only selective force driving CUB evolution. Because NAI is derived from mechanistic models, it is both easier to interpret and more amenable to future refinement than other commonly used measures of codon bias. Further, our approach can also be used as a starting point for developing other mechanistically derived measures of adaptation such as for translational accuracy. PMID:19822731
Striatal prediction errors support dynamic control of declarative memory decisions
Scimeca, Jason M.; Katzman, Perri L.; Badre, David
2016-01-01
Adaptive memory requires context-dependent control over how information is retrieved, evaluated and used to guide action, yet the signals that drive adjustments to memory decisions remain unknown. Here we show that prediction errors (PEs) coded by the striatum support control over memory decisions. Human participants completed a recognition memory test that incorporated biased feedback to influence participants' recognition criterion. Using model-based fMRI, we find that PEs—the deviation between the outcome and expected value of a memory decision—correlate with striatal activity and predict individuals' final criterion. Importantly, the striatal PEs are scaled relative to memory strength rather than the expected trial outcome. Follow-up experiments show that the learned recognition criterion transfers to free recall, and targeting biased feedback to experimentally manipulate the magnitude of PEs influences criterion consistent with PEs scaled relative to memory strength. This provides convergent evidence that declarative memory decisions can be regulated via striatally mediated reinforcement learning signals. PMID:27713407
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.
Multiple Cognitive Control Effects of Error Likelihood and Conflict
Brown, Joshua W.
2010-01-01
Recent work on cognitive control has suggested a variety of performance monitoring functions of the anterior cingulate cortex, such as errors, conflict, error likelihood, and others. Given the variety of monitoring effects, a corresponding variety of control effects on behavior might be expected. This paper explores whether conflict and error likelihood produce distinct cognitive control effects on behavior, as measured by response time. A change signal task (Brown & Braver, 2005) was modified to include conditions of likely errors due to tardy as well as premature responses, in conditions with and without conflict. The results discriminate between competing hypotheses of independent vs. interacting conflict and error likelihood control effects. Specifically, the results suggest that the likelihood of premature vs. tardy response errors can lead to multiple distinct control effects, which are independent of cognitive control effects driven by response conflict. As a whole, the results point to the existence of multiple distinct cognitive control mechanisms and challenge existing models of cognitive control that incorporate only a single control signal. PMID:19030873
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.
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.
Adaptive Optics Correction in Real-Time for Dynamic Wavefront Errors
1990-03-15
This paper reports on the principles for the use of, and the experimental results obtained from, an adaptive optics system for correcting dynamic...control system. Keywords: Adaptive optics ; Wavefront sensing; Deformable mirror; Chinese translations.
Inherent Error in Asynchronous Digital Flight Controls.
1980-02-01
the algorithm for estimating T, * will wait until the state observers (x*) equal the state variables (xp) and this system is in steady state. From...Appendix A (this system is in steady state at the time 200T) and Appendix C (the state observers equal the state variables at time approximate equals 40T...system, the DIGITAL CONTROLLER #1 in the monitor will wait until the state observers (x*) equal the state variables (xp). Then p the DIGITAL CONTROLLER
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.
Adaptive, predictive controller for optimal process control
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.
Hybrid adaptive ascent flight control for a flexible launch vehicle
NASA Astrophysics Data System (ADS)
Lefevre, Brian D.
hybrid adaptive flight controller, development of a Newton's method based online parameter update that is modified to include a step size which regulates the rate of change in the parameter estimates, comparison of the modified Newton's method and recursive least squares online parameter update algorithms, modification of the neural network's input structure to accommodate for the nature of the nonlinearities present in a launch vehicle's ascent flight, examination of both tracking error based and modeling error based neural network weight update laws, and integration of feedback filters for the purpose of preventing harmful interaction between the flight control system and flexible structural modes. To validate the hybrid adaptive controller, a high-fidelity Ares I ascent flight simulator and a classical gain-scheduled proportional-integral-derivative (PID) ascent flight controller were obtained from the NASA Marshall Space Flight Center. The classical PID flight controller is used as a benchmark when analyzing the performance of the hybrid adaptive flight controller. Simulations are conducted which model both nominal and off-nominal flight conditions with structural flexibility of the vehicle either enabled or disabled. First, rigid body ascent simulations are performed with the hybrid adaptive controller under nominal flight conditions for the purpose of selecting the update laws which drive the indirect and direct adaptive components. With the neural network disabled, the results revealed that the recursive least squares online parameter update caused high frequency oscillations to appear in the engine gimbal commands. This is highly undesirable for long and slender launch vehicles, such as the Ares I, because such oscillation of the rocket nozzle could excite unstable structural flex modes. In contrast, the modified Newton's method online parameter update produced smooth control signals and was thus selected for use in the hybrid adaptive launch vehicle flight
Adaptive and predictive control of a simulated robot arm.
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).
Multilevel Error Estimation and Adaptive h-Refinement for Cartesian Meshes with Embedded Boundaries
NASA Technical Reports Server (NTRS)
Aftosmis, M. J.; Berger, M. J.; Kwak, Dochan (Technical Monitor)
2002-01-01
This paper presents the development of a mesh adaptation module for a multilevel Cartesian solver. While the module allows mesh refinement to be driven by a variety of different refinement parameters, a central feature in its design is the incorporation of a multilevel error estimator based upon direct estimates of the local truncation error using tau-extrapolation. This error indicator exploits the fact that in regions of uniform Cartesian mesh, the spatial operator is exactly the same on the fine and coarse grids, and local truncation error estimates can be constructed by evaluating the residual on the coarse grid of the restricted solution from the fine grid. A new strategy for adaptive h-refinement is also developed to prevent errors in smooth regions of the flow from being masked by shocks and other discontinuous features. For certain classes of error histograms, this strategy is optimal for achieving equidistribution of the refinement parameters on hierarchical meshes, and therefore ensures grid converged solutions will be achieved for appropriately chosen refinement parameters. The robustness and accuracy of the adaptation module is demonstrated using both simple model problems and complex three dimensional examples using meshes with from 10(exp 6), to 10(exp 7) cells.
Cognitive control adjustments and conflict adaptation in major depressive disorder.
Clawson, Ann; Clayson, Peter E; Larson, Michael J
2013-08-01
Individuals with major depressive disorder (MDD) show alterations in the cognitive control function of conflict processing. We examined the influence of these deficits on behavioral and event-related potential (ERP) indices of conflict adaptation, a cognitive control process wherein previous-trial congruency modulates current-trial performance, in 55 individuals with MDD and 55 matched controls. ERPs were calculated while participants completed a modified flanker task. There were nonsignificant between-groups differences in response time, error rate, and N2 indices of conflict adaptation. Higher depressive symptom scores were associated with smaller mean N2 conflict adaptation scores for individuals with MDD and when collapsed across groups. Results were consistent when comorbidity and medications were analyzed. These findings suggest N2 conflict adaptation is associated with depressive symptoms rather than clinical diagnosis alone.
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.
Composite Gauss-Legendre Quadrature with Error Control
ERIC Educational Resources Information Center
Prentice, J. S. C.
2011-01-01
We describe composite Gauss-Legendre quadrature for determining definite integrals, including a means of controlling the approximation error. We compare the form and performance of the algorithm with standard Newton-Cotes quadrature. (Contains 1 table.)
Model reference adaptive control using only input and output signals
NASA Technical Reports Server (NTRS)
Monopoli, R. V.
1973-01-01
It is shown how globally stable model reference adaptive control systems may be designed using only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Liapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Filtered derivatives of the plant output replace pure derivatives which are normally required in these systems. An augmented error signal replaces the error previously used which is the difference between the model and plant outputs. However, global stability is assured in the sense that this difference approaches zero asymptotically.
2014-10-01
Number: SET 2015-0030 412 TW-PA-14481 Adaptive Modulation Schemes for OFDM and...SUBTITLE Adaptive Modulation Schemes for OFDM and SOQPSK Using Error Vector Magnitude (EVM) and Godard Dispersion 5a. CONTRACT NUMBER: W900KK-13-C...schemes of OFDM and SOQPSK? • Possible Approaches: • Find a common metric that applies for both OFDM and SOQPSK • Find the relationship between two
Adaptive Control: Actual Status and Trends
NASA Technical Reports Server (NTRS)
Landau, I. D.
1985-01-01
Important progress in research and application of Adaptive Control Systems has been achieved in the last ten years. The techniques which are currently used in applications will be reviewed. Theoretical aspects currently under investigation and which are related to the application of adaptive control techniques in various fields will be briefly discussed. Applications in various areas will be briefly reviewed. The use of adaptive techniques for vibrations monitoring and active vibration control will be emphasized.
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.
Error control of iterative linear solvers for integrated groundwater models.
Dixon, Matthew F; Bai, Zhaojun; Brush, Charles F; Chung, Francis I; Dogrul, Emin C; Kadir, Tariq N
2011-01-01
An open problem that arises when using modern iterative linear solvers, such as the preconditioned conjugate gradient method or Generalized Minimum RESidual (GMRES) method, is how to choose the residual tolerance in the linear solver to be consistent with the tolerance on the solution error. This problem is especially acute for integrated groundwater models, which are implicitly coupled to another model, such as surface water models, and resolve both multiple scales of flow and temporal interaction terms, giving rise to linear systems with variable scaling. This article uses the theory of "forward error bound estimation" to explain the correspondence between the residual error in the preconditioned linear system and the solution error. Using examples of linear systems from models developed by the US Geological Survey and the California State Department of Water Resources, we observe that this error bound guides the choice of a practical measure for controlling the error in linear systems. We implemented a preconditioned GMRES algorithm and benchmarked it against the Successive Over-Relaxation (SOR) method, the most widely known iterative solver for nonsymmetric coefficient matrices. With forward error control, GMRES can easily replace the SOR method in legacy groundwater modeling packages, resulting in the overall simulation speedups as large as 7.74×. This research is expected to broadly impact groundwater modelers through the demonstration of a practical and general approach for setting the residual tolerance in line with the solution error tolerance and presentation of GMRES performance benchmarking results.
Li, Le-Bao; Sun, Ling-Ling; Zhang, Sheng-Zhou; Yang, Qing-Quan
2015-09-01
A new control approach for speed tracking and synchronization of multiple motors is developed, by incorporating an adaptive sliding mode control (ASMC) technique into a ring coupling synchronization control structure. This control approach can stabilize speed tracking of each motor and synchronize its motion with other motors' motion so that speed tracking errors and synchronization errors converge to zero. Moreover, an adaptive law is exploited to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort and attenuate chattering. Performance comparisons with parallel control, relative coupling control and conventional PI control are investigated on a four-motor synchronization control system. Extensive simulation results show the effectiveness of the proposed control scheme.
Automatic Time Stepping with Global Error Control for Groundwater Flow Models
Tang, Guoping
2008-09-01
An automatic time stepping with global error control is proposed for the time integration of the diffusion equation to simulate groundwater flow in confined aquifers. The scheme is based on an a posteriori error estimate for the discontinuous Galerkin (dG) finite element methods. A stability factor is involved in the error estimate and it is used to adapt the time step and control the global temporal error for the backward difference method. The stability factor can be estimated by solving a dual problem. The stability factor is not sensitive to the accuracy of the dual solution and the overhead computational cost can be minimized by solving the dual problem using large time steps. Numerical experiments are conducted to show the application and the performance of the automatic time stepping scheme. Implementation of the scheme can lead to improvement in accuracy and efficiency for groundwater flow models.
Adaptive control based on retrospective cost optimization
NASA Astrophysics Data System (ADS)
Santillo, Mario A.
This dissertation studies adaptive control of multi-input, multi-output, linear, time-invariant, discrete-time systems that are possibly unstable and nonminimum phase. We consider both gradient-based adaptive control as well as retrospective-cost-based adaptive control. Retrospective cost optimization is a measure of performance at the current time based on a past window of data and without assumptions about the command or disturbance signals. In particular, retrospective cost optimization acts as an inner loop to the adaptive control algorithm by modifying the performance variables based on the difference between the actual past control inputs and the recomputed past control inputs based on the current control law. We develop adaptive control algorithms that are effective for systems that are nonminimum phase. We consider discrete-time adaptive control since these control laws can be implemented directly in embedded code without requiring an intermediate discretization step. Furthermore, the adaptive controllers in this dissertation are developed under minimal modeling assumptions. In particular, the adaptive controllers require knowledge of the sign of the high-frequency gain and a sufficient number of Markov parameters to approximate the nonminimum-phase zeros (if any). No additional modeling information is necessary. The adaptive controllers presented in this dissertation are developed for full-state-feedback stabilization, static-output-feedback stabilization, as well as dynamic compensation for stabilization, command following, disturbance rejection, and model reference adaptive control. Lyapunov-based stability and convergence proofs are provided for special cases. We present numerical examples to illustrate the algorithms' effectiveness in handling systems that are unstable and/or nonminimum phase and to provide insight into the modeling information required for controller implementation.
Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.
p-adaption for compressible flow problems using a goal-based error estimator
NASA Astrophysics Data System (ADS)
Ekelschot, Dirk; Moxey, David; Peiro, Joaquim; Sherwin, Spencer
2014-11-01
We present an approach of applying p-adaption to compressible flow problems using a dual-weighted error estimator. This technique has been implemented in the high-order h/p spectral element library Nektar + + . The compressible solver uses a high-order discontinuous Galerkin (DG) discretization. This approach is generally considered to be expensive and that is why the introduced p-adaption technique aims for lowering the computational cost while preserving the high-order accuracy and the exponential convergence properties. The numerical fluxes between the elements are discontinuous which allows one to use a different polynomial order in each element. After identifying and localizing the sources of error, the order of approximation of the solution within the element is improved. The solution to the adjoint equations for the compressible Euler equations is used to weigh the local residual of the primal solution. This provides both the error in the target quantity, which is typically the lift or drag coefficient, and an indication on how sensitive the local solution is to the target quantity. The dual-weighted error within each element serves then as a local refinement indicator that drives the p-adaptive algorithm. The performance of this p-adaptive method is demonstrated using a test case of subsonic flow past a 3D wing geometry.
The Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing
ERIC Educational Resources Information Center
Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi
2013-01-01
Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be "tailored" to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends…
Trial-to-trial adaptation in control of arm reaching and standing posture.
Pienciak-Siewert, Alison; Horan, Dylan P; Ahmed, Alaa A
2016-12-01
Classical theories of motor learning hypothesize that adaptation is driven by sensorimotor error; this is supported by studies of arm and eye movements that have shown that trial-to-trial adaptation increases with error. Studies of postural control have shown that anticipatory postural adjustments increase with the magnitude of a perturbation. However, differences in adaptation have been observed between the two modalities, possibly due to either the inherent instability or sensory uncertainty in standing posture. Therefore, we hypothesized that trial-to-trial adaptation in posture should be driven by error, similar to what is observed in arm reaching, but the nature of the relationship between error and adaptation may differ. Here we investigated trial-to-trial adaptation of arm reaching and postural control concurrently; subjects made reaching movements in a novel dynamic environment of varying strengths, while standing and holding the handle of a force-generating robotic arm. We found that error and adaptation increased with perturbation strength in both arm and posture. Furthermore, in both modalities, adaptation showed a significant correlation with error magnitude. Our results indicate that adaptation scales proportionally with error in the arm and near proportionally in posture. In posture only, adaptation was not sensitive to small error sizes, which were similar in size to errors experienced in unperturbed baseline movements due to inherent variability. This finding may be explained as an effect of uncertainty about the source of small errors. Our findings suggest that in rehabilitation, postural error size should be considered relative to the magnitude of inherent movement variability.
Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations
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
Adaptive neural network motion control of manipulators with experimental evaluations.
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.
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.
QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding
Razzaque, Mohammad Abdur; Javadi, Saeideh S.; Coulibaly, Yahaya; Hira, Muta Tah
2015-01-01
Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485
QOS-aware error recovery in wireless body sensor networks using adaptive network coding.
Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah
2014-12-29
Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.
Floating-point system quantization errors in digital control systems
NASA Technical Reports Server (NTRS)
Phillips, C. L.
1973-01-01
The results are reported of research into the effects on system operation of signal quantization in a digital control system. The investigation considered digital controllers (filters) operating in floating-point arithmetic in either open-loop or closed-loop systems. An error analysis technique is developed, and is implemented by a digital computer program that is based on a digital simulation of the system. As an output the program gives the programing form required for minimum system quantization errors (either maximum of rms errors), and the maximum and rms errors that appear in the system output for a given bit configuration. The program can be integrated into existing digital simulations of a system.
Developing control charts to review and monitor medication errors.
Ciminera, J L; Lease, M P
1992-03-01
There is a need to monitor reported medication errors in a hospital setting. Because the quantity of errors vary due to external reporting, quantifying the data is extremely difficult. Typically, these errors are reviewed using classification systems that often have wide variations in the numbers per class per month. The authors recommend the use of control charts to review historical data and to monitor future data. The procedure they have adopted is a modification of schemes using absolute (i.e., positive) values of successive differences to estimate the standard deviation when only single incidence values are available in time rather than sample averages, and when many successive differences may be zero.
Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Rohrs, C. E.
1982-01-01
Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.
Operator versus computer control of adaptive automation
NASA Technical Reports Server (NTRS)
Hilburn, Brian; Molloy, Robert; Wong, Dick; Parasuraman, Raja
1993-01-01
Adaptive automation refers to real-time allocation of functions between the human operator and automated subsystems. The article reports the results of a series of experiments whose aim is to examine the effects of adaptive automation on operator performance during multi-task flight simulation, and to provide an empirical basis for evaluations of different forms of adaptive logic. The combined results of these studies suggest several things. First, it appears that either excessively long, or excessively short, adaptation cycles can limit the effectiveness of adaptive automation in enhancing operator performance of both primary flight and monitoring tasks. Second, occasional brief reversions to manual control can counter some of the monitoring inefficiency typically associated with long cycle automation, and further, that benefits of such reversions can be sustained for some time after return to automated control. Third, no evidence was found that the benefits of such reversions depend on the adaptive logic by which long-cycle adaptive switches are triggered.
When soft controls get slippery: User interfaces and human error
Stubler, W.F.; O`Hara, J.M.
1998-12-01
Many types of products and systems that have traditionally featured physical control devices are now being designed with soft controls--input formats appearing on computer-based display devices and operated by a variety of input devices. A review of complex human-machine systems found that soft controls are particularly prone to some types of errors and may affect overall system performance and safety. This paper discusses the application of design approaches for reducing the likelihood of these errors and for enhancing usability, user satisfaction, and system performance and safety.
On the undetected error probability of a concatenated coding scheme for error control
NASA Technical Reports Server (NTRS)
Deng, H.; Costello, D. J., Jr.
1984-01-01
Consider a concatenated coding scheme for error control on a binary symmetric channel, called the inner channel. The bit error rate (BER) of the channel is correspondingly called the inner BER, and is denoted by Epsilon (sub i). Two linear block codes, C(sub f) and C(sub b), are used. The inner code C(sub f), called the frame code, is an (n,k) systematic binary block code with minimum distance, d(sub f). The frame code is designed to correct + or fewer errors and simultaneously detect gamma (gamma +) or fewer errors, where + + gamma + 1 = to or d(sub f). The outer code C(sub b) is either an (n(sub b), K(sub b)) binary block with a n(sub b) = mk, or an (n(sub b), k(Sub b) maximum distance separable (MDS) code with symbols from GF(q), where q = 2(b) and the code length n(sub b) satisfies n(sub)(b) = mk. The integerim is the number of frames. The outercode is designed for error detection only.
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.
NASA Astrophysics Data System (ADS)
Wang, Jun; Wang, Lei; Ikenaga, Takeshi; Goto, Satoshi
Transmission of compressed video over error prone channels may result in packet losses or errors, which can significantly degrade the image quality. Therefore an error concealment scheme is applied at the video receiver side to mask the damaged video. Considering there are 3 types of MBs (Macro Blocks) in natural video frame, i. e., Textural MB, Edged MB, and Smooth MB, this paper proposes an adaptive spatial error concealment which can choose 3 different methods for these 3 different MBs. For criteria of choosing appropriate method, 2 factors are taken into consideration. Firstly, standard deviation of our proposed edge statistical model is exploited. Secondly, some new features of latest video compression standard H.264/AVC, i. e., intra prediction mode is also considered for criterion formulation. Compared with previous works, which are only based on deterministic measurement, proposed method achieves the best image recovery. Subjective and objective image quality evaluations in experiments confirmed this.
Uchimura, Motoaki; Kitazawa, Shigeru
2013-04-24
Many previous studies have reported that our brains are able to encode a target position not only in body-centered coordinates but also in terms of landmarks in the background. The importance of such allocentric memory increases when we are forced to complete a delayed reaching task after the target has disappeared. However, the merit of allocentric memory in natural situations in which we are free to make an immediate reach toward a target has remained elusive. We hypothesized that allocentric memory is essential even in an immediate reach for dissociating between error attributable to the motor system and error attributable to target motion. We show here in humans that prism adaptation, that is, adaptation of reaching movements in response to errors attributable to displacement of the visual field, can be cancelled or enhanced simply by moving the background in mid-flight of the reaching movement. The results provide direct evidence for the novel contribution of allocentric memory in providing information on "where I intended to go," thereby discriminating the effect of target motion from the error resulting from the issued motor control signals.
Zero-error tracking control of uncertain nonlinear systems in the presence of actuator hysteresis
NASA Astrophysics Data System (ADS)
Zhang, Zhengqiang; Shen, Hao; Li, Ze; Zhang, Shuzhen
2015-11-01
In this paper, the problem of adaptive tracking control is addressed for a class of nonlinear systems with unknown constant parameters and unknown actuator nonlinearity. The actuator nonlinearity is modelled as the backlash-like hysteresis, which is described by a differential model. The prior knowledge on the control gain sign is not required, and only the assumption on the reference signal is made. By combining the adaptive backstepping technique with the Nussbaum gain approach, an adaptive compensation controller design approach is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop system are bounded, and the tracking error can converge to zero asymptotically despite the presence of the actuator hysteresis. Two simulation examples are included to illustrate the effectiveness of the proposed approach.
Servo control booster system for minimizing following error
Wise, W.L.
1979-07-26
A closed-loop feedback-controlled servo system is disclosed which reduces command-to-response error to the system's position feedback resolution least increment, ..delta..S/sub R/, on a continuous real-time basis, for all operational times of consequence and for all operating speeds. The servo system employs a second position feedback control loop on a by exception basis, when the command-to-response error greater than or equal to ..delta..S/sub R/, to produce precise position correction signals. When the command-to-response error is less than ..delta..S/sub R/, control automatically reverts to conventional control means as the second position feedback control loop is disconnected, becoming transparent to conventional servo control means. By operating the second unique position feedback control loop used herein at the appropriate clocking rate, command-to-response error may be reduced to the position feedback resolution least increment. The present system may be utilized in combination with a tachometer loop for increased stability.
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.
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.
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan
2009-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.
Error-Induced Learning as a Resource-Adaptive Process in Young and Elderly Individuals
NASA Astrophysics Data System (ADS)
Ferdinand, Nicola K.; Weiten, Anja; Mecklinger, Axel; Kray, Jutta
Thorndike described in his law of effect [44] that actions followed by positive events are more likely to be repeated in the future, whereas actions that are followed by negative outcomes are less likely to be repeated. This implies that behavior is evaluated in the light of its potential consequences, and non-reward events (i.e., errors) must be detected for reinforcement learning to take place. In short, humans have to monitor their performance in order to detect and correct errors, and this allows them to successfully adapt their behavior to changing environmental demands and acquire new behavior, i.e., to learn.
Reliability, Safety and Error Recovery for Advanced Control Software
NASA Technical Reports Server (NTRS)
Malin, Jane T.
2003-01-01
For long-duration automated operation of regenerative life support systems in space environments, there is a need for advanced integration and control systems that are significantly more reliable and safe, and that support error recovery and minimization of operational failures. This presentation outlines some challenges of hazardous space environments and complex system interactions that can lead to system accidents. It discusses approaches to hazard analysis and error recovery for control software and challenges of supporting effective intervention by safety software and the crew.
Design of an adaptive controller for a telerobot manipulator
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Zhou, Zhen-Lei
1989-01-01
The design of a joint-space adaptive control scheme is presented for controlling the slave arm motion of a dual-arm telerobot system developed at Goddard Space Flight Center (GSFC) to study telerobotic operations in space. Each slave arm of the dual-arm system is a kinematically redundant manipulator with 7 degrees of freedom (DOF). Using the concept of model reference adaptive control (MRAC) and Lyapunov direct method, an adatation algorithm is derived which adjusts the PD controller gains of the control scheme. The development of the adaptive control scheme assumes that the slave arm motion is non-compliant and slowly-varying. The implementation of the derived control scheme does not need the computation of the manipulator dynamics, which makes the control scheme sufficiently fast for real-time applications. Computer simulation study performed for the 7-DOF slave arm shows that the developed control scheme can efficiently adapt to sudden change in payloads while tracking various test trajectories such as ramp or sinusoids with negligible position errors.
Digital adaptive control laws for VTOL aircraft
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Stein, G.
1979-01-01
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). 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 and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
Li, Lebao; Sun, Lingling; Zhang, Shengzhou
2016-05-01
A new mean deviation coupling synchronization control strategy is developed for multiple motor control systems, which can guarantee the synchronization performance of multiple motor control systems and reduce complexity of the control structure with the increasing number of motors. The mean deviation coupling synchronization control architecture combining second-order adaptive sliding mode control (SOASMC) approach is proposed, which can improve synchronization control precision of multiple motor control systems and make speed tracking errors, mean speed errors of each motor and speed synchronization errors converge to zero rapidly. The proposed control scheme is robustness to parameter variations and random external disturbances and can alleviate the chattering phenomena. Moreover, an adaptive law is employed to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. Performance comparisons with master-slave control, relative coupling control, ring coupling control, conventional PI control and SMC are investigated on a four-motor synchronization control system. Extensive comparative results are given to shown the good performance of the proposed control scheme.
The adaptive control system of acetylene generator
NASA Astrophysics Data System (ADS)
Kovaliuk, D. O.; Kovaliuk, Oleg; Burlibay, Aron; Gromaszek, Konrad
2015-12-01
The method of acetylene production in acetylene generator was analyzed. It was found that impossible to provide the desired process characteristics by the PID-controller. The adaptive control system of acetylene generator was developed. The proposed system combines the classic controller and fuzzy subsystem for controller parameters tuning.
1983-03-01
AN ANALYSIS OF A FINITE ELEMENT METHOD FOR CONVECTION- DIFFUSION PROBLEMS PART II: A POSTERIORI ERROR ESTIMATES AND ADAPTIVITY by W. G. Szymczak Y 6a...PERIOD COVERED AN ANALYSIS OF A FINITE ELEMENT METHOD FOR final life of the contract CONVECTION- DIFFUSION PROBLEM S. Part II: A POSTERIORI ERROR ...Element Method for Convection- Diffusion Problems. Part II: A Posteriori Error Estimates and Adaptivity W. G. Szvmczak and I. Babu~ka# Laboratory for
Wireless Control of an LC Adaptive Lens
NASA Astrophysics Data System (ADS)
Vdovin, G.; Loktev, M.; Zhang, X.
We consider using liquid crystal adaptive lenses to correct the accommodation loss and higher-order aberrations of the human eye. In this configuration, the adaptive lens is embedded into the eye lens implant and can be controlled through a wireless inductive link. In this work we experimentally demonstrate a wireless control of a liquid crystal adaptive lens in a wide range of its focusing power by using two coupled coils with the primary coil driven from a low-voltage source through a switching control circuit and the secondary coil used to drive the lens.
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.
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.
Adaptive nonlinear control for autonomous ground vehicles
NASA Astrophysics Data System (ADS)
Black, William S.
We present the background and motivation for ground vehicle autonomy, and focus on uses for space-exploration. Using a simple design example of an autonomous ground vehicle we derive the equations of motion. After providing the mathematical background for nonlinear systems and control we present two common methods for exactly linearizing nonlinear systems, feedback linearization and backstepping. We use these in combination with three adaptive control methods: model reference adaptive control, adaptive sliding mode control, and extremum-seeking model reference adaptive control. We show the performances of each combination through several simulation results. We then consider disturbances in the system, and design nonlinear disturbance observers for both single-input-single-output and multi-input-multi-output systems. Finally, we show the performance of these observers with simulation results.
Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang
2015-01-01
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. PMID:25815450
Artificial neural network implementation of a near-ideal error prediction controller
NASA Technical Reports Server (NTRS)
Mcvey, Eugene S.; Taylor, Lynore Denise
1992-01-01
A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error
Floating-point system quantization errors in digital control systems
NASA Technical Reports Server (NTRS)
Phillips, C. L.; Vallely, D. P.
1978-01-01
This paper considers digital controllers (filters) operating in floating-point arithmetic in either open-loop or closed-loop systems. A quantization error analysis technique is developed, and is implemented by a digital computer program that is based on a digital simulation of the system. The program can be integrated into existing digital simulations of a system.
Adaptive Current Control Method for Hybrid Active Power Filter
NASA Astrophysics Data System (ADS)
Chau, Minh Thuyen
2016-09-01
This paper proposes an adaptive current control method for Hybrid Active Power Filter (HAPF). It consists of a fuzzy-neural controller, identification and prediction model and cost function. The fuzzy-neural controller parameters are adjusted according to the cost function minimum criteria. For this reason, the proposed control method has a capability on-line control clings to variation of the load harmonic currents. Compared to the single fuzzy logic control method, the proposed control method shows the advantages of better dynamic response, compensation error in steady-state is smaller, able to online control is better and harmonics cancelling is more effective. Simulation and experimental results have demonstrated the effectiveness of the proposed control method.
Adaptive control for payload launch vibration isolation
NASA Astrophysics Data System (ADS)
Jarosh, Julian R.; Agnes, Gregory S.; Karahalis, Gregory G.
2001-07-01
The Department of Defense has identified launch vibration isolation as a major research interest. Reducing the loads a satellite experiences during launch will greatly enhance the reliability and lifetime and decrease the payload structural mass. DoD space programs stand to benefit significantly from advances in vibration isolation technology. This study explores potential hybrid vibration isolation using adaptive control with a passive isolator. Lyapunov analysis is used to develop the structural adaptive control scheme. Simulink and Matlab simulations investigate these control methodologies on a lumped mass dynamic model of a satellite and its representative launch vehicle. The results are compared to Proportional-Integral-Derivative (PID) control and skyhook damper active control methods. The results of the modeling indicate adaptive control achieves up to a 90 percent reduction in loads on the payload when compared to the conventional active control methods. The adaptive controller compensated for the loads being transmitted to the payload from the rest of the launch vehicle. The current adaptive controller was not able to effectively control the motion of a vibrating subcomponent within the payload or the subcomponent's effect on the overall payload itself.
Continuous quantum error correction as classical hybrid control
NASA Astrophysics Data System (ADS)
Mabuchi, Hideo
2009-10-01
The standard formulation of quantum error correction (QEC) comprises repeated cycles of error estimation and corrective intervention in the free dynamics of a qubit register. QEC can thus be seen as a form of feedback control, and it is of interest to seek a deeper understanding of the connection between the associated theories. Here we present a focused case study within this broad program, connecting continuous QEC with elements of hybrid control theory. We show that canonical methods of the latter engineering discipline, such as recursive filtering and dynamic programming approaches to solving the optimal control problem, can be applied fruitfully in the design of separated controller structures for quantum memories based on coding and continuous syndrome measurement.
Self-Tuning Adaptive-Controller Using Online Frequency Identification
NASA Technical Reports Server (NTRS)
Chiang, W. W.; Cannon, R. H., Jr.
1985-01-01
A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.
Adaptive resonator control techniques for high-power lasers
Freeman, R.H.; Spinhirne, J.M.; Anafi, D.
1981-01-01
Experimental results and interpretations for correcting tilt and astigmatism aberrations using intracavity adaptive optics versus extracavity adaptive optics are presented, along with control algorithm and resonator design considerations when utilizing a multidither COAT control system for astigmatism and tilt correction. It is shown that in a high-power device, PIB (Power-in-the-Bucket) optimization, with the possible added requirement of extracavity beam clean-up to achieve good beam quality, would be a more desirable control algorithm than BQ (beam quality) optimization. Zonal multidither hill-climbing servo COAT techniques applied to tilt correction fail to achieve good correction for large tilt amplitudes when the control loop is closed after tilt is introduced. Therefore, it is suggested that a separate tilt sensor be used to provide error signal for correction of tilt and let the multidither system COAT correct for higher order aberrations
Optimal Control Modification Adaptive Law for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
On Fractional Model Reference Adaptive Control
Shi, Bao; 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
A spatial explicit strategy reduces error but interferes with sensorimotor adaptation
Benson, Bryan L.; Anguera, Joaquin A.
2011-01-01
Although sensorimotor adaptation is typically thought of as an implicit form of learning, it has been shown that participants who gain explicit awareness of the nature of the perturbation during adaptation exhibit more learning than those who do not. With rare exceptions, however, explicit awareness is typically polled at the end of the study. Here, we provided participants with either an explicit spatial strategy or no instructions before learning. Early in learning, explicit instructions greatly reduced movement errors but also resulted in increased trial-to-trial variability and longer reaction times. Late in adaptation, performance was indistinguishable between the explicit and implicit groups, but the mechanisms underlying performance improvements remained fundamentally different, as revealed by catch trials. The progression of implicit recalibration in the explicit group was modulated by the use of an explicit strategy: these participants showed a lower level of recalibration as well as decreased aftereffects. This phenomenon may be due to the reduced magnitude of errors made to the target during adaptation or inhibition of implicit learning mechanisms by explicit processing. PMID:21451054
A new adaptive configuration of PID type fuzzy logic controller.
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.
On-sky demonstration of optimal control for adaptive optics at Palomar Observatory.
Tesch, Jonathan; Truong, Tuan; Burruss, Rick; Gibson, Steve
2015-04-01
High-order adaptive optics systems often suffer from significant computational latency, which ultimately limits the temporal error rejection bandwidth when classical controllers are employed. This Letter presents results from an on-sky, real-time implementation of an optimal controller on the PALM-3000 adaptive optics system at Palomar Observatory. The optimal controller is computed directly from open-loop wavefront measurements using a multichannel subspace system identification algorithm, and mitigates latency by explicitly predicting incident turbulence. Experimental results show a significant reduction in the residual wavefront error over the controlled spatial modes, illustrating the superior performance of the optimal control approach versus the nominal integral control architecture.
Adaptive Control Techniques for Large Space Structures.
1986-09-15
Adaptive Systems: A Ji . Fixed-Point Analysis", submitted, IEEE Trans. on Circuits and Systems; Special Issue on Adaptive Systems, Sept. 1987. I.M.Y...Shaped Cost Functionals: Extensions of LQG Methods," *.. AIAA J. of Guidance and Control, pp. 529-535, Nov-Dec. 1980. [81 C.A. Desoer , R.W. Liu, J. Murray...for Parameter Conver- gence in Adaptive Control," Memo No. UCB/ERL M84/25, Univ. of California, Berke- ley, 1984. [19] C.A. Desoer and M. Vidyasagar
Model-adaptive hybrid dynamic control for robotic assembly tasks
Austin, D.J.; McCarragher, B.J.
1999-10-01
A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.
Controlling type-1 error rates in whole effluent toxicity testing
Smith, R.; Johnson, S.C.
1995-12-31
A form of variability, called the dose x test interaction, has been found to affect the variability of the mean differences from control in the statistical tests used to evaluate Whole Effluent Toxicity Tests for compliance purposes. Since the dose x test interaction is not included in these statistical tests, the assumed type-1 and type-2 error rates can be incorrect. The accepted type-1 error rate for these tests is 5%. Analysis of over 100 Ceriodaphnia, fathead minnow and sea urchin fertilization tests showed that when the test x dose interaction term was not included in the calculations the type-1 error rate was inflated to as high as 20%. In a compliance setting, this problem may lead to incorrect regulatory decisions. Statistical tests are proposed that properly incorporate the dose x test interaction variance.
Adaptive PID control based on orthogonal endocrine neural networks.
Milovanović, Miroslav B; Antić, Dragan S; Milojković, Marko T; Nikolić, Saša S; Perić, Staniša Lj; Spasić, Miodrag D
2016-12-01
A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev orthogonal polynomials. First substructure network is a regular orthogonal neural network with implemented artificial endocrine factor (OENN), in the form of environmental stimuli, to its weights. It is used for approximation of control signals and for processing system deviation/disturbance signals which are introduced in the form of environmental stimuli. The output values of OENN are used to calculate artificial environmental stimuli (AES), which represent required adaptation measure of a second network-orthogonal endocrine adaptive neuro-fuzzy inference system (OEANFIS). OEANFIS is used to process control, output and error signals of a system and to generate adjustable values of proportional, derivative, and integral parameters, used for online tuning of a PID controller. The developed structure is experimentally tested on a laboratory model of the 3D crane system in terms of analysing tracking performances and deviation signals (error signals) of a payload. OENN-OEANFIS performances are compared with traditional PID and 6 intelligent PID type controllers. Tracking performance comparisons (in transient and steady-state period) showed that the proposed adaptive controller possesses performances within the range of other tested controllers. The main contribution of OENN-OEANFIS structure is significant minimization of deviation signals (17%-79%) compared to other controllers. It is recommended to exploit it when dealing with a highly nonlinear system which operates in the presence of undesirable disturbances.
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.
Attitude-Control Algorithm for Minimizing Maneuver Execution Errors
NASA Technical Reports Server (NTRS)
Acikmese, Behcet
2008-01-01
A G-RAC attitude-control algorithm is used to minimize maneuver execution error in a spacecraft with a flexible appendage when said spacecraft must induce translational momentum by firing (in open loop) large thrusters along a desired direction for a given period of time. The controller is dynamic with two integrators and requires measurement of only the angular position and velocity of the spacecraft. The global stability of the closed-loop system is guaranteed without having access to the states describing the dynamics of the appendage and with severe saturation in the available torque. Spacecraft apply open-loop thruster firings to induce a desired translational momentum with an extended appendage. This control algorithm will assist this maneuver by stabilizing the attitude dynamics around a desired orientation, and consequently minimize the maneuver execution errors.
Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems.
Wang, Wei; Tong, Shaocheng
2017-01-10
This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains. To realize smooth and fast learning, a predictor is introduced to estimate each error surface, and the corresponding predictor error is employed to learn the optimal fuzzy parameter vector. It is proved that the developed adaptive fuzzy control scheme guarantees the uniformly ultimate boundedness of the closed-loop systems, and the tracking error converges to a small neighborhood of the origin. The simulation results and comparisons are provided to show the validity of the control strategy presented in this paper.
An adaptive error modeling scheme for the lossless compression of EEG signals.
Sriraam, N; Eswaran, C
2008-09-01
Lossless compression of EEG signal is of great importance for the neurological diagnosis as the specialists consider the exact reconstruction of the signal as a primary requirement. This paper discusses a lossless compression scheme for EEG signals that involves a predictor and an adaptive error modeling technique. The prediction residues are arranged based on the error count through an histogram computation. Two optimal regions are identified in the histogram plot through a heuristic search such that the bit requirement for encoding the two regions is minimum. Further improvement in the compression is achieved by removing the statistical redundancy that is present in the residue signal by using a context-based bias cancellation scheme. Three neural network predictors, namely, single-layer perceptron, multilayer perceptron, and Elman network and two linear predictors, namely, autoregressive model and finite impulse response filter are considered. Experiments are conducted using EEG signals recorded under different physiological conditions and the performances of the proposed methods are evaluated in terms of the compression ratio. It is shown that the proposed adaptive error modeling schemes yield better compression results compared to other known compression methods.
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.
NASA Astrophysics Data System (ADS)
Patru, Fabien; Esposito, Simone; Puglisi, Alfio; Riccardi, Armando; Pinna, Enrico; Arcidiacono, Carmelo; Hill, John; Hinz, Philip
2016-08-01
On-sky adaptive optics wavefront screens have been used and random optical path fluctuations - differential pistons - have been included in numerical simulations for the Large Binocular Telescope Interferometer. We characterize the Point Spread Function (PSF) and the Optical Transfer Function (OTF) by computing respectively the interferometric Strehl and the visibility criteria. We study the contribution of the wavefront disturbance induced by each adaptive optics system and by the optical path difference between the arms of the LBTI. To provide an image of quality (Strehl above 70%) suitable with standard science cases , the requirements for a LBTI mode in the visible wavelengths (750nm) must be at least an adaptive optics wavefront RMS fluctuations below λ/18≍40nm (Strehl above 90%) provided by each adaptive optics system, and a differential piston RMS fluctuations below λ/8≍100nm in the overall LBTI system. The adaptive optics wavefront errors - mainly the differential tip-tilt - appear to be more critical than the differential piston.
Using brain potentials to understand prism adaptation: the error-related negativity and the P300
MacLean, Stephane J.; Hassall, Cameron D.; Ishigami, Yoko; Krigolson, Olav E.; Eskes, Gail A.
2015-01-01
Prism adaptation (PA) is both a perceptual-motor learning task as well as a promising rehabilitation tool for visuo-spatial neglect (VSN)—a spatial attention disorder often experienced after stroke resulting in slowed and/or inaccurate motor responses to contralesional targets. During PA, individuals are exposed to prism-induced shifts of the visual-field while performing a visuo-guided reaching task. After adaptation, with goggles removed, visuomotor responding is shifted to the opposite direction of that initially induced by the prisms. This visuomotor aftereffect has been used to study visuomotor learning and adaptation and has been applied clinically to reduce VSN severity by improving motor responding to stimuli in contralesional (usually left-sided) space. In order to optimize PA's use for VSN patients, it is important to elucidate the neural and cognitive processes that alter visuomotor function during PA. In the present study, healthy young adults underwent PA while event-related potentials (ERPs) were recorded at the termination of each reach (screen-touch), then binned according to accuracy (hit vs. miss) and phase of exposure block (early, middle, late). Results show that two ERP components were evoked by screen-touch: an error-related negativity (ERN), and a P300. The ERN was consistently evoked on miss trials during adaptation, while the P300 amplitude was largest during the early phase of adaptation for both hit and miss trials. This study provides evidence of two neural signals sensitive to visual feedback during PA that may sub-serve changes in visuomotor responding. Prior ERP research suggests that the ERN reflects an error processing system in medial-frontal cortex, while the P300 is suggested to reflect a system for context updating and learning. Future research is needed to elucidate the role of these ERP components in improving visuomotor responses among individuals with VSN. PMID:26124715
Language control in bilinguals: The adaptive control hypothesis.
Green, David W; Abutalebi, Jubin
2013-08-01
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.
Language control in bilinguals: The adaptive control hypothesis
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
Maritime Adaptive Optics Beam Control
2010-09-01
can employ enclosures, silencers, or mass-spring- damper systems, active noise control employs secondary sources, usually electronic, to produce a...a Fourier filter in the form of an iris or aperture stop is placed in the beam to select either the +1 or -1 diffractive order to propagate through
An adaptive pattern based nonlinear PID controller.
Segovia, Juan Pablo; Sbarbaro, Daniel; Ceballos, Eric
2004-04-01
This paper presents a nonlinear proportional-integral-derivative (PID) controller, combining a pattern based adaptive algorithm to cope with the problem of tuning the controller, and an associative memory to store the parameters, according to different operating conditions. The simplicity of the algorithm enables its implementation in current programmable logic controller technology. Several real-time experiments, carried out in a pressurized tank, illustrate the performance of the proposed controller.
Coordinated joint motion control system with position error correction
Danko, George
2011-11-22
Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two-joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.
Coordinated joint motion control system with position error correction
Danko, George L.
2016-04-05
Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.
Adaptive measurement control for calorimetric assay
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.
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1991-01-01
Research activities related to error control techniques for satellite and space communication are reported. Specific areas of research include: coding gains for bandwidth efficient codes, hardware implementation of a bandwidth efficient coding scheme for the Hubble Space Telescope, construction of long trellis codes for use with sequential decoding, performance analysis of multilevel trellis codes, and M-algorithm decoding of trellis codes. Each topic is discussed in a corresponding paper that appears in the appendices.
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.
Dual adaptive control: Design principles and applications
NASA Technical Reports Server (NTRS)
Mookerjee, Purusottam
1988-01-01
The design of an actively adaptive dual controller based on an approximation of the stochastic dynamic programming equation for a multi-step horizon is presented. A dual controller that can enhance identification of the system while controlling it at the same time is derived for multi-dimensional problems. This dual controller uses sensitivity functions of the expected future cost with respect to the parameter uncertainties. A passively adaptive cautious controller and the actively adaptive dual controller are examined. In many instances, the cautious controller is seen to turn off while the latter avoids the turn-off of the control and the slow convergence of the parameter estimates, characteristic of the cautious controller. The algorithms have been applied to a multi-variable static model which represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. Monte Carlo comparisons based on parametric and nonparametric statistical analysis indicate the superiority of the dual controller over the baseline controller.
Adaptive Neural Network Controller for ATM Traffic
1996-12-01
IEEE Communications Magazine (October 1995). 2. Baum, Eric B...Adaptive Control in ATM Networks," IEEE Communications Magazine (October 1995). 9. Evanowsky, John B. "Information for the Warrior," IEEE Communications Magazine (October...Network Applications in ATM," IEEE Communications Magazine (October 1995). 78 16. Imrich, et al. "A counter based congestion control for ATM
Multiprocessor Adaptive Control Of A Dynamic System
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Hyland, David C.
1995-01-01
Architecture for fully autonomous digital electronic control system developed for use in identification and adaptive control of dynamic system. Architecture modular and hierarchical. Combines relatively simple, standardized processing units into complex parallel-processing subsystems. Although architecture based on neural-network concept, processing units themselves not neural networks; processing units implemented by programming of currently available microprocessors.
Unequal error control scheme for dimmable visible light communication systems
NASA Astrophysics Data System (ADS)
Deng, Keyan; Yuan, Lei; Wan, Yi; Li, Huaan
2017-01-01
Visible light communication (VLC), which has the advantages of a very large bandwidth, high security, and freedom from license-related restrictions and electromagnetic-interference, has attracted much interest. Because a VLC system simultaneously performs illumination and communication functions, dimming control, efficiency, and reliable transmission are significant and challenging issues of such systems. In this paper, we propose a novel unequal error control (UEC) scheme in which expanding window fountain (EWF) codes in an on-off keying (OOK)-based VLC system are used to support different dimming target values. To evaluate the performance of the scheme for various dimming target values, we apply it to H.264 scalable video coding bitstreams in a VLC system. The results of the simulations that are performed using additive white Gaussian noises (AWGNs) with different signal-to-noise ratios (SNRs) are used to compare the performance of the proposed scheme for various dimming target values. It is found that the proposed UEC scheme enables earlier base layer recovery compared to the use of the equal error control (EEC) scheme for different dimming target values and therefore afford robust transmission for scalable video multicast over optical wireless channels. This is because of the unequal error protection (UEP) and unequal recovery time (URT) of the EWF code in the proposed scheme.
Adaptive Process Control in Rubber Industry.
Brause, Rüdiger W; Pietruschka, Ulf
1998-01-01
This paper describes the problems and an adaptive solution for process control in rubber industry. We show that the human and economical benefits of an adaptive solution for the approximation of process parameters are very attractive. The modeling of the industrial problem is done by the means of artificial neural networks. For the example of the extrusion of a rubber profile in tire production our method shows good resuits even using only a few training samples.
Ordering genes: controlling the decision-error probabilities.
Rogatko, A; Zacks, S
1993-01-01
Determination of the relative gene order on chromosomes is of critical importance in the construction of human gene maps. In this paper we develop a sequential algorithm for gene ordering. We start by comparing three sequential procedures to order three genes on the basis of Bayesian posterior probabilities, maximum-likelihood ratio, and minimal recombinant class. In the second part of the paper we extend sequential procedure based on the posterior probabilities to the general case of g genes. We present a theorem that states that the predicted average probability of committing a decision error, associated with a Bayesian sequential procedure that accepts the hypothesis of a gene-order configuration with posterior probability equal to or greater than pi *, is smaller than 1 - pi *. This theorem holds irrespective of the number of genes, the genetic model, and the source of genetic information. The theorem is an extension of a classical result of Wald, concerning the sum of the actual and the nominal error probabilities in the sequential probability ratio test of two hypotheses. A stepwise strategy for ordering a large number of genes, with control over the decision-error probabilities, is discussed. An asymptotic approximation is provided, which facilitates the calculations with existing computer software for gene mapping, of the posterior probabilities of an order and the error probabilities. We illustrate with some simulations that the stepwise ordering is an efficient procedure. PMID:8488844
Robinson, Michael D; Moeller, Sara K; Fetterman, Adam K
2010-10-01
Responsiveness to negative feedback has been seen as functional by those who emphasize the value of reflecting on such feedback in self-regulating problematic behaviors. On the other hand, the very same responsiveness has been viewed as dysfunctional by its link to punishment sensitivity and reactivity. The present 4 studies, involving 203 undergraduate participants, sought to reconcile such discrepant views in the context of the trait of neuroticism. In cognitive tasks, individuals were given error feedback when they made mistakes. It was found that greater tendencies to slow down following error feedback were associated with higher levels of accuracy at low levels of neuroticism but lower levels of accuracy at high levels of neuroticism. Individual differences in neuroticism thus appear crucial in understanding whether behavioral alterations following negative feedback reflect proactive versus reactive mechanisms and processes. Implications for understanding the processing basis of neuroticism and adaptive self-regulation are discussed.
High speed and adaptable error correction for megabit/s rate quantum key distribution
Dixon, A. R.; Sato, H.
2014-01-01
Quantum Key Distribution is moving from its theoretical foundation of unconditional security to rapidly approaching real world installations. A significant part of this move is the orders of magnitude increases in the rate at which secure key bits are distributed. However, these advances have mostly been confined to the physical hardware stage of QKD, with software post-processing often being unable to support the high raw bit rates. In a complete implementation this leads to a bottleneck limiting the final secure key rate of the system unnecessarily. Here we report details of equally high rate error correction which is further adaptable to maximise the secure key rate under a range of different operating conditions. The error correction is implemented both in CPU and GPU using a bi-directional LDPC approach and can provide 90–94% of the ideal secure key rate over all fibre distances from 0–80 km. PMID:25450416
NASA Astrophysics Data System (ADS)
Gil-Leyva, Diego; Robertson, Brian; Wilkinson, Timothy D.; Henderson, Charley J.
2006-06-01
Aberration correction within a free-space optical interconnect based on a spatial light modulator for beam steering and holographic wavefront correction is presented. The wavefront sensing technique is based on an extension of a modal wavefront sensor described by Neil et al. [J. Opt. Soc. Am. A 17, 1098 (2000)], which uses a diffractive element. In this analysis such a wavefront sensor is adapted with an error diffusion algorithm that yields a low reconstruction error and fast reconfigurability. Improvement of the beam propagation quality (Strehl ratio) for different channels across the input plane is achieved. However, due to the space invariancy of the system, a trade-off among the beam propagation quality for channels is obtained. Experimental results are presented and discussed.
High speed and adaptable error correction for megabit/s rate quantum key distribution.
Dixon, A R; Sato, H
2014-12-02
Quantum Key Distribution is moving from its theoretical foundation of unconditional security to rapidly approaching real world installations. A significant part of this move is the orders of magnitude increases in the rate at which secure key bits are distributed. However, these advances have mostly been confined to the physical hardware stage of QKD, with software post-processing often being unable to support the high raw bit rates. In a complete implementation this leads to a bottleneck limiting the final secure key rate of the system unnecessarily. Here we report details of equally high rate error correction which is further adaptable to maximise the secure key rate under a range of different operating conditions. The error correction is implemented both in CPU and GPU using a bi-directional LDPC approach and can provide 90-94% of the ideal secure key rate over all fibre distances from 0-80 km.
Kiyko, V V; Kislov, V I; Ofitserov, E N
2015-08-31
In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)
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.
Tracking post-error adaptation in the motor system by transcranial magnetic stimulation.
Amengual, J L; Marco-Pallarés, J; Richter, L; Oung, S; Schweikard, A; Mohammadi, B; Rodríguez-Fornells, A; Münte, T F
2013-10-10
The commission of an error triggers cognitive control processes dedicated to error correction and prevention. Post-error adjustments leading to response slowing following an error ("post-error slowing"; PES) might be driven by changes in excitability of the motor regions and the corticospinal tract (CST). The time-course of such excitability modulations of the CST leading to PES is largely unknown. To track these presumed excitability changes after an error, single pulse transcranial magnetic stimulation (TMS) was applied to the motor cortex ipsilateral to the responding hand, while participants were performing an Eriksen flanker task. A robotic arm with a movement compensation system was used to maintain the TMS coil in the correct position during the experiment. Magnetic pulses were delivered over the primary motor cortex ipsilateral to the active hand at different intervals (150, 300, 450 ms) after correct and erroneous responses, and the motor-evoked potentials (MEP) of the first dorsal interosseous muscle (FDI) contralateral to the stimulated hemisphere were recorded. MEP amplitude was increased 450 ms after the error. Two additional experiments showed that this increase was neither associated to the correction of the erroneous responses nor to the characteristics of the motor command. To the extent to which the excitability of the motor cortex ipsi- and contralateral to the response hand are inversely related, these results suggest a decrease in the excitability of the active motor cortex after an erroneous response. This modulation of the activity of the CST serves to prevent further premature and erroneous responses. At a more general level, the study shows the power of the TMS technique for the exploration of the temporal evolution of post-error adjustments within the motor system.
Robust Adaptive Control of Hypnosis During Anesthesia
2007-11-02
1 of 4 ROBUST ADAPTIVE CONTROL OF HYPNOSIS DURING ANESTHESIA Pascal Grieder1, Andrea Gentilini1, Manfred Morari1, Thomas W. Schnider2 1ETH Zentrum...A closed-loop controller for hypnosis was designed and validated on humans at our laboratory. The controller aims at regulat- ing the Bispectral Index...BIS) - a surro- gate measure of hypnosis derived from the electroencephalogram of the patient - with the volatile anesthetic isoflurane administered
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.
Jakeman, J. D.; Wildey, T.
2015-01-01
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity. We show that utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this papermore » we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.« less
Jakeman, J. D.; Wildey, T.
2015-01-01
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity. We show that utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.
Logan, Dustin M; Hill, Kyle R; Larson, Michael J
2015-01-01
Poor awareness has been linked to worse recovery and rehabilitation outcomes following moderate-to-severe traumatic brain injury (M/S TBI). The error positivity (Pe) component of the event-related potential (ERP) is linked to error awareness and cognitive control. Participants included 37 neurologically healthy controls and 24 individuals with M/S TBI who completed a brief neuropsychological battery and the error awareness task (EAT), a modified Stroop go/no-go task that elicits aware and unaware errors. Analyses compared between-group no-go accuracy (including accuracy between the first and second halves of the task to measure attention and fatigue), error awareness performance, and Pe amplitude by level of awareness. The M/S TBI group decreased in accuracy and maintained error awareness over time; control participants improved both accuracy and error awareness during the course of the task. Pe amplitude was larger for aware than unaware errors for both groups; however, consistent with previous research on the Pe and TBI, there were no significant between-group differences for Pe amplitudes. Findings suggest possible attention difficulties and low improvement of performance over time may influence specific aspects of error awareness in M/S TBI.
Logan, Dustin M.; Hill, Kyle R.; Larson, Michael J.
2015-01-01
Poor awareness has been linked to worse recovery and rehabilitation outcomes following moderate-to-severe traumatic brain injury (M/S TBI). The error positivity (Pe) component of the event-related potential (ERP) is linked to error awareness and cognitive control. Participants included 37 neurologically healthy controls and 24 individuals with M/S TBI who completed a brief neuropsychological battery and the error awareness task (EAT), a modified Stroop go/no-go task that elicits aware and unaware errors. Analyses compared between-group no-go accuracy (including accuracy between the first and second halves of the task to measure attention and fatigue), error awareness performance, and Pe amplitude by level of awareness. The M/S TBI group decreased in accuracy and maintained error awareness over time; control participants improved both accuracy and error awareness during the course of the task. Pe amplitude was larger for aware than unaware errors for both groups; however, consistent with previous research on the Pe and TBI, there were no significant between-group differences for Pe amplitudes. Findings suggest possible attention difficulties and low improvement of performance over time may influence specific aspects of error awareness in M/S TBI. PMID:26217212
Adaptive control of an unmanned aerial vehicle
NASA Astrophysics Data System (ADS)
Nguen, V. F.; Putov, A. V.; Nguen, T. T.
2017-01-01
The paper deals with design and comparison of adaptive control systems based on plant state vector and output for unmanned aerial vehicle (UAV) with nonlinearity and uncertainty of parameters of the aircraft incomplete measurability of its state and presence of wind disturbances. The results of computer simulations of flight stabilization processes on the example of the experimental model UAV-70V (Aerospace Academy, Hanoi) with presence of periodic and non-periodic vertical wind disturbances with designed adaptive control systems based on plant state vector with state observer and plant output.
Hardware verification of distributed/adaptive control
NASA Technical Reports Server (NTRS)
Eldred, D. B.; Schaechter, D. B.
1983-01-01
Adaptive control techniques are studied for their future application to the control of large space structures, where uncertain or changing parameters may destabilize standard control system designs. The approach used is to examine an extended Kalman filter estimator, in which the state vector is augmented with the unknown parameters. The associated Riccatti equation is linearized about the case of exact knowledge of the parameters. By assuming that parameter variations occur slowly, the filter complexity is reduced further yet. Simulations on a two degree-of-freedom oscillator demonstrate the parameter-tracking capability of the filter, and an implementation on the JPL Flexible Beam Facility using an incorrect model shows the adaptive filter/optimal control to be stable where a standard Kalman filter/optimal control design is unstable.
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
Integration of auditory and somatosensory error signals in the neural control of speech movements.
Feng, Yongqiang; Gracco, Vincent L; Max, Ludo
2011-08-01
We investigated auditory and somatosensory feedback contributions to the neural control of speech. In task I, sensorimotor adaptation was studied by perturbing one of these sensory modalities or both modalities simultaneously. The first formant (F1) frequency in the auditory feedback was shifted up by a real-time processor and/or the extent of jaw opening was increased or decreased with a force field applied by a robotic device. All eight subjects lowered F1 to compensate for the up-shifted F1 in the feedback signal regardless of whether or not the jaw was perturbed. Adaptive changes in subjects' acoustic output resulted from adjustments in articulatory movements of the jaw or tongue. Adaptation in jaw opening extent in response to the mechanical perturbation occurred only when no auditory feedback perturbation was applied or when the direction of adaptation to the force was compatible with the direction of adaptation to a simultaneous acoustic perturbation. In tasks II and III, subjects' auditory and somatosensory precision and accuracy were estimated. Correlation analyses showed that the relationships 1) between F1 adaptation extent and auditory acuity for F1 and 2) between jaw position adaptation extent and somatosensory acuity for jaw position were weak and statistically not significant. Taken together, the combined findings from this work suggest that, in speech production, sensorimotor adaptation updates the underlying control mechanisms in such a way that the planning of vowel-related articulatory movements takes into account a complex integration of error signals from previous trials but likely with a dominant role for the auditory modality.
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.
Real Time & Power Efficient Adaptive - Robust Control
NASA Astrophysics Data System (ADS)
Ioan Gliga, Lavinius; Constantin Mihai, Cosmin; Lupu, Ciprian; Popescu, Dumitru
2017-01-01
A design procedure for a control system suited for dynamic variable processes is presented in this paper. The proposed adaptive - robust control strategy considers both adaptive control advantages and robust control benefits. It estimates the degradation of the system’s performances due to the dynamic variation in the process and it then utilizes it to determine when the system must be adapted with a redesign of the robust controller. A single integral criterion is used for the identification of the process, and for the design of the control algorithm, which is expressed in direct form, through a cost function defined in the space of the parameters of both the process and the controller. For the minimization of this nonlinear function, an adequate mathematical programming minimization method is used. The theoretical approach presented in this paper was validated for a closed loop control system, simulated in an application developed in C. Because of the reduced number of operations, this method is suitable for implementation on fast processes. Due to its effectiveness, it increases the idle time of the CPU, thereby saving electrical energy.
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.
Tahoun, A H
2017-01-01
In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers.
Adaptive Control of Nonlinear and Stochastic Systems
1991-01-14
Hernmndez-Lerma and S.I. Marcus, Nonparametric adaptive control of dis- crete time partially observable stochastic systems, Journal of Mathematical Analysis and Applications 137... Journal of Mathematical Analysis and Applications 137 (1989), 485-514. [19] A. Arapostathis and S.I. Marcus, Analysis of an identification algorithm
Adaptive control system for gas producing wells
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.
Geometric quantum gates that are robust against stochastic control errors
Zhu Shiliang; Zanardi, Paolo
2005-08-15
The realistic application of geometric quantum computation is crucially dependent on an unproved robustness conjecture, claiming that geometric quantum gates are more resilient against random noise than dynamic gates. We propose a suitable model that allows a direct and fair comparison between geometrical and dynamical operations. In the presence of stochastic control errors we find that the maximum of gate fidelity corresponds to quantum gates with a vanishing dynamical phase. This is a clear evidence for the robustness of nonadiabatic geometric quantum computation. The predictions here presented can be experimentally tested in almost all of the already existing quantum computer candidates.
NASA Astrophysics Data System (ADS)
Bakri, F. A.; Mashor, M. Y.; Sharun, S. M.; Bibi Sarpinah, S. N.; Abu Bakar, Z.
2016-10-01
This study proposes an adaptive fuzzy controller for attitude control system (ACS) of Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new methods used in satellite attitude control, this paper presents three structures of controllers: Fuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the time response and tracking performance among the three different structures of controllers. The parameters of controller were tuned on-line by adjustment mechanism, which was an approach similar to a PID error that could minimize errors between actual and model reference output. This paper also presents a Model References Adaptive Control (MRAC) as a control scheme to control time varying systems where the performance specifications were given in terms of the reference model. All the controllers were tested using InnoSAT system under some operating conditions such as disturbance, varying gain, measurement noise and time delay. In conclusion, among all considered DA-type structures, AFPID controller was observed as the best structure since it outperformed other controllers in most conditions.
Adaptive Tracking Control for Robots With an Interneural Computing Scheme.
Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang
2017-01-24
Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.
Robust adaptive control of HVDC systems
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.
Adaptive Control of Nonlinear Flexible Systems
1993-01-18
disturbances. The following example illustrates the need for a robust state-feedback law and the sensi- tivity of the exact - linearization based control law... exact linearization , one can bring an input-output approach to a particular case of certainty- equivalence based adaptive control design. We now...are available for this model, exact linearization can be performed. Let C(s) be the compensator that is being used so far in the previous three
Adaptive control of a vibratory angle measuring gyroscope.
Park, Sungsu
2010-01-01
This paper presents an adaptive control algorithm for realizing a vibratory angle measuring gyroscope so that rotation angle can be directly measured without integration of angular rate, thus eliminating the accumulation of numerical integration errors. The proposed control algorithm uses a trajectory following approach and the reference trajectory is generated by an ideal angle measuring gyroscope driven by the estimate of angular rate and the auxiliary sinusoidal input so that the persistent excitation condition is satisfied. The developed control algorithm can compensate for all types of fabrication imperfections such as coupled damping and stiffness, and mismatched stiffness and un-equal damping term in an on-line fashion. The simulation results show the feasibility and effectiveness of the developed control algorithm that is capable of directly measuring rotation angle without the integration of angular rate.
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.
Geometry control in prestressed adaptive space trusses
NASA Astrophysics Data System (ADS)
Sener, Murat; Utku, Senol; Wada, Ben K.
1993-04-01
In this work the actuator placement problem for the precision control in prestressed adaptive space trusses is studied. These structures cannot be statically determinate, implying that the length-adjusting actuators have to work against the existing prestressing forces, and also against the stresses caused by the actuation. This type of difficulties does not exist in statically determinate adaptive trusses where, except for overcoming the friction, the actuators operate under zero axial force, and require almost no energy. The actuator placement problem in statically inderterminate trusses is, therefore, governed seriously by the energy and the strength requirements. The paper provides various methodologies for the actuator placement problem in prestressed space trusses.
Stochastic Adaptive Control and Estimation Enhancement
1990-02-01
ilM(k-S)1.izt-) (p. 1 and then the time after which the jump n’-* ’ takes place (i.e.. the sojourn time) is chosen 11 flp~ij) gil "’(n s~i,.k 39...Asilmar ant. pp 61-5. 184.Control or High Performance Aircraft using Adaptive ( Gil N.H. Ghalson and R.L. Moose. "Maneuverirng Target Aerstim ati nd...N It Dec. 1988. [ Gil N.H. Gholson and R.L. Moose, "Maneuveringl1(k.1) Is known, thus Target Tracking Using Adaptive State Estimation.- IEEE
NASA Astrophysics Data System (ADS)
Lausch, Anthony; Chen, Jeff; Ward, Aaron D.; Gaede, Stewart; Lee, Ting-Yim; Wong, Eugene
2014-11-01
Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient’s unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.
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.
NASA Astrophysics Data System (ADS)
Kiyko, V. V.; Kislov, V. I.; Ofitserov, E. N.
2015-08-01
In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 - 2.5 times less than the number of counts, and that difference grows with increasing measurement noise.
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.
Adaptive Automation and Cue Invocation: The Effect of Cue Timing on Operator Error
2013-05-01
129. 5. Parasuraman, R. (2000). Designing automation for human use: Empirical studies and quantitative models. Ergonomics , 43, 931-951. 6...Prospective memory errors involve memory for intended actions that are planned to be performed at some designated point in the future [20]. In the DMOO...RESCHU) [21] was used in this study. A Navy pilot who is familiar with supervisory control tasks designed the RESCHU task and the task has been
Fuzzy Backstepping Torque Control Of Passive Torque Simulator With Algebraic Parameters Adaptation
NASA Astrophysics Data System (ADS)
Ullah, Nasim; Wang, Shaoping; Wang, Xingjian
2015-07-01
This work presents fuzzy backstepping control techniques applied to the load simulator for good tracking performance in presence of extra torque, and nonlinear friction effects. Assuming that the parameters of the system are uncertain and bounded, Algebraic parameters adaptation algorithm is used to adopt the unknown parameters. The effect of transient fuzzy estimation error on parameters adaptation algorithm is analyzed and the fuzzy estimation error is further compensated using saturation function based adaptive control law working in parallel with the actual system to improve the transient performance of closed loop system. The saturation function based adaptive control term is large in the transient time and settles to an optimal lower value in the steady state for which the closed loop system remains stable. The simulation results verify the validity of the proposed control method applied to the complex aerodynamics passive load simulator.
Chen, Mou; Ge, Shuzhi Sam
2013-08-01
In this paper, the direct adaptive neural control is proposed for a class of uncertain nonaffine nonlinear systems with unknown nonsymmetric input saturation. Based on the implicit function theorem and mean value theorem, both state feedback and output feedback direct adaptive controls are developed using neural networks (NNs) and a disturbance observer. A compounded disturbance is defined to take into account of the effect of the unknown external disturbance, the unknown nonsymmetric input saturation, and the approximation error of NN. Then, a disturbance observer is developed to estimate the unknown compounded disturbance, and it is established that the estimate error converges to a compact set if appropriate observer design parameters are chosen. Both state feedback and output feedback direct adaptive controls can guarantee semiglobal uniform boundedness of the closed-loop system signals as rigorously proved by Lyapunov analysis. Numerical simulation results are presented to illustrate the effectiveness of the proposed direct adaptive neural control techniques.
Improvement of Adaptive Cruise Control Performance
NASA Astrophysics Data System (ADS)
Miyata, Shigeharu; Nakagami, Takashi; Kobayashi, Sei; Izumi, Tomoji; Naito, Hisayoshi; Yanou, Akira; Nakamura, Hitomi; Takehara, Shin
2010-12-01
This paper describes the Adaptive Cruise Control system (ACC), a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.
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.
An adaptive learning control system for aircraft
NASA Technical Reports Server (NTRS)
Mekel, R.; Nachmias, S.
1976-01-01
A learning control system is developed which blends the gain scheduling and adaptive control into a single learning system that has the advantages of both. An important feature of the developed learning control system is its capability to adjust the gain schedule in a prescribed manner to account for changing aircraft operating characteristics. Furthermore, if tests performed by the criteria of the learning system preclude any possible change in the gain schedule, then the overall system becomes an ordinary gain scheduling system. Examples are discussed.
Adaptive wing and flow control technology
NASA Astrophysics Data System (ADS)
Stanewsky, E.
2001-10-01
The development of the boundary layer and the interaction of the boundary layer with the outer “inviscid” flow field, exacerbated at high speed by the occurrence of shock waves, essentially determine the performance boundaries of high-speed flight. Furthermore, flight and freestream conditions may change considerably during an aircraft mission while the aircraft itself is only designed for multiple but fixed design points thus impairing overall performance. Consequently, flow and boundary layer control and adaptive wing technology may have revolutionary new benefits for take-off, landing and cruise operating conditions for many aircraft by enabling real-time effective geometry optimization relative to the flight conditions. In this paper we will consider various conventional and novel means of boundary layer and flow control applied to moderate-to-large aspect ratio wings, delta wings and bodies with the specific objectives of drag reduction, lift enhancement, separation suppression and the improvement of air-vehicle control effectiveness. In addition, adaptive wing concepts of varying complexity and corresponding aerodynamic performance gains will be discussed, also giving some examples of possible structural realizations. Furthermore, penalties associated with the implementation of control and adaptation mechanisms into actual aircraft will be addressed. Note that the present contribution is rather application oriented.
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.
Adaptive impedance control of redundant manipulators
NASA Technical Reports Server (NTRS)
Colbaugh, R.; Glass, K.; Seraji, H.
1990-01-01
A scheme for controlling the mechanical impedance of the end-effector of a kinematically redundant manipulator is presented. The proposed control system consists of two subsystems: an adaptive impedance controller which generates the Cartesian-space control input F (is a member of Rm) required to provide the desired end-effector impedance characteristics, and an algorithm that maps this control input to the joint torque T (is a member of Rn). The F to T map is constructed so that the robot redundancy is utilized to improve either the kinematic or dynamic performance of the robot. The impedance controller does not require knowledge of the complex robot dynamic model or parameter values for the robot, the payload, or the environment, and is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme is very general and is computationally efficient for on-line implementation.
Adaptive power-controllable orbital angular momentum (OAM) multicasting
Li, Shuhui; Wang, Jian
2015-01-01
We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, “up-down” power multicasting and “ladder” power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251
NASA Astrophysics Data System (ADS)
Jedrzejewski, Konrad; Malkiewicz, Łukasz
2016-09-01
The paper presents the results of studies pertaining to the influence of gain errors of inter-stage amplifiers on performance of adaptive sub-ranging analog-to-digital converters (ADCs). It focuses on adaptive sub-ranging ADCs with simplified architecture of the analog part - using only one amplifier and a low resolution digital-to-analog converter, that is identical to that of known conventional sub-ranging ADCs. The only difference between adaptive subranging ADCs with simplified architecture and conventional sub-ranging ADCs is the process of determination of output codes of converted samples. The adaptive sub-ranging ADCs calculate the output codes on the basis of sub-codes obtained in particular stages of conversion using an adaptive algorithm. Thanks to application of the optimal adaptive algorithm, adjusted to the parameters of possible components imperfections and internal noises, the adaptive ADCs outperform, in terms of effective resolution per cycle, conventional sub-ranging ADCs forming the output codes using simple lower-level bit operations. Optimization of the conversion algorithm used in adaptive ADCs leads however to high sensitivity of adaptive ADCs performance to the inter-stage gain error. An effective method for reduction of this sensitivity in adaptive sub-ranging ADCs with simplified architecture is proposed and discussed in the paper.
NASA Astrophysics Data System (ADS)
Owens, A. R.; Kópházi, J.; Welch, J. A.; Eaton, M. D.
2017-04-01
In this paper a hanging-node, discontinuous Galerkin, isogeometric discretisation of the multigroup, discrete ordinates (SN) equations is presented in which each energy group has its own mesh. The equations are discretised using Non-Uniform Rational B-Splines (NURBS), which allows the coarsest mesh to exactly represent the geometry for a wide range of engineering problems of interest; this would not be the case using straight-sided finite elements. Information is transferred between meshes via the construction of a supermesh. This is a non-trivial task for two arbitrary meshes, but is significantly simplified here by deriving every mesh from a common coarsest initial mesh. In order to take full advantage of this flexible discretisation, goal-based error estimators are derived for the multigroup, discrete ordinates equations with both fixed (extraneous) and fission sources, and these estimators are used to drive an adaptive mesh refinement (AMR) procedure. The method is applied to a variety of test cases for both fixed and fission source problems. The error estimators are found to be extremely accurate for linear NURBS discretisations, with degraded performance for quadratic discretisations owing to a reduction in relative accuracy of the ;exact; adjoint solution required to calculate the estimators. Nevertheless, the method seems to produce optimal meshes in the AMR process for both linear and quadratic discretisations, and is ≈×100 more accurate than uniform refinement for the same amount of computational effort for a 67 group deep penetration shielding problem.
NASA Technical Reports Server (NTRS)
Lee-Rausch, E. M.; Park, M. A.; Jones, W. T.; Hammond, D. P.; Nielsen, E. J.
2005-01-01
This paper demonstrates the extension of error estimation and adaptation methods to parallel computations enabling larger, more realistic aerospace applications and the quantification of discretization errors for complex 3-D solutions. Results were shown for an inviscid sonic-boom prediction about a double-cone configuration and a wing/body segmented leading edge (SLE) configuration where the output function of the adjoint was pressure integrated over a part of the cylinder in the near field. After multiple cycles of error estimation and surface/field adaptation, a significant improvement in the inviscid solution for the sonic boom signature of the double cone was observed. Although the double-cone adaptation was initiated from a very coarse mesh, the near-field pressure signature from the final adapted mesh compared very well with the wind-tunnel data which illustrates that the adjoint-based error estimation and adaptation process requires no a priori refinement of the mesh. Similarly, the near-field pressure signature for the SLE wing/body sonic boom configuration showed a significant improvement from the initial coarse mesh to the final adapted mesh in comparison with the wind tunnel results. Error estimation and field adaptation results were also presented for the viscous transonic drag prediction of the DLR-F6 wing/body configuration, and results were compared to a series of globally refined meshes. Two of these globally refined meshes were used as a starting point for the error estimation and field-adaptation process where the output function for the adjoint was the total drag. The field-adapted results showed an improvement in the prediction of the drag in comparison with the finest globally refined mesh and a reduction in the estimate of the remaining drag error. The adjoint-based adaptation parameter showed a need for increased resolution in the surface of the wing/body as well as a need for wake resolution downstream of the fuselage and wing trailing edge
A concatenated coded modulation scheme for error control
NASA Technical Reports Server (NTRS)
Kasami, Tadao; Takata, Toyoo; Fujiwara, Toru; Lin, Shu
1990-01-01
A concatenated coded modulation scheme for error control in data communications is presented. The scheme is achieved by concatenating a Reed-Solomon outer code and a bandwidth efficient block inner code for M-ary PSK modulation. Error performance of the scheme is analyzed for an AWGN channel. It is shown that extremely high reliability can be attained by using a simple M-ary PSK modulation inner code and relatively powerful Reed-Solomon outer code. Furthermore, if an inner code of high effective rate is used, the bandwidth expansion required by the scheme due to coding will be greatly reduced. The proposed scheme is particularly effective for high speed satellite communications for large file transfer where high reliability is required. Also presented is a simple method for constructing block codes for M-ary PSK modulation. Some short M-ary PSK codes with good minimum squared Euclidean distance are constructed. These codes have trellis structure and hence can be decoded with a soft-decision Viterbi decoding algorithm.
Development of a Transmission Error Model and an Error Control Model
1975-05-01
13 Tsai uses an error burst defined by Brayer [.24] as a sequence: 1. beginning and ending with an error, 2. the ratio of the number of errors to the...real channel data has been conducted by Brayer r23], 724], [25], [26] who considers HF, troposcatter, satellite and wireline channels. Extensive...an HF link. c) A model termed the Markov-Tasi model developed for a different HF link from that of (b). d) Seven models developed by Brayer [26) to
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.
Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang
2010-09-01
This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.
Adaptive Control Techniques for Large Space Structures
1987-12-23
2500 Mizssion. CoV~ege Boulevard Sar-ta Clara, Califorr-Iia 950541-1215 P--epared for: AFOSR, O irectcorate of Aerospace Sciences Bolling Air Force...formulated in late 1982 in re- sponse to the increasing concern that performance robustness of Air Force LSS type system would be inadequate to meet...Reducing the effects of on-board disturbance rejection) is particularly important for planned Air Force missions. For these cases, adaptive control
Applications of Neural Networks to Adaptive Control
1989-12-01
DTIC ;- E py 00 NAVAL POSTGRADUATE SCHOOL Monterey, California I.$ RDTIC IELECTE fl THESIS BEG7V°U APPLICATIONS OF NEURAL NETWORKS TO ADAPTIVE CONTROL...Second keader E . Robert Wood, Chairman, Department of Aeronautics and Astronautics Gordoii E . Schacher, Dean of Faculty and Graduate Education ii ABSTRACT...23: Network Dynamic Stability for q(t) . ............................. 55 ix Figure 24: Network Dynamic Stability for e (t
An Adaptive Buddy Check for Observational Quality Control
NASA Technical Reports Server (NTRS)
Dee, Dick P.; Rukhovets, Leonid; Todling, Ricardo; DaSilva, Arlindo M.; Larson, Jay W.; Einaudi, Franco (Technical Monitor)
2000-01-01
An adaptive buddy check algorithm is presented that adjusts tolerances for outlier observations based on the variability of surrounding data. The algorithm derives from a statistical hypothesis test combined with maximum-likelihood covariance estimation. Its stability is shown to depend on the initial identification of outliers by a simple background check. The adaptive feature ensures that the final quality control decisions are not very sensitive to prescribed statistics of first-guess and observation errors, nor on other approximations introduced into the algorithm. The implementation of the algorithm in a global atmospheric data assimilation is described. Its performance is contrasted with that of a non-adaptive buddy check, for the surface analysis of an extreme storm that took place in Europe on 27 December 1999. The adaptive algorithm allowed the inclusion of many important observations that differed greatly from the first guess and that would have been excluded on the basis of prescribed statistics. The analysis of the storm development was much improved as a result of these additional observations.
Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.
Gao, Hui; Song, Yongduan; Wen, Changyun
2016-08-24
In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in L[₀,∞]. In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.
Wang, Chenhui
2016-01-01
In this paper, control of uncertain fractional-order financial chaotic system with input saturation and external disturbance is investigated. The unknown part of the input saturation as well as the system’s unknown nonlinear function is approximated by a fuzzy logic system. To handle the fuzzy approximation error and the estimation error of the unknown upper bound of the external disturbance, fractional-order adaptation laws are constructed. Based on fractional Lyapunov stability theorem, an adaptive fuzzy controller is designed, and the asymptotical stability can be guaranteed. Finally, simulation studies are given to indicate the effectiveness of the proposed method. PMID:27783648
Rinderknecht, Mike Domenik; Delaloye, Fabien André; Crespi, Alessandro; Ronsse, Renaud; Ijspeert, Auke Jan
2011-01-01
This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify.
Testing and error analysis of a real-time controller
NASA Technical Reports Server (NTRS)
Savolaine, C. G.
1983-01-01
Inexpensive ways to organize and conduct system testing that were used on a real-time satellite network control system are outlined. This system contains roughly 50,000 lines of executable source code developed by a team of eight people. For a small investment of staff, the system was thoroughly tested, including automated regression testing, before field release. Detailed records were kept for fourteen months, during which several versions of the system were written. A separate testing group was not established, but testing itself was structured apart from the development process. The errors found during testing are examined by frequency per subsystem by size and complexity as well as by type. The code was released to the user in March, 1983. To date, only a few minor problems found with the system during its pre-service testing and user acceptance has been good.
76 FR 67315 - Supplemental Nutrition Assistance Program: Quality Control Error Tolerance Threshold
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-01
... Service 7 CFR Part 275 RIN 0584-AE24 Supplemental Nutrition Assistance Program: Quality Control Error... direct final rule is amending the Quality Control (QC) review error threshold in our regulations from $25... Assistance Program: Quality Control Error Tolerance Threshold Direct Rule, in the subject line of the...
Lindström, Björn R; Mattsson-Mårn, Isak Berglund; Golkar, Armita; Olsson, Andreas
2013-01-01
Cognitive control is needed when mistakes have consequences, especially when such consequences are potentially harmful. However, little is known about how the aversive consequences of deficient control affect behavior. To address this issue, participants performed a two-choice response time task where error commissions were expected to be punished by electric shocks during certain blocks. By manipulating (1) the perceived punishment risk (no, low, high) associated with error commissions, and (2) response conflict (low, high), we showed that motivation to avoid punishment enhanced performance during high response conflict. As a novel index of the processes enabling successful cognitive control under threat, we explored electromyographic activity in the corrugator supercilii (cEMG) muscle of the upper face. The corrugator supercilii is partially controlled by the anterior midcingulate cortex (aMCC) which is sensitive to negative affect, pain and cognitive control. As hypothesized, the cEMG exhibited several key similarities with the core temporal and functional characteristics of the Error-Related Negativity (ERN) ERP component, the hallmark index of cognitive control elicited by performance errors, and which has been linked to the aMCC. The cEMG was amplified within 100 ms of error commissions (the same time-window as the ERN), particularly during the high punishment risk condition where errors would be most aversive. Furthermore, similar to the ERN, the magnitude of error cEMG predicted post-error response time slowing. Our results suggest that cEMG activity can serve as an index of avoidance motivated control, which is instrumental to adaptive cognitive control when consequences are potentially harmful.
Nonlinear signal-based control with an error feedback action for nonlinear substructuring control
NASA Astrophysics Data System (ADS)
Enokida, Ryuta; Kajiwara, Koichi
2017-01-01
A nonlinear signal-based control (NSBC) method utilises the 'nonlinear signal' that is obtained from the outputs of a controlled system and its linear model under the same input signal. Although this method has been examined in numerical simulations of nonlinear systems, its application in physical experiments has not been studied. In this paper, we study an application of NSBC in physical experiments and incorporate an error feedback action into the method to minimise the error and enhance the feasibility in practice. Focusing on NSBC in substructure testing methods, we propose nonlinear substructuring control (NLSC), that is a more general form of linear substructuring control (LSC) developed for dynamical substructured systems. In this study, we experimentally and numerically verified the proposed NLSC via substructuring tests on a rubber bearing used in base-isolated structures. In the examinations, NLSC succeeded in gaining accurate results despite significant nonlinear hysteresis and unknown parameters in the substructures. The nonlinear signal feedback action in NLSC was found to be notably effective in minimising the error caused by nonlinearity or unknown properties in the controlled system. In addition, the error feedback action in NLSC was found to be essential for maintaining stability. A stability analysis based on the Nyquist criterion, which is used particularly for linear systems, was also found to be efficient for predicting the instability conditions of substructuring tests with NLSC and useful for the error feedback controller design.
Adaptive limiter control of unimodal population maps.
Franco, Daniel; Hilker, Frank M
2013-11-21
We analyse the adaptive limiter control (ALC) method, which was recently proposed for stabilizing population oscillations and experimentally tested in laboratory populations and metapopulations of Drosophila melanogaster. We thoroughly explain the mechanisms that allow ALC to reduce the magnitude of population fluctuations under certain conditions. In general, ALC is a control strategy with a number of useful properties (e.g. being globally asymptotically stable), but there may be some caveats. The control can be ineffective or even counterproductive at small intensities, and the interventions can be extremely costly at very large intensities. Based on our analytical results, we describe recipes how to choose the control intensity, depending on the range of population sizes we wish to target. In our analysis, we highlight the possible importance of initial transients and classify them into different categories.
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.
Neural Control Adaptation to Motor Noise Manipulation
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
Robust adaptive cruise control of high speed trains.
Faieghi, Mohammadreza; Jalali, Aliakbar; Mashhadi, Seyed Kamal-e-ddin Mousavi
2014-03-01
The cruise control problem of high speed trains in the presence of unknown parameters and external disturbances is considered. In particular a Lyapunov-based robust adaptive controller is presented to achieve asymptotic tracking and disturbance rejection. The system under consideration is nonlinear, MIMO and non-minimum phase. To deal with the limitations arising from the unstable zero-dynamics we do an output redefinition such that the zero-dynamics with respect to new outputs becomes stable. Rigorous stability analyses are presented which establish the boundedness of all the internal states and simultaneously asymptotic stability of the tracking error dynamics. The results are presented for two common configurations of high speed trains, i.e. the DD and PPD designs, based on the multi-body model and are verified by several numerical simulations.
Kalman filtering to suppress spurious signals in adaptive optics control.
Poyneer, Lisa A; Véran, Jean-Pierre
2010-11-01
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.
Kalman filtering to suppress spurious signals in Adaptive Optics control
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.
Robust adaptive backstepping control for piezoelectric nano-manipulating systems
NASA Astrophysics Data System (ADS)
Zhang, Yangming; Yan, Peng; Zhang, Zhen
2017-01-01
In this paper we present a systematic modeling and control approach for nano-manipulations of a two-dimensional PZT (piezoelectric transducer) actuated servo stage. The major control challenges associated with piezoelectric nano-manipulators typically include the nonlinear dynamics of hysteresis, model uncertainties, and various disturbances. The adverse effects of these complications will result in significant performance loss, unless effectively eliminated. The primary goal of the paper is on the ultra high precision control of such systems by handling various model uncertainties and disturbances simultaneously. To this end, a novel robust adaptive backstepping-like control approach is developed such that parametric uncertainties can be estimated adaptively while the nonlinear dynamics and external disturbances are treated as bounded disturbances for robust elimination. Meanwhile, the L2-gain of the closed-loop system is considered, and an H∞ optimization problem is formulated to improve the tracking accuracy. Numerical simulations and real time experiments are finally conducted, which significantly outperform conventional PID methods and achieve around 1% tracking error for circular contouring tasks.
Adaptive control of force microscope cantilever dynamics
NASA Astrophysics Data System (ADS)
Jensen, S. E.; Dougherty, W. M.; Garbini, J. L.; Sidles, J. A.
2007-09-01
Magnetic resonance force microscopy (MRFM) and other emerging scanning probe microscopies entail the detection of attonewton-scale forces. Requisite force sensitivities are achieved through the use of soft force microscope cantilevers as high resonant-Q micromechanical oscillators. In practice, the dynamics of these oscillators are greatly improved by the application of force feedback control computed in real time by a digital signal processor (DSP). Improvements include increased sensitive bandwidth, reduced oscillator ring up/down time, and reduced cantilever thermal vibration amplitude. However, when the cantilever tip and the sample are in close proximity, electrostatic and Casimir tip-sample force gradients can significantly alter the cantilever resonance frequency, foiling fixed-gain narrow-band control schemes. We report an improved, adaptive control algorithm that uses a Hilbert transform technique to continuously measure the vibration frequency of the thermally-excited cantilever and seamlessly adjust the DSP program coefficients. The closed-loop vibration amplitude is typically 0.05 nm. This adaptive algorithm enables narrow-band formally-optimal control over a wide range of resonance frequencies, and preserves the thermally-limited signal to noise ratio (SNR).
Kertzscher, Gustavo Andersen, Claus E.; Tanderup, Kari
2014-05-15
Purpose: This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction of the dosimeter position. Instead, the treatment is judged based on dose rate comparisons between measurements and calculations of the most viable dosimeter position provided by the AEDA in a data driven approach. As a result, the AEDA compensates for false error cases related to systematic effects of the dosimeter position reconstruction. Given its nearly exclusive dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods: In the event of a measured potential treatment error, the AEDA proposes the most viable dosimeter position out of alternatives to the original reconstruction by means of a data driven matching procedure between dose rate distributions. If measured dose rates do not differ significantly from the most viable alternative, the initial error indication may be attributed to a mispositioned or misreconstructed dosimeter (false error). However, if the error declaration persists, no viable dosimeter position can be found to explain the error, hence the discrepancy is more likely to originate from a misplaced or misreconstructed source applicator or from erroneously connected source guide tubes (true error). Results: The AEDA applied on twoin vivo dosimetry implementations for pulsed dose rate BT demonstrated that the AEDA correctly described effects responsible for initial error indications. The AEDA was able to correctly identify the major part of all permutations of simulated guide tube swap errors and simulated shifts of individual needles from the original reconstruction. Unidentified errors corresponded to scenarios where the dosimeter position was
More pain, more gain: Blocking the opioid system boosts adaptive cognitive control.
van Steenbergen, Henk; Weissman, Daniel H; Stein, Dan J; Malcolm-Smith, Susan; van Honk, Jack
2017-03-07
The ability to adaptively increase cognitive control in response to cognitive challenges is crucial for goal-directed behavior. Recent findings suggest that aversive arousal triggers adaptive increases of control, but the neurochemical mechanisms underlying these effects remain unclear. Given the known contributions of the opioid system to hedonic states, we investigated whether blocking this system increases adaptive control modulations. To do so, we conducted a double-blind, placebo-controlled psychopharmacological study (n=52 females) involving a Stroop-like task. Specifically, we assessed the effect of naltrexone, an opioid blocker most selective to the mu-opioid system, on two measures of adaptive control that are thought to depend differentially on aversive arousal: post-error slowing and conflict adaptation. Consistent with our hypothesis, relative to placebo, naltrexone increased post-error slowing without influencing conflict adaptation. This finding not only supports the view that aversive arousal triggers adaptive control but also reveals a novel role for the opioid system in modulating such effects.
Lago-Rodriguez, Angel; Miall, R. Chris
2016-01-01
Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC) trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group), when compared with participants who had no EC feedback regarding movement trajectory (Arc group). Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group). Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory. PMID:27721748
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
Adaptive control of a Stewart platform-based manipulator
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.
1993-01-01
A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
Adaptive fuzzy-neural-network control for maglev transportation system.
Wai, Rong-Jong; Lee, Jeng-Dao
2008-01-01
A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies.
NASA Technical Reports Server (NTRS)
VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.
2014-01-01
Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a
Adaptive Neural Network Control for the Trajectory Tracking of the Furuta Pendulum.
Moreno-Valenzuela, Javier; Aguilar-Avelar, Carlos; Puga-Guzman, Sergio A; Santibanez, Victor
2016-12-01
The purpose of this paper is to introduce a novel adaptive neural network-based control scheme for the Furuta pendulum, which is a two degree-of-freedom underactuated system. Adaptation laws for the input and output weights are also provided. The proposed controller is able to guarantee tracking of a reference signal for the arm while the pendulum remains in the upright position. The key aspect of the derivation of the controller is the definition of an output function that depends on the position and velocity errors. The internal and external dynamics are rigorously analyzed, thereby proving the uniform ultimate boundedness of the error trajectories. By using real-time experiments, the new scheme is compared with other control methodologies, therein demonstrating the improved performance of the proposed adaptive algorithm.
ERIC Educational Resources Information Center
Weinzierl, Christiane; Kerkhoff, Georg; van Eimeren, Lucia; Keller, Ingo; Stenneken, Prisca
2012-01-01
Unilateral spatial neglect frequently involves a lateralised reading disorder, neglect dyslexia (ND). Reading of single words in ND is characterised by left-sided omissions and substitutions of letters. However, it is unclear whether the distribution of error types and positions within a word shows a unique pattern of ND when directly compared to…
NASA Technical Reports Server (NTRS)
Wen, John T.; Kreutz, Kenneth; Bayard, David S.
1988-01-01
A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.
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.
Adaptive control of space based robot manipulators
NASA Technical Reports Server (NTRS)
Walker, Michael W.; Wee, Liang-Boon
1991-01-01
For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.
Induction machine Direct Torque Control system based on fuzzy adaptive control
NASA Astrophysics Data System (ADS)
Li, Shi-ping; Yu, Yan; Jiao, Zhen-gang; Gu, Shu-sheng
2009-07-01
Direct Torque Control technology is a high-performance communication control method, it uses the space voltage vector method, and then to the inverter switch state control, to obtain high torque dynamic performance. But none of the switching states is able to generate the exact voltage vector to produce the desired changes in torque and flux in most of the switching instances. This causes a high ripple in torque. To solve this problem, a fuzzy implementation of Direct Torque Control of Induction machine is presented here. Error of stator flux, error of motor electromagnetic torque and position of angle of flux are taken as fuzzy variables. In order to further solve nonlinear problem of variation parameters in direct torque control system, the paper proposes a fuzzy parameter PID adaptive control method which is suitable for the direct torque control of an asynchronous motor. The generation of its fuzzy control is obtained by analyzing and optimizing PID control step response and combining expert's experience. For this reason, it carries out fuzzy work to PID regulator of motor speed to achieve to regulate PID parameters. Therefore the control system gets swifter response velocity, stronger robustness and higher precision of velocity control. The computer simulated results verify the validity of this novel method.
NASA Astrophysics Data System (ADS)
Shankar, Praveen
The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network
Direct adaptive control of wind energy conversion systems using Gaussian networks.
Mayosky, M A; Cancelo, I E
1999-01-01
Grid connected wind energy conversion systems (WECS) present interesting control demands, due to the intrinsic nonlinear characteristics of windmills and electric generators. In this paper a direct adaptive control strategy for WECS control is proposed. It is based on the combination of two control actions: a radial basis zfunction network-based adaptive controller, which drives the tracking error to zero with user specified dynamics, and a supervisory controller, based on crude bounds of the system's nonlinearities. The supervisory controller fires when the finite neural-network approximation properties cannot be guaranteed. The form of the supervisor control and the adaptation law for the neural controller are derived from a Lyapunov analysis of stability. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution.
Adaptive synchronization control of coupled chaotic neurons in an external electrical stimulation
NASA Astrophysics Data System (ADS)
Yu, Hai-Tao; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan
2013-05-01
In this paper we present a combined algorithm for the synchronization control of two gap junction coupled chaotic FitzHugh—Nagumo (FHN) neurons in an external electrical stimulation. The controller consists of a combination of dynamical sliding mode control and adaptive backstepping control. The combined algorithm yields an adaptive dynamical sliding mode control law which has the advantage over static sliding mode-based controllers of being chattering-free, i.e., a sufficiently smooth control input signal is generated. It is shown that the proposed control scheme can not only compensate for the system uncertainty, but also guarantee the stability of the synchronized error system. In addition, numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller.
Adaptive method with intercessory feedback control for an intelligent agent
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.
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.
Neural network-based adaptive controller design of robotic manipulators with an observer.
Sun, F; Sun, Z; Woo, P Y
2001-01-01
A neural network (NN)-based adaptive controller with an observer is proposed for the trajectory tracking of robotic manipulators with unknown dynamics nonlinearities. It is assumed that the robotic manipulator has only joint angle position measurements. A linear observer is used to estimate the robot joint angle velocity, while NNs are employed to further improve the control performance of the controlled system through approximating the modified robot dynamics function. The adaptive controller for robots with an observer can guarantee the uniform ultimate bounds of the tracking errors and the observer errors as well as the bounds of the NN weights. For performance comparisons, the conventional adaptive algorithm with an observer using linearity in parameters of the robot dynamics is also developed in the same control framework as the NN approach for online approximating unknown nonlinearities of the robot dynamics. Main theoretical results for designing such an observer-based adaptive controller with the NN approach using multilayer NNs with sigmoidal activation functions, as well as with the conventional adaptive approach using linearity in parameters of the robot dynamics are given. The performance comparisons between the NN approach and the conventional adaptation approach with an observer is carried out to show the advantages of the proposed control approaches through simulation studies.
Robust time and frequency domain estimation methods in adaptive control
NASA Technical Reports Server (NTRS)
Lamaire, Richard Orville
1987-01-01
A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.
Motor control: correcting errors and learning from mistakes.
Miall, Chris
2010-07-27
How do we learn from errors during complex movement tasks with redundancy? A new study shows that ambiguous mistakes in bimanual movements are corrected by the non-dominant hand, and responsibility for the error is assumed to fall to the effector with a recent history of poor performance.
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.
Adaptation of hybrid human-computer interaction systems using EEG error-related potentials.
Chavarriaga, Ricardo; Biasiucci, Andrea; Forster, Killian; Roggen, Daniel; Troster, Gerhard; Millan, Jose Del R
2010-01-01
Performance improvement in both humans and artificial systems strongly relies in the ability of recognizing erroneous behavior or decisions. This paper, that builds upon previous studies on EEG error-related signals, presents a hybrid approach for human computer interaction that uses human gestures to send commands to a computer and exploits brain activity to provide implicit feedback about the recognition of such commands. Using a simple computer game as a case study, we show that EEG activity evoked by erroneous gesture recognition can be classified in single trials above random levels. Automatic artifact rejection techniques are used, taking into account that subjects are allowed to move during the experiment. Moreover, we present a simple adaptation mechanism that uses the EEG signal to label newly acquired samples and can be used to re-calibrate the gesture recognition system in a supervised manner. Offline analysis show that, although the achieved EEG decoding accuracy is far from being perfect, these signals convey sufficient information to significantly improve the overall system performance.
A cascaded error control coding scheme for space and satellite communication
NASA Technical Reports Server (NTRS)
Lin, Shu; Kasami, Tadao; Fujiwara, Tohru; Takata, Toyoo
1986-01-01
An error control coding scheme for space and satellite communications is presented. The scheme is attained by cascading two codes, the inner and outer codes. Error performance of the scheme is analyzed. It is shown that, if the inner and outer codes are chosen properly, extremely high reliability can be achieved even for a high channel bit-error-rate. Several exmple schemes are studied. One of the example schemes is proposed to NASA for satellite or spacecraft downlink error control.
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.
Veran
2000-07-01
Off-axis observations made with adaptive optics are severely limited by anisoplanatism errors. However, conjugating the deformable mirror to an optimal altitude can reduce these errors; it is then necessary to control, through extrapolation, actuators that are not measured by the wave-front sensor (unilluminated actuators). In this study various common extrapolation schemes are investigated, and an optimal method that achieves a significantly better performance is proposed. This extrapolation method involves a simple matrix multiplication and will be implemented in ALTAIR, the Gemini North Telescope adaptive optics system located on Mauna Kea, Hawaii. With this optimal method, the relative H-band Strehl reduction due to extrapolation errors is only 5%, 16%, and 30% when the angular distance between the guide source and the science target is 20, 40 and 60 arc sec, respectively. For a site such as Mauna Kea, these errors are largely outweighed by the increase in the size of the isoplanatic field.
Adaptive collaborative control of highly redundant robots
NASA Astrophysics Data System (ADS)
Handelman, David A.
2008-04-01
The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.
Robustness of Adaptive Control Algorithms in the Presence of Unmodeled Dynamics,
1982-09-01
result, two possible noch - tt (t (3a) anisms of instability are isolated and discussed. It is argued, that the destabilizing effects in the presence L t [J...to Modeling Errors, Ph.D. Thesis, Dept. of Elec. Eng., Univ. of Illinois at 2. A. uer mad A.S. Norse, *Adaptive Control of Urbana -ahampaign, Report
Wavefront control for extreme adaptive optics
NASA Astrophysics Data System (ADS)
Poyneer, Lisa A.; Macintosh, Bruce A.
2003-12-01
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.
Wavefront Control for Extreme Adaptive Optics
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.
ERIC Educational Resources Information Center
Kluge, Annette; Sauer, Juergen; Burkolter, Dina; Ritzmann, Sandrina
2010-01-01
Training in process control environments requires operators to be prepared for temporal and adaptive transfer of skill. Three training methods were compared with regard to their effectiveness in supporting transfer: Drill & Practice (D&P), Error Training (ET), and procedure-based and error heuristics training (PHT). Communication…
Adaptive control for a class of second-order nonlinear systems with unknown input nonlinearities.
Zhang, T; Guay, M
2003-01-01
An adaptive controller is developed for a class of second-order nonlinear dynamic systems with input nonlinearities using artificial neural networks (ANN). The unknown input nonlinearities are continuous and monotone and satisfy a sector constraint. In contrast to conventional Lyapunov-based design techniques, an alternative Lyapunov function, which depends on both system states and control input variable, is used for the development of a control law and a learning algorithm. The proposed adaptive controller guarantees the stability of the closed-loop system and convergence of the output tracking error to an adjustable neighbour of the origin.
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.
NASA Astrophysics Data System (ADS)
Feischl, Michael; Gantner, Gregor; Praetorius, Dirk
2015-06-01
We consider the Galerkin boundary element method (BEM) for weakly-singular integral equations of the first-kind in 2D. We analyze some residual-type a posteriori error estimator which provides a lower as well as an upper bound for the unknown Galerkin BEM error. The required assumptions are weak and allow for piecewise smooth parametrizations of the boundary, local mesh-refinement, and related standard piecewise polynomials as well as NURBS. In particular, our analysis gives a first contribution to adaptive BEM in the frame of isogeometric analysis (IGABEM), for which we formulate an adaptive algorithm which steers the local mesh-refinement and the multiplicity of the knots. Numerical experiments underline the theoretical findings and show that the proposed adaptive strategy leads to optimal convergence.
Feischl, Michael; Gantner, Gregor; Praetorius, Dirk
2015-01-01
We consider the Galerkin boundary element method (BEM) for weakly-singular integral equations of the first-kind in 2D. We analyze some residual-type a posteriori error estimator which provides a lower as well as an upper bound for the unknown Galerkin BEM error. The required assumptions are weak and allow for piecewise smooth parametrizations of the boundary, local mesh-refinement, and related standard piecewise polynomials as well as NURBS. In particular, our analysis gives a first contribution to adaptive BEM in the frame of isogeometric analysis (IGABEM), for which we formulate an adaptive algorithm which steers the local mesh-refinement and the multiplicity of the knots. Numerical experiments underline the theoretical findings and show that the proposed adaptive strategy leads to optimal convergence. PMID:26085698
Neural network payload estimation for adaptive robot control.
Leahy, M R; Johnson, M A; Rogers, S K
1991-01-01
A concept is proposed for utilizing artificial neural networks to enhance the high-speed tracking accuracy of robotic manipulators. Tracking accuracy is a function of the controller's ability to compensate for disturbances produced by dynamical interactions between the links. A model-based control algorithm uses a nominal model of those dynamical interactions to reduce the disturbances. The problem is how to provide accurate dynamics information to the controller in the presence of payload uncertainty and modeling error. Neural network payload estimation uses a series of artificial neural networks to recognize the payload variation associated with a degradation in tracking performance. The network outputs are combined with a knowledge of nominal dynamics to produce a computationally efficient direct form of adaptive control. The concept is validated through experimentation and analysis on the first three links of a PUMA-560 manipulator. A multilayer perceptron architecture with two hidden layers is used. Integration of the principles of neural network pattern recognition and model-based control produces a tracking algorithm with enhanced robustness to incomplete dynamic information. Tracking efficacy and applicability to robust control algorithms are discussed.
Quantum Error Correction: Optimal, Robust, or Adaptive? Or, Where is The Quantum Flyball Governor?
NASA Astrophysics Data System (ADS)
Kosut, Robert; Grace, Matthew
2012-02-01
In The Human Use of Human Beings: Cybernetics and Society (1950), Norbert Wiener introduces feedback control in this way: ``This control of a machine on the basis of its actual performance rather than its expected performance is known as feedback ... It is the function of control ... to produce a temporary and local reversal of the normal direction of entropy.'' The classic classroom example of feedback control is the all-mechanical flyball governor used by James Watt in the 18th century to regulate the speed of rotating steam engines. What is it that is so compelling about this apparatus? First, it is easy to understand how it regulates the speed of a rotating steam engine. Secondly, and perhaps more importantly, it is a part of the device itself. A naive observer would not distinguish this mechanical piece from all the rest. So it is natural to ask, where is the all-quantum device which is self regulating, ie, the Quantum Flyball Governor? Is the goal of quantum error correction (QEC) to design such a device? Devloping the computational and mathematical tools to design this device is the topic of this talk.
MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.
Najjar-Khodabakhsh, Abbas; Soltani, Jafar
2016-03-01
In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method.
Adaptive Control of Small Outboard-Powered Boats for Survey Applications
NASA Technical Reports Server (NTRS)
VanZwieten, T.S.; VanZwieten, J.H.; Fisher, A.D.
2009-01-01
Four autopilot controllers have been developed in this work that can both hold a desired heading and follow a straight line. These PID, adaptive PID, neuro-adaptive, and adaptive augmenting control algorithms have all been implemented into a numerical simulation of a 33-foot center console vessel with wind, waves, and current disturbances acting in the perpendicular (across-track) direction of the boat s desired trajectory. Each controller is tested for its ability to follow a desired heading in the presence of these disturbances and then to follow a straight line at two different throttle settings for the same disturbances. These controllers were tuned for an input thrust of 2000 N and all four controllers showed good performance with none of the controllers significantly outperforming the others when holding a constant heading and following a straight line at this engine thrust. Each controller was then tested for a reduced engine thrust of 1200 N per engine where each of the three adaptive controllers reduced heading error and across-track error by approximately 50% after a 300 second tuning period when compared to the fixed gain PID, showing that significant robustness to changes in throttle setting was gained by using an adaptive algorithm.
FPGA-accelerated adaptive optics wavefront control
NASA Astrophysics Data System (ADS)
Mauch, S.; Reger, J.; Reinlein, C.; Appelfelder, M.; Goy, M.; Beckert, E.; Tünnermann, A.
2014-03-01
The speed of real-time adaptive optical systems is primarily restricted by the data processing hardware and computational aspects. Furthermore, the application of mirror layouts with increasing numbers of actuators reduces the bandwidth (speed) of the system and, thus, the number of applicable control algorithms. This burden turns out a key-impediment for deformable mirrors with continuous mirror surface and highly coupled actuator influence functions. In this regard, specialized hardware is necessary for high performance real-time control applications. Our approach to overcome this challenge is an adaptive optics system based on a Shack-Hartmann wavefront sensor (SHWFS) with a CameraLink interface. The data processing is based on a high performance Intel Core i7 Quadcore hard real-time Linux system. Employing a Xilinx Kintex-7 FPGA, an own developed PCie card is outlined in order to accelerate the analysis of a Shack-Hartmann Wavefront Sensor. A recently developed real-time capable spot detection algorithm evaluates the wavefront. The main features of the presented system are the reduction of latency and the acceleration of computation For example, matrix multiplications which in general are of complexity O(n3 are accelerated by using the DSP48 slices of the field-programmable gate array (FPGA) as well as a novel hardware implementation of the SHWFS algorithm. Further benefits are the Streaming SIMD Extensions (SSE) which intensively use the parallelization capability of the processor for further reducing the latency and increasing the bandwidth of the closed-loop. Due to this approach, up to 64 actuators of a deformable mirror can be handled and controlled without noticeable restriction from computational burdens.
Adaptive powertrain control for plugin hybrid electric vehicles
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.
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
Driver behaviour with adaptive cruise control.
Stanton, Neville A; Young, Mark S
2005-08-15
This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts.
Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.
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.
Dynamic modeling and adaptive control for space stations
NASA Technical Reports Server (NTRS)
Ih, C. H. C.; Wang, S. J.
1985-01-01
Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained.
Stochastic Adaptive Control and Estimation Enhancement
1989-09-01
total Zu(N-J)’Gj’Q(N)FxIN-1)ou (N-I)I’[ R (N- 1) ’(N I Gil probability theorem to (4.3) yields J*(k.k 3 - min ( Ejx(kl 0(k)x(k) - u(k)’R(klu(k) trQ(N)VI m...Is Independent of Mil), I-k*2 .... N If Dec. 1988. [ Gil N.H. Gholson and R.L. Moose, "ManeuveringM(k.1J Is known, thus Target Tracking Using Adaptive...Control and A(t) =_ J1N X(i,t) is uniformly bounded. Quasi-Variational Inequalities, Gauthier- Villars , . (t9. tER4 , exits 0’ at most a countable
A cascaded coding scheme for error control and its performance analysis
NASA Technical Reports Server (NTRS)
Kasami, Tadao; Fujiwara, Toru; Takata, Toyoo; Lin, Shu
1988-01-01
A coding scheme for error control in data communication systems is investigated. The scheme is obtained by cascading two error-correcting codes, called the inner and outer codes. Its error performance is analyzed for a binary symmetric channel with bit-error rate epsilon less than 1/2. It is shown that, if the inner and outer codes are chosen properly, high reliability can be attained even for a high-channel bit-error rate. Specific examples with inner codes ranging from high rates and Reed-Solomon codes as outer codes are considered, and their error probabilities evaluated. They all provide high reliability even for high bit-error rates, say 0.1-0.01. Several example schemes are being considered for satellite and spacecraft downlink error control.
A cascaded coding scheme for error control and its performance analysis
NASA Technical Reports Server (NTRS)
Lin, Shu; Kasami, Tadao; Fujiwara, Tohru; Takata, Toyoo
1986-01-01
A coding scheme is investigated for error control in data communication systems. The scheme is obtained by cascading two error correcting codes, called the inner and outer codes. The error performance of the scheme is analyzed for a binary symmetric channel with bit error rate epsilon <1/2. It is shown that if the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit error rate. Various specific example schemes with inner codes ranging form high rates to very low rates and Reed-Solomon codes as inner codes are considered, and their error probabilities are evaluated. They all provide extremely high reliability even for very high bit error rates. Several example schemes are being considered by NASA for satellite and spacecraft down link error control.
Soshi, Takahiro; Ando, Kumiko; Noda, Takamasa; Nakazawa, Kanako; Tsumura, Hideki; Okada, Takayuki
2015-01-01
Post-error slowing (PES) is an error recovery strategy that contributes to action control, and occurs after errors in order to prevent future behavioral flaws. Error recovery often malfunctions in clinical populations, but the relationship between behavioral traits and recovery from error is unclear in healthy populations. The present study investigated the relationship between impulsivity and error recovery by simulating a speeded response situation using a Go/No-go paradigm that forced the participants to constantly make accelerated responses prior to stimuli disappearance (stimulus duration: 250 ms). Neural correlates of post-error processing were examined using event-related potentials (ERPs). Impulsivity traits were measured with self-report questionnaires (BIS-11, BIS/BAS). Behavioral results demonstrated that the commission error for No-go trials was 15%, but PES did not take place immediately. Delayed PES was negatively correlated with error rates and impulsivity traits, showing that response slowing was associated with reduced error rates and changed with impulsivity. Response-locked error ERPs were clearly observed for the error trials. Contrary to previous studies, error ERPs were not significantly related to PES. Stimulus-locked N2 was negatively correlated with PES and positively correlated with impulsivity traits at the second post-error Go trial: larger N2 activity was associated with greater PES and less impulsivity. In summary, under constant speeded conditions, error monitoring was dissociated from post-error action control, and PES did not occur quickly. Furthermore, PES and its neural correlate (N2) were modulated by impulsivity traits. These findings suggest that there may be clinical and practical efficacy of maintaining cognitive control of actions during error recovery under common daily environments that frequently evoke impulsive behaviors. PMID:25674058
Stable adaptive control using new critic designs
NASA Astrophysics Data System (ADS)
Werbos, Paul J.
1999-03-01
Classical adaptive control proves total-system stability for control of linear plants, but only for plants meeting very restrictive assumptions. Approximate Dynamic Programming (ADP) has the potential, in principle, to ensure stability without such tight restrictions. It also offers nonlinear and neural extensions for optimal control, with empirically supported links to what is seen in the brain. However, the relevant ADP methods in use today--TD, HDP, DHP, GDHP--and the Galerkin-based versions of these all have serious limitations when used here as parallel distributed real-time learning systems; either they do not possess quadratic unconditional stability (to be defined) or they lead to incorrect results in the stochastic case. (ADAC or Q- learning designs do not help.) After explaining these conclusions, this paper describes new ADP designs which overcome these limitations. It also addresses the Generalized Moving Target problem, a common family of static optimization problems, and describes a way to stabilize large-scale economic equilibrium models, such as the old long-term energy mode of DOE.
Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Balas, Mark J.; Wright, Alan D.
2009-01-01
Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.
A cerebellar neural network model for adaptative control of saccades implemented with MATLAB.
Rodriguez Campos, Francisco A; Enderle, John
2003-01-01
This paper describes the implementation of a neural network for the adaptative control of the saccadic system. The model shows the cerebellum plays an important role in the adaptive control of the saccadic gain. Using only eye position input through the granule cells, the cerebellum projects this signal to the other cerebellar structures and then to motor neurons responsible for the saccade. The generation of an adjustment signal occurs in the inferior olive as a result of the error sensory signal created by the open loop saccade system from propioceptive position inputs from the last eye movement generated by the network until the movement towards the target is completed. In addition, a memory component has been defined in the error system to achieve the adaptation. This neural network involves only the horizontal saccade component modeled with Matrix Laboratory language (MATLAB), in conjunction with the Simulink tool.
Almost Sure Convergence of Adaptive Identification Prediction and Control Algorithms.
1981-03-01
achievable with known plant parameters, in the Cesaro sense. An additional regularity assumption on the signal model establishes the result that the...the Cesaro sense. Under an additional regularity assumption, the convergence of these errors and also that of the tracking error for the adaptive con...The 4- convergence in all these references is established in the Cesaro sense. The above schemes of [7-10] leave the question unanswered as to
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.
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.
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1990-01-01
An expurgated upper bound on the event error probability of trellis coded modulation is presented. This bound is used to derive a lower bound on the minimum achievable free Euclidean distance d sub (free) of trellis codes. It is shown that the dominant parameters for both bounds, the expurgated error exponent and the asymptotic d sub (free) growth rate, respectively, can be obtained from the cutoff-rate R sub O of the transmission channel by a simple geometric construction, making R sub O the central parameter for finding good trellis codes. Several constellations are optimized with respect to the bounds.
Lipnikov, Konstantin; Agouzal, Abdellatif; Vassilevski, Yuri
2009-01-01
We present a new technology for generating meshes minimizing the interpolation and discretization errors or their gradients. The key element of this methodology is construction of a space metric from edge-based error estimates. For a mesh with N{sub h} triangles, the error is proportional to N{sub h}{sup -1} and the gradient of error is proportional to N{sub h}{sup -1/2} which are optimal asymptotics. The methodology is verified with numerical experiments.
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.
IPTV multicast with peer-assisted lossy error control
NASA Astrophysics Data System (ADS)
Li, Zhi; Zhu, Xiaoqing; Begen, Ali C.; Girod, Bernd
2010-07-01
Emerging IPTV technology uses source-specific IP multicast to deliver television programs to end-users. To provide reliable IPTV services over the error-prone DSL access networks, a combination of multicast forward error correction (FEC) and unicast retransmissions is employed to mitigate the impulse noises in DSL links. In existing systems, the retransmission function is provided by the Retransmission Servers sitting at the edge of the core network. In this work, we propose an alternative distributed solution where the burden of packet loss repair is partially shifted to the peer IP set-top boxes. Through Peer-Assisted Repair (PAR) protocol, we demonstrate how the packet repairs can be delivered in a timely, reliable and decentralized manner using the combination of server-peer coordination and redundancy of repairs. We also show that this distributed protocol can be seamlessly integrated with an application-layer source-aware error protection mechanism called forward and retransmitted Systematic Lossy Error Protection (SLEP/SLEPr). Simulations show that this joint PARSLEP/ SLEPr framework not only effectively mitigates the bottleneck experienced by the Retransmission Servers, thus greatly enhancing the scalability of the system, but also efficiently improves the resistance to the impulse noise.
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1994-01-01
The unequal error protection capabilities of convolutional and trellis codes are studied. In certain environments, a discrepancy in the amount of error protection placed on different information bits is desirable. Examples of environments which have data of varying importance are a number of speech coding algorithms, packet switched networks, multi-user systems, embedded coding systems, and high definition television. Encoders which provide more than one level of error protection to information bits are called unequal error protection (UEP) codes. In this work, the effective free distance vector, d, is defined as an alternative to the free distance as a primary performance parameter for UEP convolutional and trellis encoders. For a given (n, k), convolutional encoder, G, the effective free distance vector is defined as the k-dimensional vector d = (d(sub 0), d(sub 1), ..., d(sub k-1)), where d(sub j), the j(exp th) effective free distance, is the lowest Hamming weight among all code sequences that are generated by input sequences with at least one '1' in the j(exp th) position. It is shown that, although the free distance for a code is unique to the code and independent of the encoder realization, the effective distance vector is dependent on the encoder realization.
Progress in adaptive control of flexible spacecraft using lattice filters
NASA Technical Reports Server (NTRS)
Sundararajan, N.; Montgomery, R. C.
1985-01-01
This paper reviews the use of the least square lattice filter in adaptive control systems. Lattice filters have been used primarily in speech and signal processing, but they have utility in adaptive control because of their order-recursive nature. They are especially useful in dealing with structural dynamics systems wherein the order of a controller required to damp a vibration is variable depending on the number of modes significantly excited. Applications are presented for adaptive control of a flexible beam. Also, difficulties in the practical implementation of the lattice filter in adaptive control are discussed.
FAT-based adaptive sliding control for flexible arms: Theory and experiments
NASA Astrophysics Data System (ADS)
Haung, An-Chyau; Liao, Kuo-Kai
2006-11-01
An adaptive sliding controller is proposed in this paper for flexible arms containing time-varying uncertainties with unknown bounds based on function approximation technique (FAT). The uncertainties are firstly represented by finite linear combinations of orthonormal basis with some unknown constant weighting vectors. Output error dynamics can thus be derived as a stable first-order filter driven by parameter error vectors. Appropriate update laws for the weighting vectors are selected using the Lyapunov method so that asymptotic convergence of the output error can be proved as long as a sufficient number of basis functions are used. Effects of the approximation error on system performance are also investigated in this paper. Both computer simulation and experimental results confirm the feasibility of the proposed control strategy.
Mal-Adaptation of Event-Related EEG Responses Preceding Performance Errors
Eichele, Heike; Juvodden, Hilde T.; Ullsperger, Markus; Eichele, Tom
2010-01-01
Recent EEG and fMRI evidence suggests that behavioral errors are foreshadowed by systematic changes in brain activity preceding the outcome by seconds. In order to further characterize this type of error precursor activity, we investigated single-trial event-related EEG activity from 70 participants performing a modified Eriksen flanker task, in particular focusing on the trial-by-trial dynamics of a fronto-central independent component that previously has been associated with error and feedback processing. The stimulus-locked peaks in the N2 and P3 latency range in the event-related averages showed expected compatibility and error-related modulations. In addition, a small pre-stimulus negative slow wave was present at erroneous trials. Significant error-preceding activity was found in local stimulus sequences with decreased conflict in the form of less negativity at the N2 latency (310–350 ms) accumulating across five trials before errors; concomitantly response times were speeding across trials. These results illustrate that error-preceding activity in event-related EEG is associated with the performance monitoring system and we conclude that the dynamics of performance monitoring contribute to the generation of error-prone states in addition to the more remote and indirect effects in ongoing activity such as posterior alpha power in EEG and default mode drifts in fMRI. PMID:20740080
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.
Reducing Pointing Errors During Cassini Reaction Control System Orbit Trim Maneuvers
NASA Technical Reports Server (NTRS)
Rizvi, Farheen
2013-01-01
The effect of altering a gain parameter in the Cassini reaction control system (RCS) delta-V controller on the maneuver execution errors during orbit trim maneuvers (OTMs) is explored. Cassini consists of two reaction control thruster branches (A & B) each with eight thrusters. Currently, the B-branch is operational while the A-branch serves as a back-up. The four Z-thrusters control the X and Y-axes, while the four Y-thrusters control the Z-axis. During an OTM, the Z-thrusters fire to maintain the X and Y-axes pointing within an attitude control dead-zone (-10 to 10 milliradians). The errors do not remain at zero due to pointing error sources such as spacecraft center of mass offset from the geometric center of the Z-facing thrusters, and variability in the thruster forces due to the thruster hardware differences. The delta-V reaction control system (RCS) controller ensures that the attitude error remains within this dead-zone. Gain parameters within the RCS delta-V controller affect the maneuver execution errors. Different parameter values are used to explore effect on these errors. It is found that pointing error decreases and magnitude error increases rapidly for gain parameters 10 times greater than the current parameter values used in the flight software.
Long, Lijun; Zhao, Jun
2015-07-01
This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.
Learning from adaptive neural network output feedback control of a unicycle-type mobile robot.
Zeng, Wei; Wang, Qinghui; Liu, Fenglin; Wang, Ying
2016-03-01
This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs.
NASA Astrophysics Data System (ADS)
Huo, Baoyu; Tong, Shaocheng; Li, Yongming
2013-12-01
This article develops an adaptive fuzzy control method for accommodating actuator faults in a class of unknown nonlinear systems with unmeasured states. The considered faults are modelled as both loss of effectiveness and lock-in-place (stuck at unknown place). With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive observer is developed for estimating the unmeasured states. Combining the backstepping technique with the nonlinear tolerant-fault control theory, a novel adaptive fuzzy faults-tolerant control approach is constructed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded and the tracking error between the system output and the reference signal converges to a small neighbourhood of zero by appropriate choice of the design parameters. Simulation results are provided to show the effectiveness of the control approach.
Robust adaptive self-structuring fuzzy control design for nonaffine, nonlinear systems
NASA Astrophysics Data System (ADS)
Chen, Pin-Cheng; Wang, Chi-Hsu; Lee, Tsu-Tian
2011-01-01
In this article, a robust adaptive self-structuring fuzzy control (RASFC) scheme for the uncertain or ill-defined nonlinear, nonaffine systems is proposed. The RASFC scheme is composed of a robust adaptive controller and a self-structuring fuzzy controller. In the self-structuring fuzzy controller design, a novel self-structuring fuzzy system (SFS) is used to approximate the unknown plant nonlinearity, and the SFS can automatically grow and prune fuzzy rules to realise a compact fuzzy rule base. The robust adaptive controller is designed to achieve an L 2 tracking performance to stabilise the closed-loop system. This L 2 tracking performance can provide a clear expression of tracking error in terms of the sum of lumped uncertainty and external disturbance, which has not been shown in previous works. Finally, five examples are presented to show that the proposed RASFC scheme can achieve favourable tracking performance, yet heavy computational burden is relieved.
ERIC Educational Resources Information Center
Rigoni, Davide; Wilquin, Helene; Brass, Marcel; Burle, Boris
2013-01-01
The belief that one can exert intentional control over behavior is deeply rooted in virtually all human beings. It has been shown that weakening such belief--e.g. by exposure to "anti-free will" messages--can lead people to display antisocial tendencies. We propose that this cursory and irresponsible behavior may be facilitated by a breakdown of…
Adaptive Control of Visually Guided Grasping in Neural Networks
1990-03-12
U01ITU S.WM NONnumsen Adaptive Control of Visually Guided Grasping in Neural Networks AFOSR-89-&CO030 88-NL-209 L AUTHOrSF 2313/A8 00 61102F (V) Dr...FINAL REPORT ADAPTIVE CONTROL OF VISUALLY GUIDED GRASPING IN NEURAL NETWORKS Neurogen Laboratories Inc. Project Summary Research performed for AFOSR...arm’s length in position and 6 degrees in orientation. Keywords: Neural Networks , Adaptive Motor Control, Sensory-Motor sensation Introduction The human
Simulation of Spacecraft Damage Tolerance and Adaptive Controls
2013-06-01
operator. Limitations of current technology abounded, leaving the X-15 with a successful, but severely limited adaptive control system. Since then...many limitations have fallen away, allowing for the first time employment of adaptive controls on a large scale. The nature of adaptive controls, or...THIS PAGE Unclassified 19. SECURITY CLASSIFICATION OF ABSTRACT Unclassified 20. LIMITATION OF ABSTRACT UU NSN 7540–01–280–5500 Standard Form
Polarimeter calibration error gets far out of control
NASA Astrophysics Data System (ADS)
Chipman, Russell A.
2015-09-01
This is a sad story about a polarization calibration error gone amuck. A simple laboratory mistake was mistaken for a new phenomena. Aggressive management did their job and sold the flawed idea very effectively and substantial funding followed. Questions were raised and a Government lab tried but couldn't to recreate the breakthrough. The results were unpleasant and the field of infrared polarimetry developed a bad reputation for several years.
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.
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.
Robust control for a biaxial servo with time delay system based on adaptive tuning technique.
Chen, Tien-Chi; Yu, Chih-Hsien
2009-07-01
A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.
Adaptive servo control for umbilical mating
NASA Technical Reports Server (NTRS)
Zia, Omar
1988-01-01
Robotic applications at Kennedy Space Center are unique and in many cases require the fime positioning of heavy loads in dynamic environments. Performing such operations is beyond the capabilities of an off-the-shelf industrial robot. Therefore Robotics Applications Development Laboratory at Kennedy Space Center has put together an integrated system that coordinates state of the art robotic system providing an excellent easy to use testbed for NASA sensor integration experiments. This paper reviews the ways of improving the dynamic response of the robot operating under force feedback with varying dynamic internal perturbations in order to provide continuous stable operations under variable load conditions. The goal is to improve the stability of the system with force feedback using the adaptive control feature of existing system over a wide range of random motions. The effect of load variations on the dynamics and the transfer function (order or values of the parameters) of the system has been investigated, more accurate models of the system have been determined and analyzed.
NASA Technical Reports Server (NTRS)
Sargent, Jeff Scott
1988-01-01
A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.
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.
Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems
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.
Synthetic consciousness: the distributed adaptive control perspective.
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'.
Optical Beam Control Using Adaptive Optics
2005-12-01
30 1. Principles of Operation......................................................................31 VI. USING ZERNIKE POLYNOMIALS TO...help patience in helping me to understand the underlying principles of optics. xiv THIS PAGE INTENTIONALLY...correct this using adaptive optics. Adaptive Optics first got its start in 215 AD with the destruction of the Roman Fleet by Archimedes (Lamberson
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.
Takemura, Aya; Ofuji, Tomoyo; Miura, Kenichiro; Kawano, Kenji
2017-01-01
To adapt to variable environments, humans regulate their behavior by modulating gains in sensory-to-motor processing. In this study, we measured a simple eye movement, the ocular following response (OFR), in monkeys to study the neuronal basis of adaptive motor learning in the visuomotor processing stream. The medial superior temporal (MST) area of the cerebral cortex is a critical site for contextual gain modulation of the OFR. However, the role of MST neurons in adaptive gain modulation of the OFR remains unknown. We adopted a velocity step-down sequence paradigm that was designed to promote adaptive gain modulation of the OFR to investigate the role of the dorsal MST (MSTd) in adaptive motor learning. In the initial learning stage, we observed a reduction in the OFR but no significant change in the “open-loop” responses for the majority of the MSTd neurons. However, in the late learning stage, some MSTd neurons exhibited significantly enhanced “closed-loop” responses in association with increases in retinal error velocity. These results indicate that the MSTd area primarily encodes visual motion, suggesting that MSTd neurons function upstream of the motor learning site to provide sensory signals to the downstream structures involved in adaptive motor learning. PMID:28102342
Adaptive neuro-control for large flexible structures
NASA Astrophysics Data System (ADS)
Krishna Kumar, K.; Montgomery, L.
1992-12-01
Special problems related to control system design for large flexible structures include the inherent low damping, wide range of modal frequencies, unmodeled dynamics, and possibility of system failures. Neuro-control, which combines concepts from artificial neural networks and adaptive control is investigated as a solution to some of these problems. Specifically, the roles of neutro-controllers in learning unmodeled dynamics and adaptive control for system failures are investigated. The neuro-controller synthesis procedure and its capabilities in adaptively controlling the structure are demonstrated using a mathematical model of an existing structure, the advanced control evaluation for systems test article located at NASA/Marshall Space Flight Center. Also, the real-time adaptive capability of neuro-controllers is demonstrated via an experiment utilizing a flexible clamped-free beam equipped with an actuator that uses a bang-bang controller.
Neural self-tuning adaptive control of non-minimum phase system
NASA Technical Reports Server (NTRS)
Ho, Long T.; Bialasiewicz, Jan T.; Ho, Hai 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.
Residual-based Methods for Controlling Discretization Error in CFD
2015-08-24
Jackson, PhD (expected, 2017) William Tyson, PhD (expected 2018) I. Introduction Computational Fluid Dynamics (CFD) has enormous potential to...are not included for the approximate TE method as the DE estimates were much worse than the rest. X. Mesh Adaptation Introduction Performing...Computational Physics, October 2014. 2. J. M. Derlaga, T. S. Phillips, and C. J. Roy, “SENSEI Computational Fluid Dynamics Code: A Case Study in Modern
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.
Error Control Coding Techniques for Space and Satellite Communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.; Cabral, Hermano A.; He, Jiali
1997-01-01
Bootstrap Hybrid Decoding (BHD) (Jelinek and Cocke, 1971) is a coding/decoding scheme that adds extra redundancy to a set of convolutionally encoded codewords and uses this redundancy to provide reliability information to a sequential decoder. Theoretical results indicate that bit error probability performance (BER) of BHD is close to that of Turbo-codes, without some of their drawbacks. In this report we study the use of the Multiple Stack Algorithm (MSA) (Chevillat and Costello, Jr., 1977) as the underlying sequential decoding algorithm in BHD, which makes possible an iterative version of BHD.
Simultaneous control of error rates in fMRI data analysis.
Kang, Hakmook; Blume, Jeffrey; Ombao, Hernando; Badre, David
2015-12-01
The key idea of statistical hypothesis testing is to fix, and thereby control, the Type I error (false positive) rate across samples of any size. Multiple comparisons inflate the global (family-wise) Type I error rate and the traditional solution to maintaining control of the error rate is to increase the local (comparison-wise) Type II error (false negative) rates. However, in the analysis of human brain imaging data, the number of comparisons is so large that this solution breaks down: the local Type II error rate ends up being so large that scientifically meaningful analysis is precluded. Here we propose a novel solution to this problem: allow the Type I error rate to converge to zero along with the Type II error rate. It works because when the Type I error rate per comparison is very small, the accumulation (or global) Type I error rate is also small. This solution is achieved by employing the likelihood paradigm, which uses likelihood ratios to measure the strength of evidence on a voxel-by-voxel basis. In this paper, we provide theoretical and empirical justification for a likelihood approach to the analysis of human brain imaging data. In addition, we present extensive simulations that show the likelihood approach is viable, leading to "cleaner"-looking brain maps and operational superiority (lower average error rate). Finally, we include a case study on cognitive control related activation in the prefrontal cortex of the human brain.
NASA Astrophysics Data System (ADS)
Jin, Xiao-Zheng; Yang, Guang-Hong
2011-03-01
In this article, a robust tracking control problem of a class of dynamical complex networks is presented through a distributed adaptive approach. Uncertain network topology with unknown coupling strength, delayed and perturbed communications and external disturbances are considered, while the bounds of channel noises and coupling delays and disturbances are assumed to be unknown. Adaptation laws are proposed to estimate the network coupling strength and the upper and lower bounds of communication state errors and disturbances on-line. Based on the information from adaptive schemes, a class of distributed robust adaptive controllers is constructed to automatically compensate for the imperfect network and disturbance effects. Then, according to the Lyapunov stability theory, it is shown that the achievement of tracking for complex networks is effective on imperfect communications and disturbances. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of an F-18 aircraft.
Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.
Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong
2015-03-01
This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Zhou, Zhen-Lei; Mosier, Gary E.
1993-01-01
This paper presents the design of a joint-space adaptive control scheme for controlling the slave arm motion of a dual-arm telerobot system developed at Goddard Space Flight Center (GSFC) to study telerobotic operations in space. Each slave arm of the dual-arm system is a kinematically redundant manipulator with seven degrees of freedom (DOF). Using the concept of model reference adaptive control (MRAC) and Liupunov direct method, we derive an adaptation algorithm that adjusts the PD controller gains of the control scheme. The development of the adaptive control scheme assumes that the slave arm motion is non-compliant and slowly varying. The implementation of the derived control scheme does not require the computation of manipulator dynamics which makes the control scheme sufficiently fast for real-time applications. Computer simulation study performed for the 7-DOF slave arm shows that the developed control scheme can efficiently adapt to sudden change in payload while tracking various test trajectories such as ramp or sinusoids with negligible position errors.
Adaptive Fuzzy Tracking Control for a Class of MIMO Nonlinear Systems in Nonstrict-Feedback Form.
Chen, Bing; Lin, Chong; Liu, Xiaoping; Liu, Kefu
2015-12-01
This paper focuses on the problem of fuzzy adaptive control for a class of multiinput and multioutput (MIMO) nonlinear systems in nonstrict-feedback form, which contains the strict-feedback form as a special case. By the condition of variable partition, a new fuzzy adaptive backstepping is proposed for such a class of nonlinear MIMO systems. The suggested fuzzy adaptive controller guarantees that the proposed control scheme can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking errors eventually converge to a small neighborhood around the origin. The main advantage of this paper is that a control approach is systematically derived for nonlinear systems with strong interconnected terms which are the functions of all states of the whole system. Simulation results further illustrate the effectiveness of the suggested approach.
NASA Astrophysics Data System (ADS)
Martin, O. A.; Gendron, É.; Rousset, G.; Gratadour, D.; Vidal, F.; Morris, T. J.; Basden, A. G.; Myers, R. M.; Correia, C. M.; Henry, D.
2017-01-01
Context. Canary is the multi-object adaptive optics (MOAO) on-sky pathfinder developed in the perspective of multi-object spectrograph on extremely large telescopes (ELTs). In 2013, Canary was operated on-sky at the William Herschel telescope (WHT), using three off-axis natural guide stars (NGS) and four off-axis Rayleigh laser guide stars (LGS), in open-loop, with the on-axis compensated turbulence observed with a H-band imaging camera and a Truth wave-front sensor (TS) for diagnostic purposes. Aims: Our purpose is to establish a reliable and accurate wave-front error breakdown for LGS MOAO. This will enable a comprehensive analysis of Canary on-sky results and provide tools for validating simulations of MOAO systems for ELTs. Methods: To evaluate the MOAO performance, we compared the Canary on-sky results running in MOAO, in single conjugated adaptive optics (SCAO) and in ground layer adaptive optics (GLAO) modes, over a large set of data acquired in 2013. We provide a statistical study of the seeing. We also evaluated the wave-front error breakdown from both analytic computations, one based on a MOAO system modelling and the other on the measurements from the Canary TS. We have focussed especially on the tomographic error and we detail its vertical error decomposition. Results: We show that Canary obtained 30.1%, 21.4% and 17.1% H-band Strehl ratios in SCAO, MOAO and GLAO respectively, for median seeing conditions with 0.66'' of total seeing including 0.59'' at the ground. Moreover, we get 99% of correlation over 4500 samples, for any AO modes, between two analytic computations of residual phase variance. Based on these variances, we obtain a reasonable Strehl-ratio (SR) estimation when compared to the measured IR image SR. We evaluate the gain in compensation for the altitude turbulence brought by MOAO when compared to GLAO.
Error Control Coding Techniques for Space and Satellite Communications
NASA Technical Reports Server (NTRS)
Lin, Shu
2000-01-01
This paper presents a concatenated turbo coding system in which a Reed-Solomom outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft-decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1995-01-01
This report focuses on the results obtained during the PI's recent sabbatical leave at the Swiss Federal Institute of Technology (ETH) in Zurich, Switzerland, from January 1, 1995 through June 30, 1995. Two projects investigated various properties of TURBO codes, a new form of concatenated coding that achieves near channel capacity performance at moderate bit error rates. The performance of TURBO codes is explained in terms of the code's distance spectrum. These results explain both the near capacity performance of the TURBO codes and the observed 'error floor' for moderate and high signal-to-noise ratios (SNR's). A semester project, entitled 'The Realization of the Turbo-Coding System,' involved a thorough simulation study of the performance of TURBO codes and verified the results claimed by previous authors. A copy of the final report for this project is included as Appendix A. A diploma project, entitled 'On the Free Distance of Turbo Codes and Related Product Codes,' includes an analysis of TURBO codes and an explanation for their remarkable performance. A copy of the final report for this project is included as Appendix B.
Adaptive and Optimal Control of Stochastic Dynamical Systems
2015-09-14
control and stochastic differential games . Stochastic linear-quadratic, continuous time, stochastic control problems are solved for systems with noise...control problems for systems with arbitrary correlated n 15. SUBJECT TERMS Adaptive control, optimal control, stochastic differential games 16. SECURITY...explicit results have been obtained for problems of stochastic control and stochastic differential games . Stochastic linear- quadratic, continuous time
Adaptive Control Techniques for Large Space Structures
1989-01-06
Point Analy- sis", submitted, IEEE Trans. on Circuits and Systems; Special Issue on Adaptive Systems, Sept. 1987. I.M.Y. Mareels, R.R. Bitmead, M. Gevers...adaptive system with unmodelled dynamics," Proc. IFAC Workshop on Adaptive Systems, San Francisco, CA. C.A. Desoer , R.W. Liu, J. Murray and R. Sacks...June 1980. C.A. Desoer and M. Vidyasagar, Feedback Systems: Input-Output Properties, Academic Press, * 1975. J.C. Doyle and G. Stein (1981
Pulse front control with adaptive optics
NASA Astrophysics Data System (ADS)
Sun, B.; Salter, P. S.; Booth, M. J.
2016-03-01
The focusing of ultrashort laser pulses is extremely important for processes including microscopy, laser fabrication and fundamental science. Adaptive optic elements, such as liquid crystal spatial light modulators or membrane deformable mirrors, are routinely used for the correction of aberrations in these systems, leading to improved resolution and efficiency. Here, we demonstrate that adaptive elements used with ultrashort pulses should not be considered simply in terms of wavefront modification, but that changes to the incident pulse front can also occur. We experimentally show how adaptive elements may be used to engineer pulse fronts with spatial resolution.
Method for removing tilt control in adaptive optics systems
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)
Method for removing tilt control in adaptive optics systems
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.
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.
NASA Astrophysics Data System (ADS)
Sakimura, Naohide; Ohashi, Takahiro; Ohishi, Kiyoshi; Miyazaki, Toshimasa
2014-09-01
Recently, the scaling up of the storage capacity and data transfer rate of digital storage media has been required. However, increasing in the storage capacity and transfer rate makes optical head control more difficult. Thus, a tracking control system for optical discs must exhibit a high degree of precision control. Consequently, a new two-stage feedforward control (TSFFC) system for high-precision control is proposed in this paper. The proposed system is constructed using two zero phase error tracking (ZPET) control systems based on error prediction and an error-based disturbance observer (EDOB) that uses a notch filter to suppress non periodic disturbances. The proposed control system is designed for DDU-1000 for digital versatile discs (DVDs). The experimental results demonstrate that the proposed system effectively suppresses tracking errors.
Fractional adaptive control for an automatic voltage regulator.
Aguila-Camacho, Norelys; Duarte-Mermoud, Manuel A
2013-11-01
This paper presents the application of a direct Fractional Order Model Reference Adaptive Controller (FOMRAC) to an Automatic Voltage Regulator (AVR). A direct FOMRAC is a direct Model Reference Adaptive Control (MRAC), whose controller parameters are adjusted using fractional order differential equations. Four realizations of the FOMRAC were designed in this work, each one considering different orders for the plant model. The design procedure consisted of determining the optimal values of the fractional order and the adaptive gains for each adaptive law, using Genetic algorithm optimization. Comparisons were made among the four FOMRAC designs, a fractional order PID (FOPID), a classical PID, and four Integer Order Model Reference Adaptive Controllers (IOMRAC), showing that the FOMRAC can improve the controlled system behavior and its robustness with respect to model uncertainties. Finally, some performance indices are presented here for the controlled schemes, in order to show the advantages and disadvantages of the FOMRAC.
An adaptive controller for enhancing operator performance during teleoperation
NASA Technical Reports Server (NTRS)
Carignan, Craig R.; Tarrant, Janice M.; Mosier, Gary E.
1989-01-01
An adaptive controller is developed for adjusting robot arm parameters while manipulating payloads of unknown mass and inertia. The controller is tested experimentally in a master/slave configuration where the adaptive slave arm is commanded via human operator inputs from a master. Kinematically similar six-joint master and slave arms are used with the last three joints locked for simplification. After a brief initial adaptation period for the unloaded arm, the slave arm retrieves different size payloads and maneuvers them about the workspace. Comparisons are then drawn with similar tasks where the adaptation is turned off. Several simplifications of the controller dynamics are also addressed and experimentally verified.
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.
High-accuracy wavefront control for retinal imaging with Adaptive-Influence-Matrix Adaptive Optics
Zou, Weiyao; Burns, Stephen A.
2010-01-01
We present an iterative technique for improving adaptive optics (AO) wavefront correction for retinal imaging, called the Adaptive-Influence-Matrix (AIM) method. This method is based on the fact that the deflection-to-voltage relation of common deformable mirrors used in AO are nonlinear, and the fact that in general the wavefront errors of the eye can be considered to be composed of a static, non-zero wavefront error (such as the defocus and astigmatism), and a time-varying wavefront error. The aberrated wavefront is first corrected with a generic influence matrix, providing a mirror compensation figure for the static wavefront error. Then a new influence matrix that is more accurate for the specific static wavefront error is calibrated based on the mirror compensation figure. Experimental results show that with the AIM method the AO wavefront correction accuracy can be improved significantly in comparison to the generic AO correction. The AIM method is most useful in AO modalities where there are large static contributions to the wavefront aberrations. PMID:19997241
Adaptive controller for a needle free jet-injector system.
Modak, Ashin; Hogan, N Catherine; Hunter, Ian W
2015-01-01
A nonlinear, sliding mode adaptive controller was created for a needle-free jet injection system. The controller was based on a simplified lumped-sum parameter model of the jet-injection mechanics. The adaptive control scheme was compared to a currently-used Feed-forward+PID controller in both ejection of water into air, and injection of dye into ex-vivo porcine tissue. The adaptive controller was more successful in trajectory tracking and was more robust to the biological variations caused by a tissue load.
Sense of Control and Career Adaptability among Undergraduate Students
ERIC Educational Resources Information Center
Duffy, Ryan D.
2010-01-01
The current study examined the direct relation of sense of control to career adaptability, as well as its ability to function as a mediator for other established predictors, with a sample of 1,991 undergraduate students. Students endorsing a greater sense of personal control were more likely to view themselves as adaptable to the world of work.…
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1992-01-01
Worked performed during the reporting period is summarized. Construction of robustly good trellis codes for use with sequential decoding was developed. The robustly good trellis codes provide a much better trade off between free distance and distance profile. The unequal error protection capabilities of convolutional codes was studied. The problem of finding good large constraint length, low rate convolutional codes for deep space applications is investigated. A formula for computing the free distance of 1/n convolutional codes was discovered. Double memory (DM) codes, codes with two memory units per unit bit position, were studied; a search for optimal DM codes is being conducted. An algorithm for constructing convolutional codes from a given quasi-cyclic code was developed. Papers based on the above work are included in the appendix.
Deep space communications, weather effects, and error control
NASA Technical Reports Server (NTRS)
Posner, Edward C.
1989-01-01
Deep space telemetry is and will remain signal-to-noise limited and vulnerable to interference. A need exists to increase received signal power and decrease noise. This includes going to Ka-band in the mid-1990's to increase directivity. The effects of a wet atmosphere can increase the noise temperature by a factor of 5 or more, even at X-band, but the order of magnitude increase in average data rate obtainable at Ka-band relative to X-band makes the increased uncertainty a good trade. Lowbit error probabilities required by data compression are available both theoretically and practically with coding, at an infinitesimal power penalty rather than the 10 to 15 dB more power required to reduce error probabilities without coding. Advances are coming rapidly in coding, as with the new constraint-length 15 rate 1/4 convolutional code concatenated with the already existing Reed-Solomon code to be demonstrated on Galileo. In addition, high density spacecraft data storage will allow selective retransmissions, even from the edge of the Solar System, to overcome weather effects. In general, deep space communication was able to operate, and will continue to operate, closer to theoretical limits than any other form of communication. These include limits in antenna area and directivity, system noise temperature, coding efficiency, and everything else. The deep space communication links of the mid-90's and beyond will be compatible with new instruments and compression algorithms and represent a sensible investment in an overall end-to-end information system design.
Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles
NASA Astrophysics Data System (ADS)
Krishnamoorthy, Kiruthika
Trajectory tracking is a critical element for the better functionality of autonomous vehicles. The main objective of this research study was to implement and analyze L1 adaptive control laws for autonomous flight under normal and upset flight conditions. The West Virginia University (WVU) Unmanned Aerial Vehicle flight simulation environment was used for this purpose. A comparison study between the L1 adaptive controller and a baseline conventional controller, which relies on position, proportional, and integral compensation, has been performed for a reduced size jet aircraft, the WVU YF-22. Special attention was given to the performance of the proposed control laws in the presence of abnormal conditions. The abnormal conditions considered are locked actuators (stabilator, aileron, and rudder) and excessive turbulence. Several levels of abnormal condition severity have been considered. The performance of the control laws was assessed over different-shape commanded trajectories. A set of comprehensive evaluation metrics was defined and used to analyze the performance of autonomous flight control laws in terms of control activity and trajectory tracking errors. The developed L1 adaptive control laws are supported by theoretical stability guarantees. The simulation results show that L1 adaptive output feedback controller achieves better trajectory tracking with lower level of control actuation as compared to the baseline linear controller under nominal and abnormal conditions.
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.
Make no mistake—errors can be controlled*
Hinckley, C
2003-01-01
Traditional quality control methods identify "variation" as the enemy. However, the control of variation by itself can never achieve the remarkably low non-conformance rates of world class quality leaders. Because the control of variation does not achieve the highest levels of quality, an inordinate focus on these techniques obscures key quality improvement opportunities and results in unnecessary pain and suffering for patients, and embarrassment, litigation, and loss of revenue for healthcare providers. Recent experience has shown that mistakes are the most common cause of problems in health care as well as in other industrial environments. Excessive product and process complexity contributes to both excessive variation and unnecessary mistakes. The best methods for controlling variation, mistakes, and complexity are each a form of mistake proofing. Using these mistake proofing techniques, virtually every mistake and non-conformance can be controlled at a fraction of the cost of traditional quality control methods. PMID:14532368
NASA Astrophysics Data System (ADS)
Zhang, Yangming; Yan, Peng
2016-12-01
This paper investigates a systematic modeling and control methodology for a multi-axis PZT (piezoelectric transducer) actuated servo stage supporting nano-manipulations. A sliding mode disturbance observer-based adaptive integral backstepping control method with an estimated inverse model compensation scheme is proposed to achieve ultra high precision tracking in the presence of the hysteresis nonlinearities, model uncertainties, and external disturbances. By introducing a time rate of the input signal, an enhanced rate-dependent Prandtl-Ishlinskii model is developed to describe the hysteresis behaviors, and its inverse is also constructed to mitigate their adverse effects. In particular, the corresponding inverse compensation error is analyzed and its boundedness is proven. Subsequently, the sliding mode disturbance observer-based adaptive integral backstepping controller is designed to guarantee the convergence of the tracking error, where the sliding mode disturbance observer can track the total disturbances in a finite time, while the integral action is incorporated into the adaptive backstepping design to improve the steady-state control accuracy. Finally, real time implementations of the proposed algorithm are applied on the PZT actuated servo system, where excellent tracking performance with tracking precision error around 6‰ for circular contour tracking is achieved in the experimental results.
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.
NASA Astrophysics Data System (ADS)
Cohen, Avi; Lange, Falk; Ben-Zvi, Guy; Graitzer, Erez; Vladimir, Dmitriev
2012-11-01
The ITRS roadmap specifies wafer overlay control as one of the major tasks for the sub 40 nm nodes in addition to CD control and defect control. Wafer overlay is strongly dependent on mask image placement error (registration errors or Reg errors)1. The specifications for registration or mask placement accuracy are significantly tighter in some of the double patterning techniques (DPT). This puts a heavy challenge on mask manufacturers (mask shops) to comply with advanced node registration specifications. The conventional methods of feeding back the systematic registration error to the E-beam writer and re-writing the mask are becoming difficult, expensive and not sufficient for the advanced nodes especially for double pattering technologies. Six production masks were measured on a standard registration metrology tool and the registration errors were calculated and plotted. Specially developed algorithm along with the RegC Wizard (dedicated software) was used to compute a correction lateral strain field that would minimize the registration errors. This strain field was then implemented in the photomask bulk material using an ultra short pulse laser based system. Finally the post process registration error maps were measured and the resulting residual registration error field with and without scale and orthogonal errors removal was calculated. In this paper we present a robust process flow in the mask shop which leads up to 32% registration 3sigma improvement, bringing some out-of-spec masks into spec, utilizing the RegC® process in the photomask periphery while leaving the exposure field optically unaffected.
Adaptive sliding mode control for a class of chaotic systems
NASA Astrophysics Data System (ADS)
Farid, R.; Ibrahim, A.; Zalam, B.
2015-03-01
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.
Dynamics modeling and adaptive control of flexible manipulators
NASA Technical Reports Server (NTRS)
Sasiadek, J. Z.
1991-01-01
An application of Model Reference Adaptive Control (MRAC) to the position and force control of flexible manipulators and robots is presented. A single-link flexible manipulator is analyzed. The problem was to develop a mathematical model of a flexible robot that is accurate. The objective is to show that the adaptive control works better than 'conventional' systems and is suitable for flexible structure control.
Adaptive sliding mode control for a class of chaotic systems
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.
Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.
Piatrou, Piotr; Gilles, Luc
2005-02-20
Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.
Analysis of Covariance with Linear Regression Error Model on Antenna Control Unit Tracking
2015-10-20
412TW-PA-15238 Analysis of Covariance with Linear Regression Error Model on Antenna Control Unit Tracking DANIEL T. LAIRD AIR...COVERED (From - To) 20 OCT 15 – 23 OCT 15 4. TITLE AND SUBTITLE Analysis of Covariance with Linear Regression Error Model on Antenna Control Tracking...analysis of variance (ANOVA) to decide for the null- or alternative-hypotheses of a telemetry antenna control unit’s (ACU) ability to track on C-band
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.
NASA Astrophysics Data System (ADS)
Li, Yuan; Lv, Hui; Jiao, Dongxiu
2017-03-01
In this study, an adaptive neural network synchronization (NNS) approach, capable of guaranteeing prescribed performance (PP), is designed for non-identical fractional-order chaotic systems (FOCSs). For PP synchronization, we mean that the synchronization error converges to an arbitrary small region of the origin with convergence rate greater than some function given in advance. Neural networks are utilized to estimate unknown nonlinear functions in the closed-loop system. Based on the integer-order Lyapunov stability theorem, a fractional-order adaptive NNS controller is designed, and the PP can be guaranteed. Finally, simulation results are presented to confirm our results.
Application of parameter estimation to aircraft stability and control: The output-error approach
NASA Technical Reports Server (NTRS)
Maine, Richard E.; Iliff, Kenneth W.
1986-01-01
The practical application of parameter estimation methodology to the problem of estimating aircraft stability and control derivatives from flight test data is examined. The primary purpose of the document is to present a comprehensive and unified picture of the entire parameter estimation process and its integration into a flight test program. The document concentrates on the output-error method to provide a focus for detailed examination and to allow us to give specific examples of situations that have arisen. The document first derives the aircraft equations of motion in a form suitable for application to estimation of stability and control derivatives. It then discusses the issues that arise in adapting the equations to the limitations of analysis programs, using a specific program for an example. The roles and issues relating to mass distribution data, preflight predictions, maneuver design, flight scheduling, instrumentation sensors, data acquisition systems, and data processing are then addressed. Finally, the document discusses evaluation and the use of the analysis results.
Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks
Pedrocchi, Alessandra; Ferrante, Simona; De Momi, Elena; Ferrigno, Giancarlo
2006-01-01
Background The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required. Methods The error mapping controller (EMC) here proposed uses artificial neural networks (ANNs) both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID) included in an anti wind-up scheme (called PIDAW) and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID). In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out. Results The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances. Conclusion Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice. PMID:17029636
Multiple Model Parameter Adaptive Control for In-Flight Simulation.
1988-03-01
dynamics of an aircraft. The plant is control- lable by a proportional-plus-integral ( PI ) control law. This section describes two methods of calculating...adaptive model-following PI control law [20-24]. The control law bases its control gains upon the parameters of a linear difference equation model which
Adaptive artificial neural network for autonomous robot control
NASA Technical Reports Server (NTRS)
Arras, Michael K.; Protzel, Peter W.; Palumbo, Daniel L.
1992-01-01
The topics are presented in viewgraph form and include: neural network controller for robot arm positioning with visual feedback; initial training of the arm; automatic recovery from cumulative fault scenarios; and error reduction by iterative fine movements.
Adaptive control of rigid-link electrically-driven robots actuated with brushless DC motors
Bridges, M.M.; Dawson, D.M.
1994-12-31
In this paper, we extend the work of [1] and [2] to design an adaptive controller for rigid-link electrically-driven (RLED) robot manipulators specifically actuated with Brushless Direct Current (BLDC) motors. In particular the adaptive controller presented is tailored to handle the multi-link dynamics of a rigid-link robot as opposed to a simple inertial load. Furthermore, the linear electrical dynamics of brushed DC motors used in the development of [1], are replaced with the multiple input nonlinear dynamics of BLDC motors. The result is an adaptive controller that guarantees globally asymptotic convergence of the link position tracking error in spite of parametric uncertainty throughout the entire electro-mechanical model.
Robust adaptive tracking control of MIMO nonlinear systems in the presence of actuator hysteresis
NASA Astrophysics Data System (ADS)
Fu, Guiyuan; Ou, Linlin; Zhang, Weidong
2016-07-01
Adaptive tracking control of a class of MIMO nonlinear system preceded by unknown hysteresis is investigated. Based on dynamic surface control, an adaptive robust control law is developed and compensators are designed to mitigate the influences of both the unknown bounded external uncertainties and the unknown Prandtl-Islinskii hysteresis. By adopting the low-pass filters, the explosion of complexity caused by tedious computation of the time derivatives of the virtual control laws is overcome. With the proposed control scheme, the closed-loop system is proved to be semi-globally ultimately bounded by the Lyapunov stability theory, and the output of the controlled system can track the desired trajectories with an arbitrarily small error. Finally, numerical simulations are given to verify the effectiveness of the proposed approach.
Adaptive control of a flexible beam using least square lattice filters
NASA Technical Reports Server (NTRS)
Sundararajan, N.; Montgomery, R. C.
1983-01-01
This paper presents an indirect adaptive control scheme for the control of flexible structures using recursive least square lattice filters. The identification scheme uses lattice filters which provide an on-line estimate of the number of modes, mode shapes and modal amplitudes. These modes are coupled and a transformation to decouple them in order to obtain the natural modes is presented. The decoupled modal amplitude time series are then used in an equation error identification scheme to identify the model parameters in an autoregressive moving average (ARMA) form. The control is based on modal pole placement scheme with the objective of vibration suppression. The control gains are calculated based on the identified ARMA parameters. Before using the identified parameters for control, detailed testing and validation procedures are carried out on the identified parameters. The full adaptive control scheme is demonstrated using the simulation for the 12 foot free-free beam apparatus at NASA Langley Research Center.
Adaptive containment control of nonlinear multi-agent systems with non-identical agents
NASA Astrophysics Data System (ADS)
Haghshenas, Hamed; Badamchizadeh, Mohammad Ali; Baradarannia, Mahdi
2015-08-01
This paper addresses the containment control problem for a group of non-identical agents, where the dynamics of agents are supposed to be nonlinear with unknown parameters and parameterised by some functions. In controller design approach for each follower, adaptive control and Lyapunov theory are utilised as the main control strategies to guarantee the convergence of all non-identical followers to the dynamic convex hull formed by the leaders. The design of distributed adaptive controllers is based on the exchange of neighbourhood errors among the agents. For analysis of containment control problem, a new formulation has been developed using M-matrices. The validity of theoretical results are demonstrated through an example.
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.
Maity, Arnab; Hocht, Leonhard; Heise, Christian; Holzapfel, Florian
2016-11-28
A new efficient adaptive optimal control approach is presented in this paper based on the indirect model reference adaptive control (MRAC) architecture for improvement of adaptation and tracking performance of the uncertain system. The system accounts here for both matched and unmatched unknown uncertainties that can act as plant as well as input effectiveness failures or damages. For adaptation of the unknown parameters of these uncertainties, the frequency selective learning approach is used. Its idea is to compute a filtered expression of the system uncertainty using multiple filters based on online instantaneous information, which is used for augmentation of the update law. It is capable of adjusting a sudden change in system dynamics without depending on high adaptation gains and can satisfy exponential parameter error convergence under certain conditions in the presence of structured matched and unmatched uncertainties as well. Additionally, the controller of the MRAC system is designed using a new optimal control method. This method is a new linear quadratic regulator-based optimal control formulation for both output regulation and command tracking problems. It provides a closed-form control solution. The proposed overall approach is applied in a control of lateral dynamics of an unmanned aircraft problem to show its effectiveness.
Parameter testing for lattice filter based adaptive modal control systems
NASA Technical Reports Server (NTRS)
Sundararajan, N.; Williams, J. P.; Montgomery, R. C.
1983-01-01
For Large Space Structures (LSS), an adaptive control system is highly desirable. The present investigation is concerned with an 'indirect' adaptive control scheme wherein the system order, mode shapes, and modal amplitudes are estimated on-line using an identification scheme based on recursive, least-squares, lattice filters. Using the identified model parameters, a modal control law based on a pole-placement scheme with the objective of vibration suppression is employed. A method is presented for closed loop adaptive control of a flexible free-free beam. The adaptive control scheme consists of a two stage identification scheme working in series and a modal pole placement control scheme. The main conclusion from the current study is that the identified parameters cannot be directly used for controller design purposes.
Individual differences in political ideology are effects of adaptive error management.
Petersen, Michael Bang; Aarøe, Lene
2014-06-01
We apply error management theory to the analysis of individual differences in the negativity bias and political ideology. Using principles from evolutionary psychology, we propose a coherent theoretical framework for understanding (1) why individuals differ in their political ideology and (2) the conditions under which these individual differences influence and fail to influence the political choices people make.
Physiological responses to error amplification in a robotic reaching adaptation task.
Shirzad, Navid; Van der Loos, H F Machiel
2014-01-01
Analysis of physiological responses provides an objective measure of a person's affective state and has been proposed as a way to evaluate motivation and engagement of therapy clients during robot-assisted therapy regimens. This paper presents the analysis of three physiological responses to different levels of error amplification in a robotic reaching task to understand the feasibility of using physiological signals in order to modify therapy exercises to achieve higher participant attentiveness. In a pilot study with 22 healthy participants, we analyzed skin conductance, skin temperature, and respiration signals, with two main goals: 1) to compare physiological parameters between baseline (rest) and error-amplified reaching motion periods; and 2) to compare physiological parameters between reaching motion periods with different levels of error amplification. Results show that features extracted from skin conductance and respiration signals show significant differences between different error amplification levels. Features extracted from the skin temperature signal are not as reliable as measures of skin conductance and respiration, however they can provide supplementary information.
The Tukey Honestly Significant Difference Procedure and Its Control of the Type I Error-Rate.
ERIC Educational Resources Information Center
Barnette, J. Jackson; McLean, James E.
Tukey's Honestly Significant Difference (HSD) procedure (J. Tukey, 1953) is probably the most recommended and used procedure for controlling Type I error rate when making multiple pairwise comparisons as follow-ups to a significant omnibus F test. This study compared observed Type I errors with nominal alphas of 0.01, 0.05, and 0.10 compared for…
Using Mendelian inheritance errors as quality control criteria in whole genome sequencing data set
2014-01-01
Although the technical and analytic complexity of whole genome sequencing is generally appreciated, best practices for data cleaning and quality control have not been defined. Family based data can be used to guide the standardization of specific quality control metrics in nonfamily based data. Given the low mutation rate, Mendelian inheritance errors are likely as a result of erroneous genotype calls. Thus, our goal was to identify the characteristics that determine Mendelian inheritance errors. To accomplish this, we used chromosome 3 whole genome sequencing family based data from the Genetic Analysis Workshop 18. Mendelian inheritance errors were provided as part of the GAW18 data set. Additionally, for binary variants we calculated Mendelian inheritance errors using PLINK. Based on our analysis, nonbinary single-nucleotide variants have an inherently high number of Mendelian inheritance errors. Furthermore, in binary variants, Mendelian inheritance errors are not randomly distributed. Indeed, we identified 3 Mendelian inheritance error peaks that were enriched with repetitive elements. However, these peaks can be lessened with the inclusion of a single filter from the sequencing file. In summary, we demonstrated that erroneous sequencing calls are nonrandomly distributed across the genome and quality control metrics can dramatically reduce the number of mendelian inheritance errors. Appropriate quality control will allow optimal use of genetic data to realize the full potential of whole genome sequencing. PMID:25519373
The Accuracy of Webcams in 2D Motion Analysis: Sources of Error and Their Control
ERIC Educational Resources Information Center
Page, A.; Moreno, R.; Candelas, P.; Belmar, F.
2008-01-01
In this paper, we show the potential of webcams as precision measuring instruments in a physics laboratory. Various sources of error appearing in 2D coordinate measurements using low-cost commercial webcams are discussed, quantifying their impact on accuracy and precision, and simple procedures to control these sources of error are presented.…
Zheng, Dongliang; Da, Feipeng; Kemao, Qian; Seah, Hock Soon
2017-03-06
Phase-shifting profilometry combined with Gray-code patterns projection has been widely used for 3D measurement. In this technique, a phase-shifting algorithm is used to calculate the wrapped phase, and a set of Gray-code binary patterns is used to determine the unwrapped phase. In the real measurement, the captured Gray-code patterns are no longer binary, resulting in phase unwrapping errors at a large number of erroneous pixels. Although this problem has been attended and well resolved by a few methods, it remains challenging when a measured object has step-heights and the captured patterns contain invalid pixels. To effectively remove unwrapping errors and simultaneously preserve step-heights, in this paper, an effective method using an adaptive median filter is proposed. Both simulations and experiments can demonstrate its effectiveness.
An averaging analysis of discrete-time indirect adaptive control
NASA Technical Reports Server (NTRS)
Phillips, Stephen M.; Kosut, Robert L.; Franklin, Gene F.
1988-01-01
An averaging analysis of indirect, discrete-time, adaptive control systems is presented. The analysis results in a signal-dependent stability condition and accounts for unmodeled plant dynamics as well as exogenous disturbances. This analysis is applied to two discrete-time adaptive algorithms: an unnormalized gradient algorithm and a recursive least-squares (RLS) algorithm with resetting. Since linearization and averaging are used for the gradient analysis, a local stability result valid for small adaptation gains is found. For RLS with resetting, the assumption is that there is a long time between resets. The results for the two algorithms are virtually identical, emphasizing their similarities in adaptive control.
Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.
Liu, Yong-Hua; Huang, Liangpei; Xiao, Dongming; Guo, Yong
2015-09-01
In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes.
State of the art in adaptive control of robotic systems
NASA Technical Reports Server (NTRS)
Tosunoglu, Sabri; Tesar, Delbert
1988-01-01
An up-to-date assessment of adaptive control technology as applied to robotics is presented. Although the field is relatively new and does not yet represent a mature discipline, considerable attention for the design of sophisticated robot controllers has occured. In this presentation, 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.
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.
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.
Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft
NASA Technical Reports Server (NTRS)
Burken, John J.; Williams-Hayes, Peggy; Karneshige, J. T.; Stachowiak, Susan J.
2006-01-01
Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.
NASA Astrophysics Data System (ADS)
Cao, Lu; Chen, Xiaoqian; Misra, Arun K.
2014-03-01
Minimum Sliding Mode Error Feedback Control (MSMEFC) is proposed to improve the control precision of spacecraft formations based on the conventional sliding mode control theory. This paper proposes a new approach to estimate and offset the system model errors, which include various kinds of uncertainties and disturbances, as well as smoothes out the effect of nonlinear switching control terms. To facilitate the analysis, the concept of equivalent control error is introduced, which is the key to the utilization of MSMEFC. A cost function is formulated on the basis of the principle of minimum sliding mode error; then the equivalent control error is estimated and fed back to the conventional sliding mode control. It is shown that the sliding mode after the MSMEFC will approximate to the ideal sliding mode, resulting in improved control performance and quality. The new methodology is applied to spacecraft formation flying. It guarantees global asymptotic convergence of the relative tracking error in the presence of J2 perturbations. In addition, some fault tolerant situations such as thruster failure for a period of time, thruster degradation and so on, are also considered to verify the effectiveness of MSMEFC. Numerical simulations are performed to demonstrate the efficacy of the proposed methodology to maintain and reconfigure the satellite formation with the existence of initial offsets and J2 perturbation effects, even in the fault-tolerant cases.
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.
Adaptive P300 based control system
Jin, Jing; Allison, Brendan Z.; Sellers, Eric W.; Brunner, Clemens; Horki, Petar; Wang, Xingyu; Neuper, Christa
2015-01-01
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 & B paradigms present all items of the 12 × 7 matrix three times using either nine 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 interference from items adjacent to targets. 14-flash A also reduced adjacent item interference and 14-flash B additionally eliminated successive (double) flashes of the same item. Results showed that accuracy and bit rate of the adaptive system were higher than 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 naïve users. PMID:21474877
Hormesis and adaptive cellular control systems
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...
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.
An adaptive control scheme for a flexible manipulator
NASA Technical Reports Server (NTRS)
Yang, T. C.; Yang, J. C. S.; Kudva, P.
1987-01-01
The problem of controlling a single link flexible manipulator is considered. A self-tuning adaptive control scheme is proposed which consists of a least squares on-line parameter identification of an equivalent linear model followed by a tuning of the gains of a pole placement controller using the parameter estimates. Since the initial parameter values for this model are assumed unknown, the use of arbitrarily chosen initial parameter estimates in the adaptive controller would result in undesirable transient effects. Hence, the initial stage control is carried out with a PID controller. Once the identified parameters have converged, control is transferred to the adaptive controller. Naturally, the relevant issues in this scheme are tests for parameter convergence and minimization of overshoots during control switch-over. To demonstrate the effectiveness of the proposed scheme, simulation results are presented with an analytical nonlinear dynamic model of a single link flexible manipulator.
Sun, W Y
1993-04-01
This thesis solves the problem of finding the optimal linear noise-reduction filter for linear tomographic image reconstruction. The optimization is data dependent and results in minimizing the mean-square error of the reconstructed image. The error is defined as the difference between the result and the best possible reconstruction. Applications for the optimal filter include reconstructions of positron emission tomographic (PET), X-ray computed tomographic, single-photon emission tomographic, and nuclear magnetic resonance imaging. Using high resolution PET as an example, the optimal filter is derived and presented for the convolution backprojection, Moore-Penrose pseudoinverse, and the natural-pixel basis set reconstruction methods. Simulations and experimental results are presented for the convolution backprojection method.
One active debris removal control system design and error analysis
NASA Astrophysics Data System (ADS)
Wang, Weilin; Chen, Lei; Li, Kebo; Lei, Yongjun
2016-11-01
The increasing expansion of debris presents a significant challenge to space safety and sustainability. To address it, active debris removal, usually involving a chaser performing autonomous rendezvous with targeted debris to be removed is a feasible solution. In this paper, we explore a mid-range autonomous rendezvous control system based on augmented proportional navigation (APN), establishing a three-dimensional kinematic equation set constructed in a rotating coordinate system. In APN, feedback control is applied in the direction of line of sight (LOS), thus analytical solutions of LOS rate and relative motion are expectedly obtained. To evaluate the effectiveness of the control system, we adopt Zero-Effort-Miss (ZEM) in this research as the index, the uncertainty of which is directly determined by that of LOS rate. Accordingly, we apply covariance analysis (CA) method to analyze the propagation of LOS rate uncertainty. Consequently, we find that the accuracy of the control system can be verified even with uncertainty and the CA method is drastically more computationally efficient compared with nonlinear Monte-Carlo method. Additionally, to justify the superiority of the system, we further discuss more simulation cases to show the robustness and feasibility of APN proposed in the paper.
NASA Astrophysics Data System (ADS)
Jones, Reese E.; Mandadapu, Kranthi K.
2012-04-01
We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.
Jones, Reese E; Mandadapu, Kranthi K
2012-04-21
We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)] and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.
Adaptive fuzzy control of underactuated robotic systems with the use of differential flatness theory
NASA Astrophysics Data System (ADS)
Rigatos, Gerasimos G.
2013-10-01
An adaptive fuzzy controller is designed for a class of underactuated nonlinear robotic manipulators, under the constraint that the system's model is unknown. The control algorithm aims at satisfying the H∞ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the robotic system into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system's parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed adaptive fuzzy control scheme results in H∞ tracking performance. The efficiency of the proposed adaptive fuzzy control scheme is checked in the case of a 2-DOF planar robotic manipulator that has the structure of a closed-chain mechanism.
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.
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.
Adaptive Force And Position Control For Robots
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1989-01-01
Control system causes end effector of robot manipulator to follow prescribed trajectory and applies desired force or torque to object manipulating or in contact. Characterized by hybrid control architecture, where positions and orientations along unconstrained coordinate axes controlled by position-control subsystem, while forces and torques along constrained coordinate axes controlled by force-control subsystem. Compensates for dynamic cross-coupling between force-and position-control loops and does not require knowledge of complicated model of dynamics of manipulator and environment.
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.
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.
Parameter Estimation for a Hybrid Adaptive Flight Controller
NASA Technical Reports Server (NTRS)
Campbell, Stefan F.; Nguyen, Nhan T.; Kaneshige, John; Krishnakumar, Kalmanje
2009-01-01
This paper expands on the hybrid control architecture developed at the NASA Ames Research Center by addressing issues related to indirect adaptation using the recursive least squares (RLS) algorithm. Specifically, the hybrid control architecture is an adaptive flight controller that features both direct and indirect adaptation techniques. This paper will focus almost exclusively on the modifications necessary to achieve quality indirect adaptive control. Additionally this paper will present results that, using a full non -linear aircraft model, demonstrate the effectiveness of the hybrid control architecture given drastic changes in an aircraft s dynamics. Throughout the development of this topic, a thorough discussion of the RLS algorithm as a system identification technique will be provided along with results from seven well-known modifications to the popular RLS algorithm.
Adaptive optimization and control using neural networks
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.
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.
Adaptive tracking control for a class of uncertain chaotic systems
NASA Astrophysics Data System (ADS)
Chen, Feng-Xiang; Wang, Wei; Zhang, Wei-Dong
2007-09-01
The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty, but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.
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.
Hauser, Tobias U; Iannaccone, Reto; Walitza, Susanne; Brandeis, Daniel; Brem, Silvia
2015-01-01
Adolescence is associated with quickly changing environmental demands which require excellent adaptive skills and high cognitive flexibility. Feedback-guided adaptive learning and cognitive flexibility are driven by reward prediction error (RPE) signals, which indicate the accuracy of expectations and can be estimated using computational models. Despite the importance of cognitive flexibility during adolescence, only little is known about how RPE processing in cognitive flexibility deviates between adolescence and adulthood. In this study, we investigated the developmental aspects of cognitive flexibility by means of computational models and functional magnetic resonance imaging (fMRI). We compared the neural and behavioral correlates of cognitive flexibility in healthy adolescents (12-16years) to adults performing a probabilistic reversal learning task. Using a modified risk-sensitive reinforcement learning model, we found that adolescents learned faster from negative RPEs than adults. The fMRI analysis revealed that within the RPE network, the adolescents had a significantly altered RPE-response in the anterior insula. This effect seemed to be mainly driven by increased responses to negative prediction errors. In summary, our findings indicate that decision making in adolescence goes beyond merely increased reward-seeking behavior and provides a developmental perspective to the behavioral and neural mechanisms underlying cognitive flexibility in the context of reinforcement learning.
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
Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants
NASA Astrophysics Data System (ADS)
Masri Husam Fayiz, Al
2017-01-01
The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms.
Dual-thread parallel control strategy for ophthalmic adaptive optics.
Yu, Yongxin; Zhang, Yuhua
To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a closed loop updating frequency up to 110 Hz, and demonstrated robust compensation for ocular wave aberration up to 50 Hz in an adaptive optics scanning laser ophthalmoscope.
Distributed adaptive tracking control for synchronization of unknown networked Lagrangian systems.
Chen, Gang; Lewis, Frank L
2011-06-01
This paper investigates the cooperative tracking control problem for a group of Lagrangian vehicle systems with directed communication graph topology. All the vehicles can have different dynamics. A design method for a distributed adaptive protocol is given which guarantees that all the networked systems synchronize to the motion of a target system. The dynamics of the networked systems, as well as the target system, are all assumed unknown. A neural network (NN) is used at each node to approximate the distributed dynamics. The resulting protocol consists of a simple decentralized proportional-plus-derivative term and a nonlinear term with distributed adaptive tuning laws at each node. The case with nonconstant NN approximation error is considered. There, a robust term is added to suppress the external disturbances and the approximation errors of the NNs. Simulation examples are included to demonstrate the effectiveness of the proposed algorithms.
Wang, Huanqing; Chen, Bing; Liu, Kefu; Liu, Xiaoping; Lin, Chong
2014-05-01
This paper considers the problem of adaptive neural control of stochastic nonlinear systems in nonstrict-feedback form with unknown backlash-like hysteresis nonlinearities. To overcome the design difficulty of nonstrict-feedback structure, variable separation technique is used to decompose the unknown functions of all state variables into a sum of smooth functions of each error dynamic. By combining radial basis function neural networks' universal approximation capability with an adaptive backstepping technique, an adaptive neural control algorithm is proposed. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are four-moment semiglobally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood of the origin in the sense of mean quartic value. Simulation results further show the effectiveness of the presented control scheme.
NASA Technical Reports Server (NTRS)
Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.
1992-01-01
A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).
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.
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.
A geometric view of adaptive optics control: boiling atmosphere model
NASA Astrophysics Data System (ADS)
Wiberg, Donald M.; Max, Claire E.; Gavel, Donald T.
2004-10-01
The separation principle of optimal adaptive optics control is derived, and definitions of controllability and observability are introduced. An exact finite dimensional state space representation of the control system dynamics is obtained without the need for truncation in modes such as Zernikes. The uncertainty of sensing uncontrollable modes confuses present adaptive optics controllers. This uncertainty can be modeled by a Kalman filter. Reducing this uncertainty permits increased gain, increasing the Strehl, which is done by an optimal control law derived here. A general model of the atmosphere is considered, including boiling.
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.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Wen, Yuntong; Ren, Xuemei
2011-10-01
This paper investigates a neural network (NN) state observer-based adaptive control for a class of time-varying delays nonlinear systems with unknown control direction. An adaptive neural memoryless observer, in which the knowledge of time-delay is not used, is designed to estimate the system states. Furthermore, by applying the property of the function tanh(2)(ϑ/ε)/ϑ (the function can be defined at ϑ = 0) and introducing a novel type appropriate Lyapunov-Krasovskii functional, an adaptive output feedback controller is constructed via backstepping method which can efficiently avoid the problem of controller singularity and compensate for the time-delay. It is highly proven that the closed-loop systems controller designed by the NN-basis function property, new kind parameter adaptive law and Nussbaum function in detecting the control direction is able to guarantee the semi-global uniform ultimate boundedness of all signals and the tracking error can converge to a small neighborhood of zero. The characteristic of the proposed approach is that it relaxes any restrictive assumptions of Lipschitz condition for the unknown nonlinear continuous functions. And the proposed scheme is suitable for the systems with mismatching conditions and unmeasurable states. Finally, two simulation examples are given to illustrate the effectiveness and applicability of the proposed approach.
An error-resistant linguistic protocol for air traffic control
NASA Technical Reports Server (NTRS)
Cushing, Steven
1989-01-01
The research results described here are intended to enhance the effectiveness of the DATALINK interface that is scheduled by the Federal Aviation Administration (FAA) to be deployed during the 1990's to improve the safety of various aspects of aviation. While voice has a natural appeal as the preferred means of communication both among humans themselves and between humans and machines as the form of communication that people find most convenient, the complexity and flexibility of natural language are problematic, because of the confusions and misunderstandings that can arise as a result of ambiguity, unclear reference, intonation peculiarities, implicit inference, and presupposition. The DATALINK interface will avoid many of these problems by replacing voice with vision and speech with written instructions. This report describes results achieved to date on an on-going research effort to refine the protocol of the DATALINK system so as to avoid many of the linguistic problems that still remain in the visual mode. In particular, a working prototype DATALINK simulator system has been developed consisting of an unambiguous, context-free grammar and parser, based on the current air-traffic-control language and incorporated into a visual display involving simulated touch-screen buttons and three levels of menu screens. The system is written in the C programming language and runs on the Macintosh II computer. After reviewing work already done on the project, new tasks for further development are described.
Small, J R
1993-01-01
This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed. PMID:8257434
Force reflecting teleoperation with adaptive impedance control.
Love, Lonnie J; Book, Wayne J
2004-02-01
Experimentation and a survey of the literature clearly show that contact stability in a force reflecting teleoperation system requires high levels of damping on the master robot. However, excessive damping increases the energy required by an operator for commanding motion. The objective of this paper is to describe a new force reflecting teleoperation methodology that reduces operator energy requirements without sacrificing stability. We begin by describing a new approach to modeling and identifying the remote environment of the teleoperation system. We combine a conventional multi-input, multi-output recursive least squares (MIMO-RLS) system identification, identifying in real-time the remote environment impedance, with a discretized representation of the remote environment. This methodology generates a time-varying, position-dependent representation of the remote environment dynamics. Next, we adapt the target impedance of the master robot with respect to the dynamic model of the remote environment. The environment estimation and impedance adaptation are executed simultaneously and in real time. We demonstrate, through experimentation, that this approach significantly reduces the energy required by an operator to execute remote tasks while simultaneously providing sufficient damping to ensure contact stability.
Adaptive control of waveguide modes using a directional coupler.
Lu, Peng; Shipton, Matthew; Wang, Anbo; Xu, Yong
2014-08-25
Using adaptive optics (AO) and a directional coupler, we demonstrate adaptive control of linearly polarized (LP) modes in a two mode fiber. The AO feedback is provided by the coupling ratio of the directional coupler, and does not depend on the spatial profiles of optical field distributions. As a proof of concept demonstration, this work confirms the feasibility of using AO and all fiber devices to control the waveguide modes in a multimode network in a quasi-distributed manner.
Design of a digital adaptive control system for reentry vehicles.
NASA Technical Reports Server (NTRS)
Picon-Jimenez, J. L.; Montgomery, R. C.; Grigsby, L. L.
1972-01-01
The flying qualities of atmospheric reentry vehicles experience considerable variations due to the wide changes in flight conditions characteristic of reentry trajectories. A digital adaptive control system has been designed to modify the vehicle's dynamic characteristics and to provide desired flying qualities for all flight conditions. This adaptive control system consists of a finite-memory identifier which determines the vehicle's unknown parameters, and a gain computer which calculates feedback gains to satisfy flying quality requirements.