Call admission algorithms in multiservice and multiclass ATM network
NASA Astrophysics Data System (ADS)
Hamma, Salima; Hebuterne, Gerard
2004-09-01
The introduction of new ATM service categories increases the benefits of ATM, making the technology suitable for a virtually unlimited range of applications. Connection Admission Control (CAC) is defined as the set of actions taken by the network during the call (virtual connection) set-up phase, or during call re-negotiation phase, to determine whether a connection request can be accepted or rejected. Network resources (port bandwidth and buffer space) are reserved to the incoming connection at each switching element traversed, if so required, by the service category. The major focus of this paper is call admission in the context of multi-service, multi-class ATM networks. Several strategies suggesting rules on bandwidth sharing are found in the litterature. This study investigates particularly the Complete Sharing approach. Two service categories are concerned, namely, Constant Bit rate/Deterministic Bit Rate (CBR/DBR) and Variable Bit Rate/Statistical Bit Rate (VBR/SBR). Each service category is represented by a set of call classes corresponding to different bandwidth needs. We propose two algorithms to solve the underlying Markovian system: Product-form and Recursive solutions. A performance study based on the latter algorithm is implemented. We analyze the results of this very sharing strategy and set the not-to-violate limits for a beneficial use of it.
28 CFR 541.47 - Admission to control unit.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Admission to control unit. 541.47 Section 541.47 Judicial Administration BUREAU OF PRISONS, DEPARTMENT OF JUSTICE INSTITUTIONAL MANAGEMENT INMATE DISCIPLINE AND SPECIAL HOUSING UNITS Control Unit Programs § 541.47 Admission to control...
A self-learning call admission control scheme for CDMA cellular networks.
Liu, Derong; Zhang, Yi; Zhang, Huaguang
2005-09-01
In the present paper, a call admission control scheme that can learn from the network environment and user behavior is developed for code division multiple access (CDMA) cellular networks that handle both voice and data services. The idea is built upon a novel learning control architecture with only a single module instead of two or three modules in adaptive critic designs (ACDs). The use of adaptive critic approach for call admission control in wireless cellular networks is new. The call admission controller can perform learning in real-time as well as in offline environments and the controller improves its performance as it gains more experience. Another important contribution in the present work is the choice of utility function for the present self-learning control approach which makes the present learning process much more efficient than existing learning control methods. The performance of our algorithm will be shown through computer simulation and compared with existing algorithms. PMID:16252828
A lexicographic approach to constrained MDP admission control
NASA Astrophysics Data System (ADS)
Panfili, Martina; Pietrabissa, Antonio; Oddi, Guido; Suraci, Vincenzo
2016-02-01
This paper proposes a reinforcement learning-based lexicographic approach to the call admission control problem in communication networks. The admission control problem is modelled as a multi-constrained Markov decision process. To overcome the problems of the standard approaches to the solution of constrained Markov decision processes, based on the linear programming formulation or on a Lagrangian approach, a multi-constraint lexicographic approach is defined, and an online implementation based on reinforcement learning techniques is proposed. Simulations validate the proposed approach.
Tomasz Plawski, J. Hovater
2010-09-01
A digital low level radio frequency (RF) system typically incorporates either a heterodyne or direct sampling technique, followed by fast ADCs, then an FPGA, and finally a transmitting DAC. This universal platform opens up the possibilities for a variety of control algorithm implementations. The foremost concern for an RF control system is cavity field stability, and to meet the required quality of regulation, the chosen control system needs to have sufficient feedback gain. In this paper we will investigate the effectiveness of the regulation for three basic control system algorithms: I&Q (In-phase and Quadrature), Amplitude & Phase and digital SEL (Self Exciting Loop) along with the example of the Jefferson Lab 12 GeV cavity field control system.
Medication reconciliation at patient admission: a randomized controlled trial
Mendes, Antonio E.; Lombardi, Natália F.; Andrzejevski, Vânia S.; Frandoloso, Gibran; Correr, Cassyano J.; Carvalho, Mauricio
2015-01-01
Objective: To measure length of hospital stay (LHS) in patients receiving medication reconciliation. Secondary characteristics included analysis of number of preadmission medications, medications prescribed at admission, number of discrepancies, and pharmacists interventions done and accepted by the attending physician. Methods: A 6 month, randomized, controlled trial conducted at a public teaching hospital in southern Brazil. Patients admitted to general wards were randomized to receive usual care or medication reconciliation, performed within the first 72 hours of hospital admission. Results: The randomization process assigned 68 patients to UC and 65 to MR. LHS was 10±15 days in usual care and 9±16 days in medication reconciliation (p=0.620). The total number of discrepancies was 327 in the medication reconciliation group, comprising 52.6% of unintentional discrepancies. Physicians accepted approximately 75.0% of the interventions. Conclusion: These results highlight weakness at patient transition care levels in a public teaching hospital. LHS, the primary outcome, should be further investigated in larger studies. Medication reconciliation was well accepted by physicians and it is a useful tool to find and correct discrepancies, minimizing the risk of adverse drug events and improving patient safety. PMID:27011775
Lin, Di; Labeau, Fabrice; Yao, Yuanzhe; Vasilakos, Athanasios V; Tang, Yu
2016-07-01
Wireless technologies and vehicle-mounted or wearable medical sensors are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario rests at the electromagnetic interference (EMI) caused by radio frequency transmission. A high level of EMI may lead to a critical malfunction of medical sensors, and in such a scenario, a few users who are not transmitting emergency data could be required to reduce their transmit power or even temporarily disconnect from the network in order to guarantee the normal operation of medical sensors as well as the transmission of emergency data. In this paper, we propose a joint power and admission control algorithm to schedule the users' transmission of medical data. The objective of this algorithm is to minimize the number of users who are forced to disconnect from the network while keeping the EMI on medical sensors at an acceptable level. We show that a fixed point of proposed algorithm always exists, and at the fixed point, our proposed algorithm can minimize the number of low-priority users who are required to disconnect from the network. Numerical results illustrate that the proposed algorithm can achieve robust performance against the variations of mobile hospital environments. PMID:25974956
ERIC Educational Resources Information Center
Seo, Dong-Chul; Torabi, Mohammad R.
2007-01-01
There has been no research linking implementation of a public smoking ban and reduced incidence of acute myocardial infarction (AMI) among nonsmoking patients. An ex post facto matched control group study was conducted to determine whether there was a change in hospital admissions for AMI among nonsmoking patients after a public smoking ban was…
Algorithmic formulation of control problems in manipulation
NASA Technical Reports Server (NTRS)
Bejczy, A. K.
1975-01-01
The basic characteristics of manipulator control algorithms are discussed. The state of the art in the development of manipulator control algorithms is briefly reviewed. Different end-point control techniques are described together with control algorithms which operate on external sensor (imaging, proximity, tactile, and torque/force) signals in realtime. Manipulator control development at JPL is briefly described and illustrated with several figures. The JPL work pays special attention to the front or operator input end of the control algorithms.
A Robustly Stabilizing Model Predictive Control Algorithm
NASA Technical Reports Server (NTRS)
Ackmece, A. Behcet; Carson, John M., III
2007-01-01
A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.
BARTER: Behavior Profile Exchange for Behavior-Based Admission and Access Control in MANETs
NASA Astrophysics Data System (ADS)
Frias-Martinez, Vanessa; Stolfo, Salvatore J.; Keromytis, Angelos D.
Mobile Ad-hoc Networks (MANETs) are very dynamic networks with devices continuously entering and leaving the group. The highly dynamic nature of MANETs renders the manual creation and update of policies associated with the initial incorporation of devices to the MANET (admission control) as well as with anomaly detection during communications among members (access control) a very difficult task. In this paper, we present BARTER, a mechanism that automatically creates and updates admission and access control policies for MANETs based on behavior profiles. BARTER is an adaptation for fully distributed environments of our previously introduced BB-NAC mechanism for NAC technologies. Rather than relying on a centralized NAC enforcer, MANET members initially exchange their behavior profiles and compute individual local definitions of normal network behavior. During admission or access control, each member issues an individual decision based on its definition of normalcy. Individual decisions are then aggregated via a threshold cryptographic infrastructure that requires an agreement among a fixed amount of MANET members to change the status of the network. We present experimental results using content and volumetric behavior profiles computed from the ENRON dataset. In particular, we show that the mechanism achieves true rejection rates of 95% with false rejection rates of 9%.
NASA Astrophysics Data System (ADS)
Wieselthier, Jeffrey E.; Barnhart, Craig M.; Ephremides, Anthony
1995-08-01
In this report we apply the ideas of ordinal optimization and the technique of Standard Clock (SC) simulation to the voice-call admission-control problem in integrated voice/data multihop radio networks. We first describe the use of the SC approach on sequential machines, and quantify the speedup in simulation time that is achieved by its use in a number of queueing examples. We then develop an efficient simulation model for wireless integrated networks based on the use of the SC approach, which permits the rapid parallel simulation of a large number of admission-control policies. We have extended the basic SC approach by incorporating fixed strength data packets, whereas SC simulation is normally limited to systems with exponential interevent times. Using this model, we demonstrate the effectiveness of ordinal-optimization techniques, which provide a remarkable good ranking of admission-control policies after relatively short simulation runs, thereby facilitating the rapid determination of good policies. Moreover, we demonstrate that the use of crude, inaccurate analytical and simulation models can provide highly accurate policy rankings that can be used in conjunction with ordinal-optimization methods, provided that they incorporate the key aspects of system operation.
Control algorithms for dynamic attenuators
Hsieh, Scott S.; Pelc, Norbert J.
2014-06-15
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
NASA Astrophysics Data System (ADS)
Sánchez, M.; Esteban, L.; Kornejew, P.; Hirsch, M.
2008-03-01
Mid Infrared (10,6 μm CO2 laser lines) interferometers as a plasma density diagnostic must use two-colour systems with superposed interferometers beams at different wavelengths in order to cope with mechanical vibrations and drifts. They require a highly precise phase difference measurement where all sources of error must be reduced. One of these is the cross-talk between the signals which creates nonlinear spurious periodic mixing products. The reason may be either optical or electrical crosstalk both resulting in similar perturbations of the measurement. In the TJII interferometer a post-processing algorithm is used to reduce the crosstalk in the data. This post-processing procedure is not appropriate for very long pulses, as it is the case for in new tokamak (ITER) or stellarator (W7-X) projects. In both cases an on-line reduction process is required or—even better—the unwanted signal components must be reduced in the system itself CO2 laser interferometers which as the second wavelength use the CO laser line (5,3 μm), may apply a single common detector sensitive to both wavelengths and separate the corresponding IF signals by appropriate bandpass filters. This reduces complexity of the optical arrangement and avoids a possible source of vibration induced phase noise as both signals share the same beam path. To avoid cross talk in this arrangement filtering must be appropriate. In this paper we present calculations to define the limits of crosstalk for a desired plasma density precision. A crosstalk reduction algorithm has been developed and is applied to experimental results from TJ-II pulses. Results from a single detector arrangement as under investigation for the CO2/CO laser interferometer developed for W7-X are presented.
Automatic control algorithm effects on energy production
NASA Technical Reports Server (NTRS)
Mcnerney, G. M.
1981-01-01
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
Medical-Grade Channel Access and Admission Control in 802.11e EDCA for Healthcare Applications
Son, Sunghwa; Park, Kyung-Joon; Park, Eun-Chan
2016-01-01
In this paper, we deal with the problem of assuring medical-grade quality of service (QoS) for real-time medical applications in wireless healthcare systems based on IEEE 802.11e. Firstly, we show that the differentiated channel access of IEEE 802.11e cannot effectively assure medical-grade QoS because of priority inversion. To resolve this problem, we propose an efficient channel access algorithm. The proposed algorithm adjusts arbitrary inter-frame space (AIFS) in the IEEE 802.11e protocol depending on the QoS measurement of medical traffic, to provide differentiated near-absolute priority for medical traffic. In addition, based on rigorous capacity analysis, we propose an admission control scheme that can avoid performance degradation due to network overload. Via extensive simulations, we show that the proposed mechanism strictly assures the medical-grade QoS and improves the throughput of low-priority traffic by more than several times compared to the conventional IEEE 802.11e. PMID:27490666
Medical-Grade Channel Access and Admission Control in 802.11e EDCA for Healthcare Applications.
Son, Sunghwa; Park, Kyung-Joon; Park, Eun-Chan
2016-01-01
In this paper, we deal with the problem of assuring medical-grade quality of service (QoS) for real-time medical applications in wireless healthcare systems based on IEEE 802.11e. Firstly, we show that the differentiated channel access of IEEE 802.11e cannot effectively assure medical-grade QoS because of priority inversion. To resolve this problem, we propose an efficient channel access algorithm. The proposed algorithm adjusts arbitrary inter-frame space (AIFS) in the IEEE 802.11e protocol depending on the QoS measurement of medical traffic, to provide differentiated near-absolute priority for medical traffic. In addition, based on rigorous capacity analysis, we propose an admission control scheme that can avoid performance degradation due to network overload. Via extensive simulations, we show that the proposed mechanism strictly assures the medical-grade QoS and improves the throughput of low-priority traffic by more than several times compared to the conventional IEEE 802.11e. PMID:27490666
El-Qulity, Said Ali; Mohamed, Ali Wagdy
2016-01-01
This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness. PMID:26819583
El-Qulity, Said Ali; Mohamed, Ali Wagdy
2016-01-01
This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness. PMID:26819583
Mitigating Handoff Call Dropping in Wireless Cellular Networks: A Call Admission Control Technique
NASA Astrophysics Data System (ADS)
Ekpenyong, Moses Effiong; Udoh, Victoria Idia; Bassey, Udoma James
2016-06-01
Handoff management has been an important but challenging issue in the field of wireless communication. It seeks to maintain seamless connectivity of mobile users changing their points of attachment from one base station to another. This paper derives a call admission control model and establishes an optimal step-size coefficient (k) that regulates the admission probability of handoff calls. An operational CDMA network carrier was investigated through the analysis of empirical data collected over a period of 1 month, to verify the performance of the network. Our findings revealed that approximately 23 % of calls in the existing system were lost, while 40 % of the calls (on the average) were successfully admitted. A simulation of the proposed model was then carried out under ideal network conditions to study the relationship between the various network parameters and validate our claim. Simulation results showed that increasing the step-size coefficient degrades the network performance. Even at optimum step-size (k), the network could still be compromised in the presence of severe network crises, but our model was able to recover from these problems and still functions normally.
Algorithm For Control Of Large Antenna
NASA Technical Reports Server (NTRS)
Hill, Robert E.
1990-01-01
Alternative position-error feedback modes provided. Modern control theory basis for computer algorithm used to control two-axis positioning of large antenna. Algorithm - incorporated into software of real-time control computer - enables rapid intertarget positioning as well as precise tracking (using one of two optional position-feedback modes) without need of human operator intervention. Control system for one axis of two-axis azimuth/elevation control system embodied mostly in software based on advanced control theory. System has linear properties of classical linear feedback controller. Performance described by bandwidth and linear error coefficients.
Large space structures control algorithm characterization
NASA Technical Reports Server (NTRS)
Fogel, E.
1983-01-01
Feedback control algorithms are developed for sensor/actuator pairs on large space systems. These algorithms have been sized in terms of (1) floating point operation (FLOP) demands; (2) storage for variables; and (3) input/output data flow. FLOP sizing (per control cycle) was done as a function of the number of control states and the number of sensor/actuator pairs. Storage for variables and I/O sizing was done for specific structure examples.
Hanley, Janet; McCloughan, Lucy; Todd, Allison; Krishan, Ashma; Lewis, Stephanie; Stoddart, Andrew; van der Pol, Marjon; MacNee, William; Sheikh, Aziz; Pagliari, Claudia; McKinstry, Brian
2013-01-01
Objective To test the effectiveness of telemonitoring integrated into existing clinical services such that intervention and control groups have access to the same clinical care. Design Researcher blind, multicentre, randomised controlled trial. Setting UK primary care (Lothian, Scotland). Participants Adults with at least one admission for chronic obstructive pulmonary disease (COPD) in the year before randomisation. We excluded people who had other significant lung disease, who were unable to provide informed consent or complete the study, or who had other significant social or clinical problems. Interventions Participants were recruited between 21 May 2009 and 28 March 2011, and centrally randomised to receive telemonitoring or conventional self monitoring. Using a touch screen, telemonitoring participants recorded a daily questionnaire about symptoms and treatment use, and monitored oxygen saturation using linked instruments. Algorithms, based on the symptom score, generated alerts if readings were omitted or breached thresholds. Both groups received similar care from existing clinical services. Main outcome measures The primary outcome was time to hospital admission due to COPD exacerbation up to one year after randomisation. Other outcomes included number and duration of admissions, and validated questionnaire assessments of health related quality of life (using St George’s respiratory questionnaire (SGRQ)), anxiety or depression (or both), self efficacy, knowledge, and adherence to treatment. Analysis was intention to treat. Results Of 256 patients completing the study, 128 patients were randomised to telemonitoring and 128 to usual care; baseline characteristics of each group were similar. The number of days to admission did not differ significantly between groups (adjusted hazard ratio 0.98, 95% confidence interval 0.66 to 1.44). Over one year, the mean number of COPD admissions was similar in both groups (telemonitoring 1.2 admissions per person
Control algorithms for autonomous robot navigation
Jorgensen, C.C.
1985-09-20
This paper examines control algorithm requirements for autonomous robot navigation outside laboratory environments. Three aspects of navigation are considered: navigation control in explored terrain, environment interactions with robot sensors, and navigation control in unanticipated situations. Major navigation methods are presented and relevance of traditional human learning theory is discussed. A new navigation technique linking graph theory and incidental learning is introduced.
Pinning impulsive control algorithms for complex network
Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo
2014-03-15
In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
ERIC Educational Resources Information Center
Orlando, Frank
This report identifies policies and practices essential to overcoming problems with admissions to juvenile detention facilities, using information from the Juvenile Detention Alternatives Initiative (JDAI). Chapter 1, "Why Objective Admissions Policies and Practices Are Critical to Detention Reform," describes factors contributing to uncontrolled…
Approximation algorithms for planning and control
NASA Technical Reports Server (NTRS)
Boddy, Mark; Dean, Thomas
1989-01-01
A control system operating in a complex environment will encounter a variety of different situations, with varying amounts of time available to respond to critical events. Ideally, such a control system will do the best possible with the time available. In other words, its responses should approximate those that would result from having unlimited time for computation, where the degree of the approximation depends on the amount of time it actually has. There exist approximation algorithms for a wide variety of problems. Unfortunately, the solution to any reasonably complex control problem will require solving several computationally intensive problems. Algorithms for successive approximation are a subclass of the class of anytime algorithms, algorithms that return answers for any amount of computation time, where the answers improve as more time is allotted. An architecture is described for allocating computation time to a set of anytime algorithms, based on expectations regarding the value of the answers they return. The architecture described is quite general, producing optimal schedules for a set of algorithms under widely varying conditions.
Genetic algorithms in adaptive fuzzy control
NASA Technical Reports Server (NTRS)
Karr, C. Lucas; Harper, Tony R.
1992-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
Control Algorithms For Liquid-Cooled Garments
NASA Technical Reports Server (NTRS)
Drew, B.; Harner, K.; Hodgson, E.; Homa, J.; Jennings, D.; Yanosy, J.
1988-01-01
Three algorithms developed for control of cooling in protective garments. Metabolic rate inferred from temperatures of cooling liquid outlet and inlet, suitably filtered to account for thermal lag of human body. Temperature at inlet adjusted to value giving maximum comfort at inferred metabolic rate. Applicable to space suits, used for automatic control of cooling in suits worn by workers in radioactive, polluted, or otherwise hazardous environments. More effective than manual control, subject to frequent, overcompensated adjustments as level of activity varies.
Decentralized control of Markovian decision processes: Existence Sigma-admissable policies
NASA Technical Reports Server (NTRS)
Greenland, A.
1980-01-01
The problem of formulating and analyzing Markov decision models having decentralized information and decision patterns is examined. Included are basic examples as well as the mathematical preliminaries needed to understand Markov decision models and, further, to superimpose decentralized decision structures on them. The notion of a variance admissible policy for the model is introduced and it is proved that there exist (possibly nondeterministic) optional policies from the class of variance admissible policies. Directions for further research are explored.
Digital control algorithms for microgravity isolation systems
NASA Technical Reports Server (NTRS)
Sinha, A.; Wang, Y.-P.
1993-01-01
New digital control algorithms have been developed to achieve the desired transmissibility function for a microgravity isolation system. Two approaches have been presented for the controller design in the context of a single degree of freedom system for which an attractive electromagnet is used as the actuator. The relative displacement and the absolute acceleration of the mass have been used as feedback signals. The results from numerical studies are presented. It has been found that the resulting transmissibility is quite close to the desired function. Also, the maximum coil currents required by new algorithms are smaller than the maximum current demanded by the previously proposed lead/lag method.
A reliable algorithm for optimal control synthesis
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1992-01-01
In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.
NASA Astrophysics Data System (ADS)
Chowdhury, Prasun; Saha Misra, Iti
2014-10-01
Nowadays, due to increased demand for using the Broadband Wireless Access (BWA) networks in a satisfactory manner a promised Quality of Service (QoS) is required to manage the seamless transmission of the heterogeneous handoff calls. To this end, this paper proposes an improved Call Admission Control (CAC) mechanism with prioritized handoff queuing scheme that aims to reduce dropping probability of handoff calls. Handoff calls are queued when no bandwidth is available even after the allowable bandwidth degradation of the ongoing calls and get admitted into the network when an ongoing call is terminated with a higher priority than the newly originated call. An analytical Markov model for the proposed CAC mechanism is developed to analyze various performance parameters. Analytical results show that our proposed CAC with handoff queuing scheme prioritizes the handoff calls effectively and reduces dropping probability of the system by 78.57% for real-time traffic without degrading the number of failed new call attempts. This results in the increased bandwidth utilization of the network.
A novel source rate control algorithm for video streaming over the Internet
NASA Astrophysics Data System (ADS)
Zhu, Peng; Zeng, Wenjun; Li, Chunwen
2006-01-01
In this paper, we propose a novel source rate control algorithm for video streaming over the Internet. With the incorporation of a virtual network buffer management mechanism (VB), the QoS requirements of the application can be translated into the source rate constraints, based on which the source rate control is implemented. The maximum admissible bandwidth (or send rate) constraint, which is imposed by the encoder and decoder buffer sizes of the application, is also derived. To make sure the send rate not exceeding the maximum bandwidth constraint, a rate regulator using the token bucket approach is adopted at the application layer to limit the output rate of the encoder buffer when necessary. Simulation results show that our proposed algorithm can help the application reduce the overflow and underflow of the decoder buffer, and achieve better video quality and quality smoothness than traditional source rate control algorithms.
ERIC Educational Resources Information Center
Hoover, Eric; Millman, Sierra
2007-01-01
Marilee Jones's career had been a remarkable success. She joined Massachusetts Institute of Technology's (MIT's) admissions office in 1979, landing a job in Cambridge at a time when boys ruled the sandbox of the admissions profession. Her job was to help MIT recruit more women, who then made up less than one-fifth of the institute's students. She…
Algorithm for Controlling a Centrifugal Compressor
NASA Technical Reports Server (NTRS)
Benedict, Scott M.
2004-01-01
An algorithm has been developed for controlling a centrifugal compressor that serves as the prime mover in a heatpump system. Experimental studies have shown that the operating conditions for maximum compressor efficiency are close to the boundary beyond which surge occurs. Compressor surge is a destructive condition in which there are instantaneous reversals of flow associated with a high outlet-to-inlet pressure differential. For a given cooling load, the algorithm sets the compressor speed at the lowest possible value while adjusting the inlet guide vane angle and diffuser vane angle to maximize efficiency, subject to an overriding requirement to prevent surge. The onset of surge is detected via the onset of oscillations of the electric current supplied to the compressor motor, associated with surge-induced oscillations of the torque exerted by and on the compressor rotor. The algorithm can be implemented in any of several computer languages.
Computational Controls Workstation: Algorithms and hardware
NASA Technical Reports Server (NTRS)
Venugopal, R.; Kumar, M.
1993-01-01
The Computational Controls Workstation provides an integrated environment for the modeling, simulation, and analysis of Space Station dynamics and control. Using highly efficient computational algorithms combined with a fast parallel processing architecture, the workstation makes real-time simulation of flexible body models of the Space Station possible. A consistent, user-friendly interface and state-of-the-art post-processing options are combined with powerful analysis tools and model databases to provide users with a complete environment for Space Station dynamics and control analysis. The software tools available include a solid modeler, graphical data entry tool, O(n) algorithm-based multi-flexible body simulation, and 2D/3D post-processors. This paper describes the architecture of the workstation while a companion paper describes performance and user perspectives.
Fuzzy controller design by parallel genetic algorithms
NASA Astrophysics Data System (ADS)
Mondelli, G.; Castellano, G.; Attolico, Giovanni; Distante, Arcangelo
1998-03-01
Designing a fuzzy system involves defining membership functions and constructing rules. Carrying out these two steps manually often results in a poorly performing system. Genetic Algorithms (GAs) has proved to be a useful tool for designing optimal fuzzy controller. In order to increase the efficiency and effectiveness of their application, parallel GAs (PAGs), evolving synchronously several populations with different balances between exploration and exploitation, have been implemented using a SIMD machine (APE100/Quadrics). The parameters to be identified are coded in such a way that the algorithm implicitly provides a compact fuzzy controller, by finding only necessary rules and removing useless inputs from them. Early results, working on a fuzzy controller implementing the wall-following task for a real vehicle as a test case, provided better fitness values in less generations with respect to previous experiments made using a sequential implementation of GAs.
Gradient algorithm applied to laboratory quantum control
Roslund, Jonathan; Rabitz, Herschel
2009-05-15
The exploration of a quantum control landscape, which is the physical observable as a function of the control variables, is fundamental for understanding the ability to perform observable optimization in the laboratory. For high control variable dimensions, trajectory-based methods provide a means for performing such systematic explorations by exploiting the measured gradient of the observable with respect to the control variables. This paper presents a practical, robust, easily implemented statistical method for obtaining the gradient on a general quantum control landscape in the presence of noise. In order to demonstrate the method's utility, the experimentally measured gradient is utilized as input in steepest-ascent trajectories on the landscapes of three model quantum control problems: spectrally filtered and integrated second harmonic generation as well as excitation of atomic rubidium. The gradient algorithm achieves efficiency gains of up to approximately three times that of the standard genetic algorithm and, as such, is a promising tool for meeting quantum control optimization goals as well as landscape analyses. The landscape trajectories directed by the gradient should aid in the continued investigation and understanding of controlled quantum phenomena.
On-orbit flight control algorithm description
NASA Technical Reports Server (NTRS)
1975-01-01
Algorithms are presented for rotational and translational control of the space shuttle orbiter in the orbital mission phases, which are external tank separation, orbit insertion, on-orbit and de-orbit. The program provides a versatile control system structure while maintaining uniform communications with other programs, sensors, and control effectors by using an executive routine/functional subroutine format. Software functional requirements are described using block diagrams where feasible, and input--output tables, and the software implementation of each function is presented in equations and structured flow charts. Included are a glossary of all symbols used to define the requirements, and an appendix of supportive material.
Algorithm For Optimal Control Of Large Structures
NASA Technical Reports Server (NTRS)
Salama, Moktar A.; Garba, John A..; Utku, Senol
1989-01-01
Cost of computation appears competitive with other methods. Problem to compute optimal control of forced response of structure with n degrees of freedom identified in terms of smaller number, r, of vibrational modes. Article begins with Hamilton-Jacobi formulation of mechanics and use of quadratic cost functional. Complexity reduced by alternative approach in which quadratic cost functional expressed in terms of control variables only. Leads to iterative solution of second-order time-integral matrix Volterra equation of second kind containing optimal control vector. Cost of algorithm, measured in terms of number of computations required, is of order of, or less than, cost of prior algoritms applied to similar problems.
Efficient Controls for Finitely Convergent Sequential Algorithms
Chen, Wei; Herman, Gabor T.
2010-01-01
Finding a feasible point that satisfies a set of constraints is a common task in scientific computing: examples are the linear feasibility problem and the convex feasibility problem. Finitely convergent sequential algorithms can be used for solving such problems; an example of such an algorithm is ART3, which is defined in such a way that its control is cyclic in the sense that during its execution it repeatedly cycles through the given constraints. Previously we found a variant of ART3 whose control is no longer cyclic, but which is still finitely convergent and in practice it usually converges faster than ART3 does. In this paper we propose a general methodology for automatic transformation of finitely convergent sequential algorithms in such a way that (i) finite convergence is retained and (ii) the speed of convergence is improved. The first of these two properties is proven by mathematical theorems, the second is illustrated by applying the algorithms to a practical problem. PMID:20953327
NASA Astrophysics Data System (ADS)
Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing
2015-08-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).
Algorithms for optimizing CT fluence control
NASA Astrophysics Data System (ADS)
Hsieh, Scott S.; Pelc, Norbert J.
2014-03-01
The ability to customize the incident x-ray fluence in CT via beam-shaping filters or mA modulation is known to improve image quality and/or reduce radiation dose. Previous work has shown that complete control of x-ray fluence (ray-by-ray fluence modulation) would further improve dose efficiency. While complete control of fluence is not currently possible, emerging concepts such as dynamic attenuators and inverse-geometry CT allow nearly complete control to be realized. Optimally using ray-by-ray fluence modulation requires solving a very high-dimensional optimization problem. Most optimization techniques fail or only provide approximate solutions. We present efficient algorithms for minimizing mean or peak variance given a fixed dose limit. The reductions in variance can easily be translated to reduction in dose, if the original variance met image quality requirements. For mean variance, a closed form solution is derived. The peak variance problem is recast as iterated, weighted mean variance minimization, and at each iteration it is possible to bound the distance to the optimal solution. We apply our algorithms in simulations of scans of the thorax and abdomen. Peak variance reductions of 45% and 65% are demonstrated in the abdomen and thorax, respectively, compared to a bowtie filter alone. Mean variance shows smaller gains (about 15%).
Redmond, J.; Parker, G.
1993-07-01
This paper examines the role of the control objective and the control time in determining fuel-optimal actuator placement for structural vibration suppression. A general theory is developed that can be easily extended to include alternative performance metrics such as energy and time-optimal control. The performance metric defines a convex admissible control set which leads to a max-min optimization problem expressing optimal location as a function of initial conditions and control time. A solution procedure based on a nested Genetic Algorithm is presented and applied to an example problem. Results indicate that the optimal locations vary widely as a function of control time and initial conditions.
Genetic Algorithm based Decentralized PI Type Controller: Load Frequency Control
NASA Astrophysics Data System (ADS)
Dwivedi, Atul; Ray, Goshaidas; Sharma, Arun Kumar
2016-05-01
This work presents a design of decentralized PI type Linear Quadratic (LQ) controller based on genetic algorithm (GA). The proposed design technique allows considerable flexibility in defining the control objectives and it does not consider any knowledge of the system matrices and moreover it avoids the solution of algebraic Riccati equation. To illustrate the results of this work, a load-frequency control problem is considered. Simulation results reveal that the proposed scheme based on GA is an alternative and attractive approach to solve load-frequency control problem from both performance and design point of views.
Digital control algorithms for microgravity isolation systems
NASA Technical Reports Server (NTRS)
Sinha, Alok; Wang, Yung-Peng
1992-01-01
New digital control algorithms were developed to achieve the desired acceleration transmissibility function. The attractive electromagnets have been taken as actuators. The relative displacement and the acceleration of the mass were used as feedback signals. Two approaches were developed to find that controller transfer function in Z-domain, which yields the desired transmissibility at each frequency. In the first approach, the controller transfer function is obtained by assuming that the desired transmissibility is known in Z-domain. Since the desired transmissibility H sub d(S) = 1/(tauS+1)(exp 2) is given in S-domain, the first task is to obtain the desired transmissibility in Z-domain. There are three methods to perform this task: bilinear transformation, and backward and forward rectangular rules. The bilinear transformation and backward rectangular rule lead to improper controller transfer functions, which are physically not realizable. The forward rectangular rule does lead to a physically realizable controller. However, this controller is found to be marginally stable because of a pole at Z=1. In order to eliminate this pole, a hybrid control structure is proposed. Here the control input is composed of two parts: analog and digital. The analog input simply represents the velocity (or the integral of acceleration) feedback; and the digital controller which uses only relative displacement signal, is then obtained to achieve the desired closed-loop transfer function. The stability analysis indicates that the controller transfer function is stable for typical values of sampling period. In the second approach, the aforementioned hybrid control structure is again used. First, an analog controller transfer function corresponding to relative displacement feedback is obtained to achieve the transmissibility as 1/(tauS+1)(exp 2). Then the transfer function for the digital control input is obtained by discretizing this analog controller transfer function via bilinear
Santos, Josue; Jones, Sasia; Wakefield, Daniel; Grady, James; Andemariam, Biree
2016-01-01
Background. A treatment algorithm for sickle cell disease (SCD) pain in adults presenting to a single emergency department (ED) was developed prioritizing initiation of patient controlled analgesia (PCA) for patients awaiting hospitalization. Objectives. Evaluate the proportion of ED visits in which PCA was started in the ED. Methods. A two-year retrospective chart review of consecutive SCD pain ED visits was undertaken. Data abstracted included PCA initiation, low versus high utilizer status, pain scores, bolus opioid number, treatment times, and length of hospitalization. Results. 258 visits resulted in hospitalization. PCA was initiated in 230 (89%) visits of which 157 (68%) were initiated in the ED. Time to PCA initiation was longer when PCA was begun after hospitalization versus in the ED (8.6 versus 4.5 hours, p < 0.001). ED PCA initiation was associated with fewer opioid boluses following decision to admit and less time without analgesic treatment (all p < 0.05). Mean pain intensity (MPI) reduction did not differ between groups. Among visits where PCA was begun in the ED, low utilizers demonstrated greater MPI reduction than high utilizers (2.8 versus 2.0, p = 0.04). Conclusions. ED PCA initiation for SCD-related pain is possible and associated with more timely analgesic delivery. PMID:27445606
A quadratic weight selection algorithm. [for optimal flight control
NASA Technical Reports Server (NTRS)
Broussard, J. R.
1981-01-01
A new numerical algorithm is presented which determines a positive semi-definite state weighting matrix in the linear-quadratic optimal control design problem. The algorithm chooses the weighting matrix by placing closed-loop eigenvalues and eigenvectors near desired locations using optimal feedback gains. A simplified flight control design example is used to illustrate the algorithms capabilities.
Mahmoodpoor, Ata; Hamishehkar, Hadi; Shadvar, Kamran; Beigmohammadi, Mohammadtaghi; Iranpour, Afshin; Sanaie, Sarvin
2016-01-01
Background and Aims: The association between hyperglycemia and mortality is believed to be influenced by the presence of diabetes mellitus (DM). In this study, we evaluated the effect of preexisting hyperglycemia on the association between acute blood glucose management and mortality in critically ill patients. The primary objective of the study was the relationship between HbA1c and mortality in critically ill patients. Secondary objectives of the study were relationship between Intensive Care Unit (ICU) admission blood glucose and glucose control during ICU stay with mortality in critically ill patients. Materials and Methods: Five hundred patients admitted to two ICUs were enrolled. Blood sugar and hemoglobin A1c (HbA1c) concentrations on ICU admission were measured. Age, sex, history of DM, comorbidities, Acute Physiology and Chronic Health Evaluation II score, sequential organ failure assessment score, hypoglycemic episodes, drug history, mortality, and development of acute kidney injury and liver failure were noted for all patients. Results: Without considering the history of diabetes, nonsurvivors had significantly higher HbA1c values compared to survivors (7.25 ± 1.87 vs. 6.05 ± 1.22, respectively, P < 0.001). Blood glucose levels in ICU admission showed a significant correlation with risk of death (P < 0.006, confidence interval [CI]: 1.004–1.02, relative risk [RR]: 1.01). Logistic regression analysis revealed that HbA1c increased the risk of death; with each increase in HbA1c level, the risk of death doubled. However, this relationship was not statistically significant (P: 0.161, CI: 0.933–1.58, RR: 1.2). Conclusions: Acute hyperglycemia significantly affects mortality in the critically ill patients; this relation is also influenced by chronic hyperglycemia. PMID:27076705
Multiobjective Genetic Algorithm applied to dengue control.
Florentino, Helenice O; Cantane, Daniela R; Santos, Fernando L P; Bannwart, Bettina F
2014-12-01
Dengue fever is an infectious disease caused by a virus of the Flaviridae family and transmitted to the person by a mosquito of the genus Aedes aegypti. This disease has been a global public health problem because a single mosquito can infect up to 300 people and between 50 and 100 million people are infected annually on all continents. Thus, dengue fever is currently a subject of research, whether in the search for vaccines and treatments for the disease or efficient and economical forms of mosquito control. The current study aims to study techniques of multiobjective optimization to assist in solving problems involving the control of the mosquito that transmits dengue fever. The population dynamics of the mosquito is studied in order to understand the epidemic phenomenon and suggest strategies of multiobjective programming for mosquito control. A Multiobjective Genetic Algorithm (MGA_DENGUE) is proposed to solve the optimization model treated here and we discuss the computational results obtained from the application of this technique. PMID:25230238
Automatic-control-algorithm effects on energy production
McNerney, G.M.
1981-01-01
Algorithm control strategy for unattended wind turbine operation is a potentially important aspect of wind energy production that has thus far escaped treatment in the literature. Early experience in automatic operation of the Sandia 17-m VAWT has demonstrated the need for a systematic study of control algorithms. To this end, a computer model has been developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model has been used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long-term energy production. An attempt has been made to generalize these results from local site and turbine characteristics to obtain general guidelines for control algorithm design.
Stabilizing the Richardson eigenvector algorithm by controlling chaos
He, S.
1997-03-01
By viewing the operations of the Richardson purification algorithm as a discrete time dynamical process, we propose a method to overcome the instability of this eigenvector algorithm by controlling chaos. We present theoretical analysis and numerical results on the behavior and performance of the stabilized algorithm. {copyright} {ital 1997 American Institute of Physics.}
Evaluation of TCP congestion control algorithms.
Long, Robert Michael
2003-12-01
Sandia, Los Alamos, and Lawrence Livermore National Laboratories currently deploy high speed, Wide Area Network links to permit remote access to their Supercomputer systems. The current TCP congestion algorithm does not take full advantage of high delay, large bandwidth environments. This report involves evaluating alternative TCP congestion algorithms and comparing them with the currently used congestion algorithm. The goal was to find if an alternative algorithm could provide higher throughput with minimal impact on existing network traffic. The alternative congestion algorithms used were Scalable TCP and High-Speed TCP. Network lab experiments were run to record the performance of each algorithm under different network configurations. The network configurations used were back-to-back with no delay, back-to-back with a 30ms delay, and two-to-one with a 30ms delay. The performance of each algorithm was then compared to the existing TCP congestion algorithm to determine if an acceptable alternative had been found. Comparisons were made based on throughput, stability, and fairness.
Force-Control Algorithm for Surface Sampling
NASA Technical Reports Server (NTRS)
Acikmese, Behcet; Quadrelli, Marco B.; Phan, Linh
2008-01-01
A G-FCON algorithm is designed for small-body surface sampling. It has a linearization component and a feedback component to enhance performance. The algorithm regulates the contact force between the tip of a robotic arm attached to a spacecraft and a surface during sampling.
An algorithm for obtaining bang-bang control laws
NASA Technical Reports Server (NTRS)
Wen, J.; Desrochers, A. A.
1987-01-01
A new computational method for solving control problems, when it is desired that the control action be bang-bang is presented. A gradient-based algorithm is developed where the switching times are updated to minimize the final state missed distance. The algorithm explains how a change in a switching time propagates through the other switching times and affects the final state. The algorithm is applicable to linear and nonlinear problems, including multiinput systems.
Advanced CHP Control Algorithms: Scope Specification
Katipamula, Srinivas; Brambley, Michael R.
2006-04-28
The primary objective of this multiyear project is to develop algorithms for combined heat and power systems to ensure optimal performance, increase reliability, and lead to the goal of clean, efficient, reliable and affordable next generation energy systems.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
NASA Astrophysics Data System (ADS)
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Rate control algorithm based on frame complexity estimation for MVC
NASA Astrophysics Data System (ADS)
Yan, Tao; An, Ping; Shen, Liquan; Zhang, Zhaoyang
2010-07-01
Rate control has not been well studied for multi-view video coding (MVC). In this paper, we propose an efficient rate control algorithm for MVC by improving the quadratic rate-distortion (R-D) model, which reasonably allocate bit-rate among views based on correlation analysis. The proposed algorithm consists of four levels for rate bits control more accurately, of which the frame layer allocates bits according to frame complexity and temporal activity. Extensive experiments show that the proposed algorithm can efficiently implement bit allocation and rate control according to coding parameters.
Global search algorithm for optimal control
NASA Technical Reports Server (NTRS)
Brocker, D. H.; Kavanaugh, W. P.; Stewart, E. C.
1970-01-01
Random-search algorithm employs local and global properties to solve two-point boundary value problem in Pontryagin maximum principle for either fixed or variable end-time problems. Mixed boundary value problem is transformed to an initial value problem. Mapping between initial and terminal values utilizes hybrid computer.
A controllable sensor management algorithm capable of learning
NASA Astrophysics Data System (ADS)
Osadciw, Lisa A.; Veeramacheneni, Kalyan K.
2005-03-01
Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.
The evaluation of the OSGLR algorithm for restructurable controls
NASA Technical Reports Server (NTRS)
Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.
1986-01-01
The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.
Montgomery, Ann L.; Fadel, Shaza; Kumar, Rajesh; Bondy, Sue; Moineddin, Rahim; Jha, Prabhat
2014-01-01
Background Research in areas of low skilled attendant coverage found that maternal mortality is paradoxically higher in women who seek obstetric care. We estimated the effect of health-facility admission on maternal survival, and how this effect varies with skilled attendant coverage across India. Methods/Findings Using unmatched population-based case-control analysis of national datasets, we compared the effect of health-facility admission at any time (antenatal, intrapartum, postpartum) on maternal deaths (cases) to women reporting pregnancies (controls). Probability of maternal death decreased with increasing skilled attendant coverage, among both women who were and were not admitted to a health-facility, however, the risk of death among women who were admitted was higher (at 50% coverage, OR = 2.32, 95% confidence interval 1.85–2.92) than among those women who were not; while at higher levels of coverage, the effect of health-facility admission was attenuated. In a secondary analysis, the probability of maternal death decreased with increasing coverage among both women admitted for delivery or delivered at home but there was no effect of admission for delivery on mortality risk (50% coverage, OR = 1.0, 0.80–1.25), suggesting that poor quality of obstetric care may have attenuated the benefits of facility-based care. Subpopulation analysis of obstetric hemorrhage cases and report of ‘excessive bleeding’ in controls showed that the probability of maternal death decreased with increasing skilled attendant coverage; but the effect of health-facility admission was attenuated (at 50% coverage, OR = 1.47, 0.95–1.79), suggesting that some of the effect in the main model can be explained by women arriving at facility with complications underway. Finally, highest risk associated with health-facility admission was clustered in women with education 8 years. Conclusions The effect of health-facility admission did vary by skilled attendant coverage, and
Regularization design and control of change admission in prior-image-based reconstruction
NASA Astrophysics Data System (ADS)
Dang, Hao; Siewerdsen, Jeffrey H.; Stayman, J. Webster
2014-03-01
Nearly all reconstruction methods are controlled through various parameter selections. Traditionally, such parameters are used to specify a particular noise and resolution trade-off in the reconstructed image volumes. The introduction of reconstruction methods that incorporate prior image information has demonstrated dramatic improvements in dose utilization and image quality, but has complicated the selection of reconstruction parameters including those associated with balancing information used from prior images with that of the measurement data. While a noise-resolution tradeoff still exists, other potentially detrimental effects are possible with poor prior image parameter values including the possible introduction of false features and the failure to incorporate sufficient prior information to gain any improvements. Traditional parameter selection methods such as heuristics based on similar imaging scenarios are subject to error and suboptimal solutions while exhaustive searches can involve a large number of time-consuming iterative reconstructions. We propose a novel approach that prospectively determines optimal prior image regularization strength to accurately admit specific anatomical changes without performing full iterative reconstructions. This approach leverages analytical approximations to the implicitly defined prior image-based reconstruction solution and predictive metrics used to estimate imaging performance. The proposed method is investigated in phantom experiments and the shift-variance and data-dependence of optimal prior strength is explored. Optimal regularization based on the predictive approach is shown to agree well with traditional exhaustive reconstruction searches, while yielding substantial reductions in computation time. This suggests great potential of the proposed methodology in allowing for prospective patient-, data-, and change-specific customization of prior-image penalty strength to ensure accurate reconstruction of specific
Control strategies and algorithms for large astronomical optical telescope
NASA Astrophysics Data System (ADS)
Yang, Shihai
2010-07-01
This paper gives a summary on control strategies and algorithms for contemporary large astronomical optical telescopes. The study lays emphasis on high precision tracking for large astronomical optical telescopes with large inertia, ultra-low speed and multi-disturbance. The control strategies and algorithms of some telescopes based on direct drive or friction drive are analyzed carefully. Finally, the future development in this field is presented.
Comparative analysis of PSO algorithms for PID controller tuning
NASA Astrophysics Data System (ADS)
Štimac, Goranka; Braut, Sanjin; Žigulić, Roberto
2014-09-01
The active magnetic bearing(AMB) suspends the rotating shaft and maintains it in levitated position by applying controlled electromagnetic forces on the rotor in radial and axial directions. Although the development of various control methods is rapid, PID control strategy is still the most widely used control strategy in many applications, including AMBs. In order to tune PID controller, a particle swarm optimization(PSO) method is applied. Therefore, a comparative analysis of particle swarm optimization(PSO) algorithms is carried out, where two PSO algorithms, namely (1) PSO with linearly decreasing inertia weight(LDW-PSO), and (2) PSO algorithm with constriction factor approach(CFA-PSO), are independently tested for different PID structures. The computer simulations are carried out with the aim of minimizing the objective function defined as the integral of time multiplied by the absolute value of error(ITAE). In order to validate the performance of the analyzed PSO algorithms, one-axis and two-axis radial rotor/active magnetic bearing systems are examined. The results show that PSO algorithms are effective and easily implemented methods, providing stable convergence and good computational efficiency of different PID structures for the rotor/AMB systems. Moreover, the PSO algorithms prove to be easily used for controller tuning in case of both SISO and MIMO system, which consider the system delay and the interference among the horizontal and vertical rotor axes.
Development of a biomimetic robotic fish and its control algorithm.
Yu, Junzhi; Tan, Min; Wang, Shuo; Chen, Erkui
2004-08-01
This paper is concerned with the design of a robotic fish and its motion control algorithms. A radio-controlled, four-link biomimetic robotic fish is developed using a flexible posterior body and an oscillating foil as a propeller. The swimming speed of the robotic fish is adjusted by modulating joint's oscillating frequency, and its orientation is tuned by different joint's deflections. Since the motion control of a robotic fish involves both hydrodynamics of the fluid environment and dynamics of the robot, it is very difficult to establish a precise mathematical model employing purely analytical methods. Therefore, the fish's motion control task is decomposed into two control systems. The online speed control implements a hybrid control strategy and a proportional-integral-derivative (PID) control algorithm. The orientation control system is based on a fuzzy logic controller. In our experiments, a point-to-point (PTP) control algorithm is implemented and an overhead vision system is adopted to provide real-time visual feedback. The experimental results confirm the effectiveness of the proposed algorithms. PMID:15462446
Can Computers Simplify Admissions?
ERIC Educational Resources Information Center
Bruker, Robert M.
1978-01-01
Based on experience with a simplified admissions concept, Southern Illinois University is satisfied that the admissions process has been made easier for prospective students, high school counselors, and admissions staff. The computer does not make decisions regarding admission of a student, but reduced work loads for everyone concerned. (Author)
Impulse position control algorithms for nonlinear systems
NASA Astrophysics Data System (ADS)
Sesekin, A. N.; Nepp, A. N.
2015-11-01
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Impulse position control algorithms for nonlinear systems
Sesekin, A. N.; Nepp, A. N.
2015-11-30
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Algorithm for calculating torque base in vehicle traction control system
NASA Astrophysics Data System (ADS)
Li, Hongzhi; Li, Liang; Song, Jian; Wu, Kaihui; Qiao, Yanjuan; Liu, Xingchun; Xia, Yongguang
2012-11-01
Existing research on the traction control system(TCS) mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS (referred to as the torque base in this paper), which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop(HIL) simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.
A disturbance based control/structure design algorithm
NASA Technical Reports Server (NTRS)
Mclaren, Mark D.; Slater, Gary L.
1989-01-01
Some authors take a classical approach to the simultaneous structure/control optimization by attempting to simultaneously minimize the weighted sum of the total mass and a quadratic form, subject to all of the structural and control constraints. Here, the optimization will be based on the dynamic response of a structure to an external unknown stochastic disturbance environment. Such a response to excitation approach is common to both the structural and control design phases, and hence represents a more natural control/structure optimization strategy than relying on artificial and vague control penalties. The design objective is to find the structure and controller of minimum mass such that all the prescribed constraints are satisfied. Two alternative solution algorithms are presented which have been applied to this problem. Each algorithm handles the optimization strategy and the imposition of the nonlinear constraints in a different manner. Two controller methodologies, and their effect on the solution algorithm, will be considered. These are full state feedback and direct output feedback, although the problem formulation is not restricted solely to these forms of controller. In fact, although full state feedback is a popular choice among researchers in this field (for reasons that will become apparent), its practical application is severely limited. The controller/structure interaction is inserted by the imposition of appropriate closed-loop constraints, such as closed-loop output response and control effort constraints. Numerical results will be obtained for a representative flexible structure model to illustrate the effectiveness of the solution algorithms.
Tuning of active vibration controllers for ACTEX by genetic algorithm
NASA Astrophysics Data System (ADS)
Kwak, Moon K.; Denoyer, Keith K.
1999-06-01
This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.
Control algorithms for aerobraking in the Martian atmosphere
NASA Technical Reports Server (NTRS)
Ward, Donald T.; Shipley, Buford W., Jr.
1991-01-01
The Analytic Predictor Corrector (APC) and Energy Controller (EC) atmospheric guidance concepts were adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. Changes are made to the APC to improve its robustness to density variations. These changes include adaptation of a new exit phase algorithm, an adaptive transition velocity to initiate the exit phase, refinement of the reference dynamic pressure calculation and two improved density estimation techniques. The modified controller with the hybrid density estimation technique is called the Mars Hybrid Predictor Corrector (MHPC), while the modified controller with a polynomial density estimator is called the Mars Predictor Corrector (MPC). A Lyapunov Steepest Descent Controller (LSDC) is adapted to control the vehicle. The LSDC lacked robustness, so a Lyapunov tracking exit phase algorithm is developed to guide the vehicle along a reference trajectory. This algorithm, when using the hybrid density estimation technique to define the reference path, is called the Lyapunov Hybrid Tracking Controller (LHTC). With the polynomial density estimator used to define the reference trajectory, the algorithm is called the Lyapunov Tracking Controller (LTC). These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. The MHPC, MPC, LHTC, and LTC show dramatic improvements in robustness over the APC and EC.
Precise flight-path control using a predictive algorithm
NASA Technical Reports Server (NTRS)
Hess, R. A.; Jung, Y. C.
1991-01-01
Generalized predictive control describes an algorithm for the control of dynamic systems in which a control input is generated that minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. A design technique is discussed for applying the single-input/single-output generalized predictive control algorithm to a problem of longitudinal/vertical terrain-following flight of a rotorcraft. By using the generalized predictive control technique to provide inputs to a classically designed stability and control augmentation system, it is demonstrated that a robust flight-path control system can be created that exhibits excellent tracking performance.
Ultramaneuverable steering control algorithms for terrain transitions
NASA Astrophysics Data System (ADS)
Torrie, Mel W.; Koch, Ralf; Bahl, Vikas; Cripps, Don
1999-07-01
The Center for Self-Organizing and Intelligent Systems has built several vehicles with ultra-maneuverable steering capability. Each drive wheel on the vehicle can be independently set at any angle with respect to the vehicle body and the vehicles can rotate or translate in any direction. The vehicles are expected to operate on a wide range of terrain surfaces and problems arise in effectively controlling changes in wheel steering angles as the vehicle transitions from one extreme running surface to another. Controllers developed for smooth surfaces may not perform well on rough or 'sticky' surfaces and vice versa. The approach presented involves the development of a model of the steering motor with the static and viscous friction of the steering motor load included. The model parameters are then identified through a series of environmental tests using a vehicle wheel assembly and the model thus obtained is used for control law development. Four different robust controllers were developed and evaluated through simulation and vehicle testing. The findings of this development will be presented.
Applying new optimization algorithms to more predictive control
Wright, S.J.
1996-03-01
The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.
On-board attitude determination and control algorithms for SAMPEX
NASA Technical Reports Server (NTRS)
Flatley, Thomas W.; Forden, Josephine K.; Henretty, Debra A.; Lightsey, E. Glenn; Markley, F. Landis
1990-01-01
Algorithms for onboard attitude determination and control of the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) were developed. The algorithms include spacecraft ephemeris and geomagnetic field models, attitude determination with 2 degree accuracy, control of pitch axis pointing to the sun and yaw axis pointing away from the Earth to achieve control of pitch axis within 5 degrees of sunline, momentum unloading, and nutation damping. The closed loop simulations were performed on a VAX 8830 using a prototype version of the on-board software.
A Review of Control Algorithms for Autonomous Quadrotors
NASA Astrophysics Data System (ADS)
Zulu, Andrew; John, Samuel
The quadrotor unmanned aerial vehicle is a great platform for control systems research as its nonlinear nature and under-actuated configuration make it ideal to synthesize and analyze control algorithms. After a brief explanation of the system, several algorithms have been analyzed including their advantages and disadvantages: PID, Linear Quadratic Regulator (LQR), Sliding mode, Backstepping, Feedback linearization, Adaptive, Robust, Optimal, L1, H-infinity, Fuzzy logic and Artificial neutral networks. The conclusion of this work is a proposal of hybrid systems to be considered as they combine advantages from more than one control philosophy.
Discrete-time minimal control synthesis adaptive algorithm
NASA Astrophysics Data System (ADS)
di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.
2010-12-01
This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.
NASA Astrophysics Data System (ADS)
Zhang, Xianxia; Wang, Jian; Qin, Tinggao
2003-09-01
Intelligent control algorithms are introduced into the control system of temperature and humidity. A multi-mode control algorithm of PI-Single Neuron is proposed for single loop control of temperature and humidity. In order to remove the coupling between temperature and humidity, a new decoupling method is presented, which is called fuzzy decoupling. The decoupling is achieved by using a fuzzy controller that dynamically modifies the static decoupling coefficient. Taking the control algorithm of PI-Single Neuron as the single loop control of temperature and humidity, the paper provides the simulated output response curves with no decoupling control, static decoupling control and fuzzy decoupling control. Those control algorithms are easily implemented in singlechip-based hardware systems.
Stall Recovery Guidance Algorithms Based on Constrained Control Approaches
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje; Kaneshige, John; Acosta, Diana
2016-01-01
Aircraft loss-of-control, in particular approach to stall or fully developed stall, is a major factor contributing to aircraft safety risks, which emphasizes the need to develop algorithms that are capable of assisting the pilots to identify the problem and providing guidance to recover the aircraft. In this paper we present several stall recovery guidance algorithms, which are implemented in the background without interfering with flight control system and altering the pilot's actions. They are using input and state constrained control methods to generate guidance signals, which are provided to the pilot in the form of visual cues. It is the pilot's decision to follow these signals. The algorithms are validated in the pilot-in-the loop medium fidelity simulation experiment.
Adaptive process control using fuzzy logic and genetic algorithms
NASA Technical Reports Server (NTRS)
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Adaptive Process Control with Fuzzy Logic and Genetic Algorithms
NASA Technical Reports Server (NTRS)
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
Athans, M. (Editor); Willsky, A. S. (Editor)
1982-01-01
The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
1975-01-01
Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.
Comparative analysis of algorithms for lunar landing control
NASA Astrophysics Data System (ADS)
Zhukov, B. I.; Likhachev, V. N.; Sazonov, V. V.; Sikharulidze, Yu. G.; Tuchin, A. G.; Tuchin, D. A.; Fedotov, V. P.; Yaroshevskii, V. S.
2015-11-01
For the descent from the pericenter of a prelanding circumlunar orbit a comparison of three algorithms for the control of lander motion is performed. These algorithms use various combinations of terminal and programmed control in a trajectory including three parts: main braking, precision braking, and descent with constant velocity. In the first approximation, autonomous navigational measurements are taken into account and an estimate of the disturbances generated by movement of the fuel in the tanks was obtained. Estimates of the accuracy for landing placement, fuel consumption, and performance of the conditions for safe lunar landing are obtained.
Application of genetic algorithms to tuning fuzzy control systems
NASA Technical Reports Server (NTRS)
Espy, Todd; Vombrack, Endre; Aldridge, Jack
1993-01-01
Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.
Design of PID-type controllers using multiobjective genetic algorithms.
Herreros, Alberto; Baeyens, Enrique; Perán, José R
2002-10-01
The design of a PID controller is a multiobjective problem. A plant and a set of specifications to be satisfied are given. The designer has to adjust the parameters of the PID controller such that the feedback interconnection of the plant and the controller satisfies the specifications. These specifications are usually competitive and any acceptable solution requires a tradeoff among them. An approach for adjusting the parameters of a PID controller based on multiobjective optimization and genetic algorithms is presented in this paper. The MRCD (multiobjective robust control design) genetic algorithm has been employed. The approach can be easily generalized to design multivariable coupled and decentralized PID loops and has been successfully validated for a large number of experimental cases. PMID:12398277
Optimizing the controllability of arbitrary networks with genetic algorithm
NASA Astrophysics Data System (ADS)
Li, Xin-Feng; Lu, Zhe-Ming
2016-04-01
Recently, as the controllability of complex networks attracts much attention, how to optimize networks' controllability has become a common and urgent problem. In this paper, we develop an efficient genetic algorithm oriented optimization tool to optimize the controllability of arbitrary networks consisting of both state nodes and control nodes under Popov-Belevitch-Hautus rank condition. The experimental results on a number of benchmark networks show the effectiveness of this method and the evolution of network topology is captured. Furthermore, we explore how network structure affects its controllability and find that the sparser a network is, the more control nodes are needed to control it and the larger the differences between node degrees, the more control nodes are needed to achieve the full control. Our framework provides an alternative to controllability optimization and can be applied to arbitrary networks without any limitations.
Control algorithm implementation for a redundant degree of freedom manipulator
NASA Technical Reports Server (NTRS)
Cohan, Steve
1991-01-01
This project's purpose is to develop and implement control algorithms for a kinematically redundant robotic manipulator. The manipulator is being developed concurrently by Odetics Inc., under internal research and development funding. This SBIR contract supports algorithm conception, development, and simulation, as well as software implementation and integration with the manipulator hardware. The Odetics Dexterous Manipulator is a lightweight, high strength, modular manipulator being developed for space and commercial applications. It has seven fully active degrees of freedom, is electrically powered, and is fully operational in 1 G. The manipulator consists of five self-contained modules. These modules join via simple quick-disconnect couplings and self-mating connectors which allow rapid assembly/disassembly for reconfiguration, transport, or servicing. Each joint incorporates a unique drive train design which provides zero backlash operation, is insensitive to wear, and is single fault tolerant to motor or servo amplifier failure. The sensing system is also designed to be single fault tolerant. Although the initial prototype is not space qualified, the design is well-suited to meeting space qualification requirements. The control algorithm design approach is to develop a hierarchical system with well defined access and interfaces at each level. The high level endpoint/configuration control algorithm transforms manipulator endpoint position/orientation commands to joint angle commands, providing task space motion. At the same time, the kinematic redundancy is resolved by controlling the configuration (pose) of the manipulator, using several different optimizing criteria. The center level of the hierarchy servos the joints to their commanded trajectories using both linear feedback and model-based nonlinear control techniques. The lowest control level uses sensed joint torque to close torque servo loops, with the goal of improving the manipulator dynamic behavior
Synthesis of nonlinear control strategies from fuzzy logic control algorithms
NASA Technical Reports Server (NTRS)
Langari, Reza
1993-01-01
Fuzzy control has been recognized as an alternative to conventional control techniques in situations where the plant model is not sufficiently well known to warrant the application of conventional control techniques. Precisely what fuzzy control does and how it does what it does is not quite clear, however. This important issue is discussed and in particular it is shown how a given fuzzy control scheme can resolve into a nonlinear control law and that in those situations the success of fuzzy control hinges on its ability to compensate for nonlinearities in plant dynamics.
An hourglass control algorithm for Lagrangian Smooth Particle Hydrodynamics
NASA Astrophysics Data System (ADS)
Ganzenmüller, Georg C.
2015-04-01
This paper presents a stabilization scheme which addresses the rank-deficiency problem in meshless collocation methods for solid mechanics. Specifically, Smooth-Particle Hydrodynamics (SPH) in the Total Lagrangian formalism is considered. This method is rank-deficient in the sense that the SPH approximation of the deformation gradient is not unique with respect to the positions of the integration points. The non-uniqueness can result in the formation of zero-energy modes. If undetected, these modes can grow and completely dominate the solution. Here, an algorithm is introduced, which effectively suppresses these modes in a fashion similar to hour-glass control mechanisms in Finite-Element methods. Simulations utilizing this control algorithm result exhibit much improved stability, accuracy, and error convergence properties. In contrast to an alternative method which eliminates zero-energy modes, namely the use of additional integration points, the here presented algorithm is easy to implement and computationally very efficient.
Control of nonlinear processes by using linear model predictive control algorithms.
Gu, Bingfeng; Gupta, Yash P
2008-04-01
Most chemical processes are inherently nonlinear. However, because of their simplicity, linear control algorithms have been used for the control of nonlinear processes. In this study, the use of the dynamic matrix control algorithm and a simplified model predictive control algorithm for control of a bench-scale pH neutralization process is investigated. The nonlinearity is handled by dividing the operating region into sub-regions and by switching the controller model as the process moves from one sub-region to another. A simple modification for model predictive control algorithms is presented to handle the switching. The simulation and experimental results show that the modification can provide a significant improvement in the control of nonlinear processes. PMID:18255068
ERIC Educational Resources Information Center
Lucido, Jerome A.
2012-01-01
When one thinks of seminal publications in college admission, the first piece that comes to mind is B. Alden Thresher's "College Admissions in the Public Interest" (1966). Thresher's work, relevant to this day, is credited with being the foundational document of the admission profession. McDonough and Robertson's 1995 study, commissioned by NACAC,…
Performance evaluation of power control algorithms in wireless cellular networks
NASA Astrophysics Data System (ADS)
Temaneh-Nyah, C.; Iita, V.
2014-10-01
Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.
Fully efficient time-parallelized quantum optimal control algorithm
NASA Astrophysics Data System (ADS)
Riahi, M. K.; Salomon, J.; Glaser, S. J.; Sugny, D.
2016-04-01
We present a time-parallelization method that enables one to accelerate the computation of quantum optimal control algorithms. We show that this approach is approximately fully efficient when based on a gradient method as optimization solver: the computational time is approximately divided by the number of available processors. The control of spin systems, molecular orientation, and Bose-Einstein condensates are used as illustrative examples to highlight the wide range of applications of this numerical scheme.
Thrust vector control algorithm design for the Cassini spacecraft
NASA Technical Reports Server (NTRS)
Enright, Paul J.
1993-01-01
This paper describes a preliminary design of the thrust vector control algorithm for the interplanetary spacecraft, Cassini. Topics of discussion include flight software architecture, modeling of sensors, actuators, and vehicle dynamics, and controller design and analysis via classical methods. Special attention is paid to potential interactions with structural flexibilities and propellant dynamics. Controller performance is evaluated in a simulation environment built around a multi-body dynamics model, which contains nonlinear models of the relevant hardware and preliminary versions of supporting attitude determination and control functions.
Distributed autonomous systems: resource management, planning, and control algorithms
NASA Astrophysics Data System (ADS)
Smith, James F., III; Nguyen, ThanhVu H.
2005-05-01
Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.
Integrated control algorithms for plant environment in greenhouse
NASA Astrophysics Data System (ADS)
Zhang, Kanyu; Deng, Lujuan; Gong, Youmin; Wang, Shengxue
2003-09-01
In this paper a survey of plant environment control in artificial greenhouse was put forward for discussing the future development. Firstly, plant environment control started with the closed loop control of air temperature in greenhouse. With the emergence of higher property computer, the adaptive control algorithm and system identification were integrated into the control system. As adaptation control is more depending on observation of variables by sensors and yet many variables are unobservable or difficult to observe, especially for observation of crop growth status, so model-based control algorithm were developed. In order to evade modeling difficulty, one method is predigesting the models and the other method is utilizing fuzzy logic and neural network technology that realize the models by the black box and gray box theory. Studies on control method of plant environment in greenhouse by means of expert system (ES) and artificial intelligence (AI) have been initiated and developed. Nowadays, the research of greenhouse environment control focus on energy saving, optimal economic profit, enviornment protection and continualy develop.
FEM Optimization of Spin Forming Using a Fuzzy Control Algorithm
NASA Astrophysics Data System (ADS)
Yoshihara, S.; Ray, P.; MacDonald, B. J.; Koyama, H.; Kawahara, M.
2004-06-01
Finite element (FE) simulation of the manufacturing of a conical nosing such as a pressure vessel from circular tubes, using the spin forming method, was performed on the commercially available software package, ANSYS/LS-DYNA3D. The finite element method (FEM) provides a powerful tool for evaluating the potential to form the pressure vessel with proposed modifications to the process. The use of fuzzy logic inference as a control system to achieve the designed shape of the pressure vessel was investigated using the FEM. The path of the roller as a process parameter was decided by the fuzzy inference control algorithm from information of the result of deformation of each element respectively. The fuzzy control algorithm investigated was validated from the results of the production process time and the deformed shape using FE simulation.
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.
Algorithm development for the control design of flexible structures
NASA Technical Reports Server (NTRS)
Skelton, R. E.
1983-01-01
The critical problems associated with the control of highly damped flexible structures are outlined. The practical problems include: high performance; assembly in space, configuration changes; on-line controller software design; and lack of test data. Underlying all of these problems is the central problem of modeling errors. To justify the expense of a space structure, the performance requirements will necessarily be very severe. On the other hand, the absence of economical tests precludes the availability of reliable data before flight. A design algorithm is offered which: (1) provides damping for a larger number of modes than the optimal attitude controller controls; (2) coordinates the rate of feedback design with the attitude control design by use of a similar cost function; and (3) provides model reduction and controller reduction decisions which are systematically connected to the mathematical statement of the control objectives and the disturbance models.
Backup Attitude Control Algorithms for the MAP Spacecraft
NASA Technical Reports Server (NTRS)
ODonnell, James R., Jr.; Andrews, Stephen F.; Ericsson-Jackson, Aprille J.; Flatley, Thomas W.; Ward, David K.; Bay, P. Michael
1999-01-01
The Microwave Anisotropy Probe (MAP) is a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE) spacecraft. The MAP spacecraft will perform its mission, studying the early origins of the universe, in a Lissajous orbit around the Earth-Sun L(sub 2) Lagrange point. Due to limited mass, power, and financial resources, a traditional reliability concept involving fully redundant components was not feasible. This paper will discuss the redundancy philosophy used on MAP, describe the hardware redundancy selected (and why), and present backup modes and algorithms that were designed in lieu of additional attitude control hardware redundancy to improve the odds of mission success. Three of these modes have been implemented in the spacecraft flight software. The first onboard mode allows the MAP Kalman filter to be used with digital sun sensor (DSS) derived rates, in case of the failure of one of MAP's two two-axis inertial reference units. Similarly, the second onboard mode allows a star tracker only mode, using attitude and derived rate from one or both of MAP's star trackers for onboard attitude determination and control. The last backup mode onboard allows a sun-line angle offset to be commanded that will allow solar radiation pressure to be used for momentum management and orbit stationkeeping. In addition to the backup modes implemented on the spacecraft, two backup algorithms have been developed in the event of less likely contingencies. One of these is an algorithm for implementing an alternative scan pattern to MAP's nominal dual-spin science mode using only one or two reaction wheels and thrusters. Finally, an algorithm has been developed that uses thruster one shots while in science mode for momentum management. This algorithm has been developed in case system momentum builds up faster than anticipated, to allow adequate momentum management while minimizing interruptions to science. In this paper, each mode and
Algorithmic aspects of topology control problems for ad hoc networks
Liu, R.; Lloyd, E. L.; Marathe, M. V.; Ramanathan, R.; Ravi, S. S.
2002-01-01
Topology control problems are concerned with the assignment of power values to nodes of an ad hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing the maximum power and minimizing the total power. A general approach leading to a polynomial algorithm is presented for minimizing maximum power for a class of graph properties, called monotone properties. The difficulty of generalizing the approach to properties that are not monoione is pointed out. Problems involving the minimization of total power are known to be NP-complete even for simple graph properties. A general approach that leads to an approximation algorithm for minimizing the total power for some monotone properties is presented. Using this approach, a new approximation algorithm for the problem of minimizing the total power for obtaining a 2-node-connected graph is obtained. It is shown that this algorithm provides a constant performance guarantee. Experimental results from an implementation of the approximation algorithm are also presented.
Full design of fuzzy controllers using genetic algorithms
NASA Technical Reports Server (NTRS)
Homaifar, Abdollah; Mccormick, ED
1992-01-01
This paper examines the applicability of genetic algorithms (GA) in the complete design of fuzzy logic controllers. While GA has been used before in the development of rule sets or high performance membership functions, the interdependence between these two components dictates that they should be designed together simultaneously. GA is fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. We show the application of this new method to the development of a cart controller.
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Controller design based on μ analysis and PSO algorithm.
Lari, Ali; Khosravi, Alireza; Rajabi, Farshad
2014-03-01
In this paper an evolutionary algorithm is employed to address the controller design problem based on μ analysis. Conventional solutions to μ synthesis problem such as D-K iteration method often lead to high order, impractical controllers. In the proposed approach, a constrained optimization problem based on μ analysis is defined and then an evolutionary approach is employed to solve the optimization problem. The goal is to achieve a more practical controller with lower order. A benchmark system named two-tank system is considered to evaluate performance of the proposed approach. Simulation results show that the proposed controller performs more effective than high order H(∞) controller and has close responses to the high order D-K iteration controller as the common solution to μ synthesis problem. PMID:24314832
Student System, On-Line Admissions.
ERIC Educational Resources Information Center
White, Stephen R.
This report provides technical information on an on-line admissions system developed by Montgomery College. Part I, Systems Development, describes the background, objectives and responsibilities, system design, and reports generated by the system. Part II, Operating Instructions, describes input forms and controls, admission system functions, file…
Optimum Actuator Selection with a Genetic Algorithm for Aircraft Control
NASA Technical Reports Server (NTRS)
Rogers, James L.
2004-01-01
The placement of actuators on a wing determines the control effectiveness of the airplane. One approach to placement maximizes the moments about the pitch, roll, and yaw axes, while minimizing the coupling. For example, the desired actuators produce a pure roll moment without at the same time causing much pitch or yaw. For a typical wing, there is a large set of candidate locations for placing actuators, resulting in a substantially larger number of combinations to examine in order to find an optimum placement satisfying the mission requirements and mission constraints. A genetic algorithm has been developed for finding the best placement for four actuators to produce an uncoupled pitch moment. The genetic algorithm has been extended to find the minimum number of actuators required to provide uncoupled pitch, roll, and yaw control. A simplified, untapered, unswept wing is the model for each application.
42 CFR 456.123 - Admission review process.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 42 Public Health 4 2011-10-01 2011-10-01 false Admission review process. 456.123 Section 456.123... (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Control: Hospitals Ur Plan: Review of Need for Admission 1 § 456.123 Admission review process. The UR plan must provide that— (a)...
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
Tapp, P.A.
1992-04-01
A brief overview of adaptive control methods relating to the design of self-tuning proportional-integral-derivative (PID) controllers is given. The methods discussed include gain scheduling, self-tuning, auto-tuning, and model-reference adaptive control systems. Several process identification and parameter adjustment methods are discussed. Characteristics of the two most common types of self-tuning controllers implemented by industry (i.e., pattern recognition and process identification) are summarized. The substance of the work is a comparison of three self-tuning proportional-plus-integral (STPI) control algorithms developed to work in conjunction with the Bristol-Babcock PID control module. The STPI control algorithms are based on closed-loop cycling theory, pattern recognition theory, and model-based theory. A brief theory of operation of these three STPI control algorithms is given. Details of the process simulations developed to test the STPI algorithms are given, including an integrating process, a first-order system, a second-order system, a system with initial inverse response, and a system with variable time constant and delay. The STPI algorithms' performance with regard to both setpoint changes and load disturbances is evaluated, and their robustness is compared. The dynamic effects of process deadtime and noise are also considered. Finally, the limitations of each of the STPI algorithms is discussed, some conclusions are drawn from the performance comparisons, and a few recommendations are made. 6 refs.
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
Tapp, P.A.
1992-04-01
A brief overview of adaptive control methods relating to the design of self-tuning proportional-integral-derivative (PID) controllers is given. The methods discussed include gain scheduling, self-tuning, auto-tuning, and model-reference adaptive control systems. Several process identification and parameter adjustment methods are discussed. Characteristics of the two most common types of self-tuning controllers implemented by industry (i.e., pattern recognition and process identification) are summarized. The substance of the work is a comparison of three self-tuning proportional-plus-integral (STPI) control algorithms developed to work in conjunction with the Bristol-Babcock PID control module. The STPI control algorithms are based on closed-loop cycling theory, pattern recognition theory, and model-based theory. A brief theory of operation of these three STPI control algorithms is given. Details of the process simulations developed to test the STPI algorithms are given, including an integrating process, a first-order system, a second-order system, a system with initial inverse response, and a system with variable time constant and delay. The STPI algorithms` performance with regard to both setpoint changes and load disturbances is evaluated, and their robustness is compared. The dynamic effects of process deadtime and noise are also considered. Finally, the limitations of each of the STPI algorithms is discussed, some conclusions are drawn from the performance comparisons, and a few recommendations are made. 6 refs.
Gurieva, Tanya; Bootsma, Martin C. J.; Bonten, Marc J. M.
2013-01-01
Nosocomial infection rates due to antibiotic-resistant bacteriae, e.g., methicillin-resistant Staphylococcus aureus (MRSA) remain high in most countries. Screening for MRSA carriage followed by barrier precautions for documented carriers (so-called screen and isolate (S&I)) has been successful in some, but not all settings. Moreover, different strategies have been proposed, but comparative studies determining their relative effects and costs are not available. We, therefore, used a mathematical model to evaluate the effect and costs of different S&I strategies and to identify the critical parameters for this outcome. The dynamic stochastic simulation model consists of 3 hospitals with general wards and intensive care units (ICUs) and incorporates readmission of carriers of MRSA. Patient flow between ICUs and wards was based on real observations. Baseline prevalence of MRSA was set at 20% in ICUs and hospital-wide at 5%; ranges of costs and infection rates were based on published data. Four S&I strategies were compared to a do-nothing scenario: S&I of previously documented carriers (“flagged” patients); S&I of flagged patients and ICU admissions; S&I of flagged and group of “frequent” patients; S&I of all hospital admissions (universal screening). Evaluated levels of efficacy of S&I were 10%, 25%, 50% and 100%. Our model predicts that S&I of flagged and S&I of flagged and ICU patients are the most cost-saving strategies with fastest return of investment. For low isolation efficacy universal screening and S&I of flagged and “frequent” patients may never become cost-saving. Universal screening is predicted to prevent hardly more infections than S&I of flagged and “frequent” patients, albeit at higher costs. Whether an intervention becomes cost-saving within 10 years critically depends on costs per infection in ICU, costs of screening and isolation efficacy. PMID:23436984
Precompression quality-control algorithm for JPEG 2000.
Chang, Yu-Wei; Fang, Hung-Chi; Cheng, Chih-Chi; Chen, Chun-Chia; Chen, Liang-Gee
2006-11-01
In this paper, a precompression quality-control algorithm is proposed. It can greatly reduce computational power of the embedded block coding (EBC) and memory requirement to buffer bit streams. By using the propagation property and the randomness property of the EBC algorithm, rate and distortion of coding passes is approximately predicted. Thus, the truncation points are chosen before actual coding by the entropy coder. Therefore, the computational power, which is measured with the number of contexts to be processed, is greatly reduced since most of the computations are skipped. The memory requirement, which is measured with the amount required to buffer bit streams, is also reduced since the skipped contexts do not generate bit streams. Experimental results show that the proposed algorithm reduces the computational power of the EBC by 80% on average at 0.8 bpp compared with the conventional postcompression rate-distortion optimization algorithm. Moreover, the memory requirement is also reduced by 90%. The average PSNR degrades only about 0.1-0.3 dB, on average. PMID:17076390
RATE-ADJUSTMENT ALGORITHM FOR AGGREGATE TCP CONGESTION CONTROL
P. TINNAKORNSRISUPHAP, ET AL
2000-09-01
The TCP congestion-control mechanism is an algorithm designed to probe the available bandwidth of the network path that TCP packets traverse. However, it is well-known that the TCP congestion-control mechanism does not perform well on networks with a large bandwidth-delay product due to the slow dynamics in adapting its congestion window, especially for short-lived flows. One promising solution to the problem is to aggregate and share the path information among TCP connections that traverse the same bottleneck path, i.e., Aggregate TCP. However, this paper shows via a queueing analysis of a generalized processor-sharing (GPS) queue with regularly-varying service time that a simple aggregation of local TCP connections together into a single aggregate TCP connection can result in a severe performance degradation. To prevent such a degradation, we introduce a rate-adjustment algorithm. Our simulation confirms that by utilizing our rate-adjustment algorithm on aggregate TCP, connections which would normally receive poor service achieve significant performance improvements without penalizing connections which already receive good service.
A cooperative control algorithm for camera based observational systems.
Young, Joseph G.
2012-01-01
Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.
Technology in International Admissions
ERIC Educational Resources Information Center
White, Elizabeth
2012-01-01
In a relatively short time, technology applications have become an essential feature of the admissions business. They make the jobs of international admissions professionals easier in many ways, allowing for more robust communication with applicants and counselors, a streamlined application process, and quicker access to information about…
An Admissions Officer's Credentials
ERIC Educational Resources Information Center
Chronicle of Higher Education, 2007
2007-01-01
Marilee Jones has resigned as a dean of admissions at the Massachusetts Institute of Technology after admitting that she had misrepresented her academic degrees when first applying to work at the university in 1979. As one of the nation's most prominent admissions officers--and a leader in the movement to make the application process less…
What Admissions Officials Think
ERIC Educational Resources Information Center
Hoover, Eric
2008-01-01
Over the past two decades, college admissions has become a prime-time preoccupation. Most people know at least something about the process, especially if they have a teenager in high school and a college guide on their coffee table. Nonetheless, widespread public misconceptions persist about admissions requirements, the selection process, and the…
A Digital Control Algorithm for Magnetic Suspension Systems
NASA Technical Reports Server (NTRS)
Britton, Thomas C.
1996-01-01
An ongoing program exists to investigate and develop magnetic suspension technologies and modelling techniques at NASA Langley Research Center. Presently, there is a laboratory-scale large air-gap suspension system capable of five degree-of-freedom (DOF) control that is operational and a six DOF system that is under development. Those systems levitate a cylindrical element containing a permanent magnet core above a planar array of electromagnets, which are used for levitation and control purposes. In order to evaluate various control approaches with those systems, the Generic Real-Time State-Space Controller (GRTSSC) software package was developed. That control software package allows the user to implement multiple control methods and allows for varied input/output commands. The development of the control algorithm is presented. The desired functionality of the software is discussed, including the ability to inject noise on sensor inputs and/or actuator outputs. Various limitations, common issues, and trade-offs are discussed including data format precision; the drawbacks of using either Direct Memory Access (DMA), interrupts, or program control techniques for data acquisition; and platform dependent concerns related to the portability of the software, such as memory addressing formats. Efforts to minimize overall controller loop-rate and a comparison of achievable controller sample rates are discussed. The implementation of a modular code structure is presented. The format for the controller input data file and the noise information file is presented. Controller input vector information is available for post-processing by mathematical analysis software such as MATLAB1.
An Active Learning Algorithm for Control of Epidural Electrostimulation.
Desautels, Thomas A; Choe, Jaehoon; Gad, Parag; Nandra, Mandheerej S; Roy, Roland R; Zhong, Hui; Tai, Yu-Chong; Edgerton, V Reggie; Burdick, Joel W
2015-10-01
Epidural electrostimulation has shown promise for spinal cord injury therapy. However, finding effective stimuli on the multi-electrode stimulating arrays employed requires a laborious manual search of a vast space for each patient. Widespread clinical application of these techniques would be greatly facilitated by an autonomous, algorithmic system which choses stimuli to simultaneously deliver effective therapy and explore this space. We propose a method based on GP-BUCB, a Gaussian process bandit algorithm. In n = 4 spinally transected rats, we implant epidural electrode arrays and examine the algorithm's performance in selecting bipolar stimuli to elicit specified muscle responses. These responses are compared with temporally interleaved intra-animal stimulus selections by a human expert. GP-BUCB successfully controlled the spinal electrostimulation preparation in 37 testing sessions, selecting 670 stimuli. These sessions included sustained autonomous operations (ten-session duration). Delivered performance with respect to the specified metric was as good as or better than that of the human expert. Despite receiving no information as to anatomically likely locations of effective stimuli, GP-BUCB also consistently discovered such a pattern. Further, GP-BUCB was able to extrapolate from previous sessions' results to make predictions about performance in new testing sessions, while remaining sufficiently flexible to capture temporal variability. These results provide validation for applying automated stimulus selection methods to the problem of spinal cord injury therapy. PMID:25974925
Efficient computer algebra algorithms for polynomial matrices in control design
NASA Technical Reports Server (NTRS)
Baras, J. S.; Macenany, D. C.; Munach, R.
1989-01-01
The theory of polynomial matrices plays a key role in the design and analysis of multi-input multi-output control and communications systems using frequency domain methods. Examples include coprime factorizations of transfer functions, cannonical realizations from matrix fraction descriptions, and the transfer function design of feedback compensators. Typically, such problems abstract in a natural way to the need to solve systems of Diophantine equations or systems of linear equations over polynomials. These and other problems involving polynomial matrices can in turn be reduced to polynomial matrix triangularization procedures, a result which is not surprising given the importance of matrix triangularization techniques in numerical linear algebra. Matrices with entries from a field and Gaussian elimination play a fundamental role in understanding the triangularization process. In the case of polynomial matrices, matrices with entries from a ring for which Gaussian elimination is not defined and triangularization is accomplished by what is quite properly called Euclidean elimination. Unfortunately, the numerical stability and sensitivity issues which accompany floating point approaches to Euclidean elimination are not very well understood. New algorithms are presented which circumvent entirely such numerical issues through the use of exact, symbolic methods in computer algebra. The use of such error-free algorithms guarantees that the results are accurate to within the precision of the model data--the best that can be hoped for. Care must be taken in the design of such algorithms due to the phenomenon of intermediate expressions swell.
NASA Technical Reports Server (NTRS)
Mark, H; Mark, Herman; Zettle, Eugene V
1952-01-01
An investigation of a single-annulus turbojet combustor with slot-type air admission was conducted to demonstrate the application of certain design principles to the control of outlet-gas temperature distributions. Comparisons of performance of a one-quarter-annulus combustor (duct-type installation) and a full-annulus combustor (obtained in a full-scale turbojet engine) are presented to indicate the applicability of results obtained from combustion studies conducted in duct-type installations. A reasonable correlation existed between the performance of the one-quarter-annulus and full-annulus combustors except for temperature distribution. Sufficient trends did exist which made it possible to predict temperature distributions for the engine, although absolute correlation did not exist. A radial temperature distribution similar to that required for a given engine was obtained using a one-quarter-annulus duct-type setup to predict results.
Algorithms and implementations of APT resonant control system
Wang, Yi-Ming; Regan, A.
1997-08-01
A digital signal processor is implemented to control resonant frequency of the RFQ prototype in APT/LEDA. Two schemes are implemented to calculate the resonant frequency of RFQ. One uses the measurement of the forward and reflected fields. The other uses the measurement of the forward and transmitted fields. The former is sensitive and accurate when the operation frequency is relatively far from the resonant frequency. The latter gives accurate results when the operation frequency is close to the resonant frequency. Linearized algorithms are derived to calculate the resonant frequency of the RFQ efficiently using a fixed-point DSP. The control frequency range is about 100kHz for 350MHz operation frequency. A frequency agile scheme is employed using a dual direct digital synthesizer to drive klystron at the cavity`s resonant frequency (not necessarily the required beam resonant frequency) in power-up mode to quickly the cavity to the desired resonant frequency. This paper will address the algorithm implementation, error analysis, as well as related hardware design issues.
Advanced illumination control algorithm for medical endoscopy applications
NASA Astrophysics Data System (ADS)
Sousa, Ricardo M.; Wäny, Martin; Santos, Pedro; Morgado-Dias, F.
2015-05-01
CMOS image sensor manufacturer, AWAIBA, is providing the world's smallest digital camera modules to the world market for minimally invasive surgery and one time use endoscopic equipment. Based on the world's smallest digital camera head and the evaluation board provided to it, the aim of this paper is to demonstrate an advanced fast response dynamic control algorithm of the illumination LED source coupled to the camera head, over the LED drivers embedded on the evaluation board. Cost efficient and small size endoscopic camera modules nowadays embed minimal size image sensors capable of not only adjusting gain and exposure time but also LED illumination with adjustable illumination power. The LED illumination power has to be dynamically adjusted while navigating the endoscope over changing illumination conditions of several orders of magnitude within fractions of the second to guarantee a smooth viewing experience. The algorithm is centered on the pixel analysis of selected ROIs enabling it to dynamically adjust the illumination intensity based on the measured pixel saturation level. The control core was developed in VHDL and tested in a laboratory environment over changing light conditions. The obtained results show that it is capable of achieving correction speeds under 1 s while maintaining a static error below 3% relative to the total number of pixels on the image. The result of this work will allow the integration of millimeter sized high brightness LED sources on minimal form factor cameras enabling its use in endoscopic surgical robotic or micro invasive surgery.
Control algorithms of SONET integrated self-healing networks
NASA Astrophysics Data System (ADS)
Hasegawa, Satoshi; Okaoue, Yasuyo; Egawa, Takashi; Sakauchi, Hideki
1994-01-01
As the deployment of high-speed fiber transmission systems has been accelerated, they are widely recognized as a firm infrastructure of information society. Under this circumstance, the importance of network survivability has been increasing rapidly in these days. In SONET, the self-healing networks have been highlighted as one of the most advanced mechanisms to realize SONET survivable networks. Several schemes have been proposed and studied actively due to a rapid progress on the development of highly intelligent NE's. Among them in this paper, a DCS based distributed self-healing network is discussed from a viewpoint of its control algorithms. Specifically, our self-healing algorithm called TRANS is explained in detail, which possesses such desirable features as providing fast and flexible restoration with line and path level restoration applied to an individual STS-1 channel, capability to handle multiple and even node failures, and so on. Both software simulation and hardware experiment verify that TRANS works properly in a real distributed environment, the result of which is shown in the paper. In addition, the combined use of TRANS and the ring restoration control is proposed taking into account the use in a practical SONET.
Combustion distribution control using the extremum seeking algorithm
NASA Astrophysics Data System (ADS)
Marjanovic, A.; Krstic, M.; Djurovic, Z.; Kvascev, G.; Papic, V.
2014-12-01
Quality regulation of the combustion process inside the furnace is the basis of high demands for increasing robustness, safety and efficiency of thermal power plants. The paper considers the possibility of spatial temperature distribution control inside the boiler, based on the correction of distribution of coal over the mills. Such control system ensures the maintenance of the flame focus away from the walls of the boiler, and thus preserves the equipment and reduces the possibility of ash slugging. At the same time, uniform heat dissipation over mills enhances the energy efficiency of the boiler, while reducing the pollution of the system. A constrained multivariable extremum seeking algorithm is proposed as a tool for combustion process optimization with the main objective of centralizing the flame in the furnace. Simulations are conducted on a model corresponding to the 350MW boiler of the Nikola Tesla Power Plant, in Obrenovac, Serbia.
Algorithm for Public Electric Transport Schedule Control for Intelligent Embedded Devices
NASA Astrophysics Data System (ADS)
Alps, Ivars; Potapov, Andrey; Gorobetz, Mikhail; Levchenkov, Anatoly
2010-01-01
In this paper authors present heuristics algorithm for precise schedule fulfilment in city traffic conditions taking in account traffic lights. The algorithm is proposed for programmable controller. PLC is proposed to be installed in electric vehicle to control its motion speed and signals of traffic lights. Algorithm is tested using real controller connected to virtual devices and real functional models of real tram devices. Results of experiments show high precision of public transport schedule fulfilment using proposed algorithm.
Jan, Carmen; Lee, Marcos; Roa, Reina; Herrera, Víctor; Politis, Michael; Motta, Jorge
2014-01-01
Objective To evaluate the association of a nationwide comprehensive smoking ban (CSB) and tobacco tax increase (TTI) on the risk of acute myocardial infarctions (AMI) in Panama for the period of 2006 – 2010 using hospital admissions data. Methods Data of AMI cases was gathered from public and private hospitals in the country for the period of January 1, 2006 to December 31, 2010. The number of AMI cases was calculated on a monthly basis. The risk of AMI was estimated for the pre-CSB period (January 2006 to April 2008) and was used as a reference point. Three post-intervention periods were examined: (1) post-CSB from May 2008 to April 2009 (12 months); (2) post-CSB from May 2009 to November 2009 (7 months); and (3) post-TTI from December 2009 to December 2010 (13 months). Relative risks (RR) of AMI were estimated for each post intervention periods by using a Poisson regression model. Mortality registries for the country attributed to myocardial infarction (MI) were obtained from January 2001 to December 2012. The annual percentage change (APC) of the number of deaths from MI was calculated using Joinpoint regression analysis. Results A total sample size of 2191 AMI cases was selected (monthly mean number of cases 36.52±8.24 SD). Using the pre-CSB as a reference point (RR = 1.00), the relative risk of AMI during the first CSB period, the second CSB period and post-TTI were 0.982, 1.049, and 0.985, respectively. The APC of deaths from MI from January 2001 to April 2008 was 0.5%. From January 2001 to June 2010 the APC trend was 0.47% and from July 2010 to December 2012 the APC was –0.3%. Conclusions The implementation of a CSB and TTI in Panama were associated with a decrease in tobacco consumption and a reduction of the RR of AMI. PMID:24520421
Grude, Nils; Lindbaek, Morten
2015-01-01
Objective. To compare the clinical outcome of patients presenting with symptoms of uncomplicated cystitis who were seen by a doctor, with patients who were given treatment following a diagnostic algorithm. Design. Randomized controlled trial. Setting. Out-of-hours service, Oslo, Norway. Intervention. Women with typical symptoms of uncomplicated cystitis were included in the trial in the time period September 2010–November 2011. They were randomized into two groups. One group received standard treatment according to the diagnostic algorithm, the other group received treatment after a regular consultation by a doctor. Subjects. Women (n = 441) aged 16–55 years. Mean age in both groups 27 years. Main outcome measures. Number of days until symptomatic resolution. Results. No significant differences were found between the groups in the basic patient demographics, severity of symptoms, or percentage of urine samples with single culture growth. A median of three days until symptomatic resolution was found in both groups. By day four 79% in the algorithm group and 72% in the regular consultation group were free of symptoms (p = 0.09). The number of patients who contacted a doctor again in the follow-up period and received alternative antibiotic treatment was insignificantly higher (p = 0.08) after regular consultation than after treatment according to the diagnostic algorithm. There were no cases of severe pyelonephritis or hospital admissions during the follow-up period. Conclusion. Using a diagnostic algorithm is a safe and efficient method for treating women with symptoms of uncomplicated cystitis at an out-of-hours service. This simplification of treatment strategy can lead to a more rational use of consultation time and a stricter adherence to National Antibiotic Guidelines for a common disorder. PMID:25961367
Myles, Puja R.; Nguyen-Van-Tam, Jonathan S.; Lim, Wei Shen; Nicholson, Karl G.; Brett, Stephen J.; Enstone, Joanne E.; McMenamin, James; Openshaw, Peter J. M.; Read, Robert C.; Taylor, Bruce L.; Bannister, Barbara; Semple, Malcolm G.
2012-01-01
Triage tools have an important role in pandemics to identify those most likely to benefit from higher levels of care. We compared Community Assessment Tools (CATs), the CURB-65 score, and the Pandemic Medical Early Warning Score (PMEWS); to predict higher levels of care (high dependency - Level 2 or intensive care - Level 3) and/or death in patients at or shortly after admission to hospital with A/H1N1 2009 pandemic influenza. This was a case-control analysis using retrospectively collected data from the FLU-CIN cohort (1040 adults, 480 children) with PCR-confirmed A/H1N1 2009 influenza. Area under receiver operator curves (AUROC), sensitivity, specificity, positive predictive values and negative predictive values were calculated. CATs best predicted Level 2/3 admissions in both adults [AUROC (95% CI): CATs 0.77 (0.73, 0.80); CURB-65 0.68 (0.64, 0.72); PMEWS 0.68 (0.64, 0.73), p<0.001] and children [AUROC: CATs 0.74 (0.68, 0.80); CURB-65 0.52 (0.46, 0.59); PMEWS 0.69 (0.62, 0.75), p<0.001]. CURB-65 and CATs were similar in predicting death in adults with both performing better than PMEWS; and CATs best predicted death in children. CATs were the best predictor of Level 2/3 care and/or death for both adults and children. CATs are potentially useful triage tools for predicting need for higher levels of care and/or mortality in patients of all ages. PMID:22509303
Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul
2014-03-01
Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. PMID:24139308
Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms
NASA Technical Reports Server (NTRS)
Colby, Mitchell; Knudson, Matthew D.; Tumer, Kagan
2014-01-01
Dynamic environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal paths through these environments. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially with the number of agents in the system. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance.
Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms
NASA Technical Reports Server (NTRS)
Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan
2014-01-01
Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance
An Adaptable Power System with Software Control Algorithm
NASA Technical Reports Server (NTRS)
Castell, Karen; Bay, Mike; Hernandez-Pellerano, Amri; Ha, Kong
1998-01-01
A low cost, flexible and modular spacecraft power system design was developed in response to a call for an architecture that could accommodate multiple missions in the small to medium load range. Three upcoming satellites will use this design, with one launch date in 1999 and two in the year 2000. The design consists of modular hardware that can be scaled up or down, without additional cost, to suit missions in the 200 to 600 Watt orbital average load range. The design will be applied to satellite orbits that are circular, polar elliptical and a libration point orbit. Mission unique adaptations are accomplished in software and firmware. In designing this advanced, adaptable power system, the major goals were reduction in weight volume and cost. This power system design represents reductions in weight of 78 percent, volume of 86 percent and cost of 65 percent from previous comparable systems. The efforts to miniaturize the electronics without sacrificing performance has created streamlined power electronics with control functions residing in the system microprocessor. The power system design can handle any battery size up to 50 Amp-hour and any battery technology. The three current implementations will use both nickel cadmium and nickel hydrogen batteries ranging in size from 21 to 50 Amp-hours. Multiple batteries can be used by adding another battery module. Any solar cell technology can be used and various array layouts can be incorporated with no change in Power System Electronics (PSE) hardware. Other features of the design are the standardized interfaces between cards and subsystems and immunity to radiation effects up to 30 krad Total Ionizing Dose (TID) and 35 Mev/cm(exp 2)-kg for Single Event Effects (SEE). The control algorithm for the power system resides in a radiation-hardened microprocessor. A table driven software design allows for flexibility in mission specific requirements. By storing critical power system constants in memory, modifying the system
Double Motor Coordinated Control Based on Hybrid Genetic Algorithm and CMAC
NASA Astrophysics Data System (ADS)
Cao, Shaozhong; Tu, Ji
A novel hybrid cerebellar model articulation controller (CMAC) and online adaptive genetic algorithm (GA) controller is introduced to control two Brushless DC motor (BLDCM) which applied in a biped robot. Genetic Algorithm simulates the random learning among the individuals of a group, and CMAC simulates the self-learning of an individual. To validate the ability and superiority of the novel algorithm, experiments have been done in MATLAB/SIMULINK. Analysis among GA, hybrid GA-CMAC and CMAC feed-forward control is also given. The results prove that the torque ripple of the coordinated control system is eliminated by using the hybrid GA-CMAC algorithm.
Study of a global search algorithm for optimal control.
NASA Technical Reports Server (NTRS)
Brocker, D. H.; Kavanaugh, W. P.; Stewart, E. C.
1967-01-01
Adaptive random search algorithm utilizing boundary cost-function hypersurfaces measurement to implement Pontryagin maximum principle, discussing hybrid computer use, iterative solution and convergence properties
Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed
NASA Technical Reports Server (NTRS)
Tian, Ye; Song, Qi; Cattafesta, Louis
2005-01-01
This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.
ERIC Educational Resources Information Center
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
NASA Astrophysics Data System (ADS)
Chen, Dong; Yuan, Ding; Li, Tan; Sidan, Du
2015-12-01
A novel nonlinear adaptive algorithm named as diagonal structure bilinear filtered-x least mean square (DBFXLMS) for multichannel nonlinear active noise control is proposed in this paper. The performances of the proposed algorithm are shown below and the computational complexity is compared with the second-order Volterra filtered-x LMS (VFXLMS) algorithm and the filtered-s least mean square (FSLMS) algorithm, in terms of normalized mean square error (NMSE), for multichannel active control of nonlinear noise processes. Both the simulations and the computational complexity analyses demonstrate that the proposed method has an improvement as compared to the proposed algorithms.
Sensor signals monitoring and control using wavelets transform representation algorithm
NASA Astrophysics Data System (ADS)
Paul, Okuwobi I.; Lu, Yonghua
2015-03-01
The usefulness of wavelet transforms has been compared and contrasted to Fourier transforms. Most importantly, wavelets transform provide a much needed alternative to Fourier transform for certain application such as pattern based monitoring and control. Effort has been made to provide a technique to extract essential trends from process signals and provide a compact representation. The effectiveness of a signal processing technique depends to a large extent on the nature of the signals involved. On technique that works for specific signal trends might not be effective in dealing with other signal trends. More so in pre-processing stage, signal extension has been identified as the critical factor influencing signal representation and retention of trends. This paper introduce a new algorithm in solving the present problems in sensor signal monitoring and control. The New Extension Technique (NET) was introduced, which provide an accurate wavelet decomposition irrespective of the nature of the signal. This method uses a statistical approach to provide a good approximation of the signal outside the boundaries of the signal depending on signal trends at the boundaries. Different statistical approaches were adopted for this purpose and four new extension methods were also introduced in order to ascertain which extension methods provide a reliable extension for all cases. The concept behind these methods is the same, since the signal samples close to the boundary are considered and a mean value is determined. The procedure for determining this mean value differs for each of these four methods; NET A, NET B, NET C, and NET D. The signal is then extended by making it symmetric with respect to that mean value and then inverting it.
Novel postural control algorithm for control of multifunctional myoelectric prosthetic hands
Segil, Jacob L.; Weir, Richard F. ff.
2015-01-01
The myoelectric controller (MEC) remains a technological bottleneck in the development of multifunctional prosthetic hands. Current MECs require physiologically inappropriate commands to indicate intent and lack effectiveness in a clinical setting. Postural control schemes use surface electromyography signals to drive a cursor in a continuous two-dimensional domain that is then transformed into a hand posture. Here, we present a novel algorithm for a postural controller and test the efficacy of the system during two experiments with 11 total subjects. In the first experiment, we found that performance increased when a velocity cursor-control technique versus a position cursor-control technique was used. Also, performance did not change when using 3, 4, or 12 surface electrodes. In the second experiment, subjects commanded a six degree-of-freedom virtual hand into seven functional postures without training, with completion rates of 82 +/− 4%, movement times of 3.5 +/− 0.2 s, and path efficiencies of 45 +/− 3%. Subjects retained the ability to use the postural controller at a high level across days after a single 1 h training session. Our results substantiate the novel algorithm for a postural controller as a robust and advantageous design for a MEC of multifunction prosthetic hands. PMID:26348320
An efficient artificial bee colony algorithm with application to nonlinear predictive control
NASA Astrophysics Data System (ADS)
Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed
2016-05-01
In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.
The Admissions Equity Struggle
ERIC Educational Resources Information Center
Freedman, Eric
2012-01-01
It has been a long, litigious road from Heman Sweatt, an African-American mail carrier who wanted to attend the prestigious, all-White law school at the University of Texas at Austin in 1946, to Abigail Fisher, a White high school student who failed to win undergraduate admission to the same university a half-century later. Depending on what the…
Gayeski, N.; Armstrong, Peter; Alvira, M.; Gagne, J.; Katipamula, Srinivas
2011-11-30
KGS Buildings LLC (KGS) and Pacific Northwest National Laboratory (PNNL) have developed a simplified control algorithm and prototype low-lift chiller controller suitable for model-predictive control in a demonstration project of low-lift cooling. Low-lift cooling is a highly efficient cooling strategy conceived to enable low or net-zero energy buildings. A low-lift cooling system consists of a high efficiency low-lift chiller, radiant cooling, thermal storage, and model-predictive control to pre-cool thermal storage overnight on an optimal cooling rate trajectory. We call the properly integrated and controlled combination of these elements a low-lift cooling system (LLCS). This document is the final report for that project.
NASA Astrophysics Data System (ADS)
Joung, JinWook; Smyth, Andrew W.; Chung, Lan
2010-06-01
The active interaction control (AIC) system consisting of a primary structure, an auxiliary structure and an interaction element was proposed to protect the primary structure against earthquakes and winds. The objective of the AIC system in reducing the responses of the primary structure is fulfilled by activating or deactivating the switching between the engagement and the disengagement of the primary and auxiliary structures through the interaction element. The status of the interaction element is controlled by switching control algorithms. The previously developed switching control algorithms require an excessive amount of switching, which is inefficient. In this paper, the excessive amount of switching is restricted by imposing an appropriately designed switching boundary region, where switching is prohibited, on pre-designed engagement-disengagement conditions. Two different approaches are used in designing the newly proposed AID-off and AID-off2 algorithms. The AID-off2 algorithm is designed to affect deactivated switching regions explicitly, unlike the AID-off algorithm, which follows the same procedure of designing the engagement-disengagement conditions of the previously developed algorithms, by using the current status of the AIC system. Both algorithms are shown to be effective in reducing the amount of switching times triggered from the previously developed AID algorithm under an appropriately selected control sampling period for different earthquakes, but the AID-off2 algorithm outperforms the AID-off algorithm in reducing the number of switching times.
Zhang, Ying; Nitschke, Monika; Krackowizer, Antoinette; Dear, Keith; Pisaniello, Dino; Weinstein, Philip; Tucker, Graeme; Shakib, Sepehr; Bi, Peng
2016-01-01
Objective The extreme heatwave of 2009 in South Australia dramatically increased morbidity, with a 14-fold increase in direct heat-related hospitalisation in metropolitan Adelaide. Our study aimed to identify risk factors for the excess morbidity. Design A matched case–control study of risk factors was conducted. Setting Patients and matched community controls were interviewed to gather data on demographics, living environment, social support, health status and behaviour changes during the heatwave. Participants Cases were all hospital admissions with heat-related diagnoses during the 5-day heatwave in 2009. Controls were randomly selected from communities. Outcome measures Descriptive analyses, simple and multiple conditional logistic regressions were performed. Adjusted ORs (AORs) were estimated. Results In total, 143 hospital patients and 143 matched community controls were interviewed, with a mean age of 73 years (SD 21), 96% European ethnicity, 63% retired, 36% with high school or higher education, and 8% institutional living. The regression model indicated that compared with the controls, cases were more likely to have heart disease (AOR=13.56, 95% CI 1.27 to 144.86) and dementia (AOR=26.43, 95% CI 1.99 to 350.73). The protective factors included higher education level (AOR=0.48, 95% CI 0.23 to 0.99), having air-conditioner in the bedroom (AOR=0.12, 95% CI 0.02 to 0.74), having an emergency button (AOR=0.09, 95% CI 0.01 to 0.96), using refreshment (AOR=0.10, 95% CI 0.01 to 0.84), and having more social activities (AOR=0.11, 95% CI 0.02 to 0.57). Conclusions Pre-existing heart disease and dementia significantly increase the risk of direct heat-related hospitalisations during heatwaves. The presence of an air-conditioner in the bedroom, more social activities, a higher education level, use of emergency buttons and refreshments reduce the risk during heatwaves. PMID:27256088
Genetic algorithms for adaptive real-time control in space systems
NASA Technical Reports Server (NTRS)
Vanderzijp, J.; Choudry, A.
1988-01-01
Genetic Algorithms that are used for learning as one way to control the combinational explosion associated with the generation of new rules are discussed. The Genetic Algorithm approach tends to work best when it can be applied to a domain independent knowledge representation. Applications to real time control in space systems are discussed.
NASA Astrophysics Data System (ADS)
Hasbullah Mohd Isa, Wan; Taha, Zahari; Mohd Khairuddin, Ismail; Majeed, Anwar P. P. Abdul; Fikri Muhammad, Khairul; Abdo Hashem, Mohammed; Mahmud, Jamaluddin; Mohamed, Zulkifli
2016-02-01
This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. The Newton-Euler formulation was used in deriving the dynamic modelling of both the anthropometry based human upper extremity as well as the exoskeleton that consists of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. The Mamdani Fuzzy based rule is employed to approximate the estimated inertial properties of the system to ensure the AFC loop responds efficiently. It is found that the IAFC-PD performed well against the disturbances introduced into the system as compared to the conventional PD control architecture in performing the desired trajectory tracking.
NASA Astrophysics Data System (ADS)
Yamamoto, Kensei; Aoki, Hidenori; Naoi, Kenji; Mizutani, Yoshibumi
This paper presents the result of executing the conventional genetic algorithm (GA) and a new method to the voltage and reactive power control (VQC). The conventional GA can give the control process and improve the fitness with the practical control times. And, the method to cancel the limited deviation as early as possible is implemented. Moreover, the method to reduce the control times to the fitness as much as possible is proposed. The proposed method is integrated the tabu search (TS) into the conventional GA. The proposed method generates next generation’s individual with the crossover of the conventional GA and the neighborhood search of the TS. Therefore, the proposed method executes an effective search. As a result, the proposed method can obtain better fitness than the conventional GA in the same calculation times. The effectiveness of the proposed method is demonstrated by practical 15-bus and 118-bus systems.
Physiologic control algorithms for rotary blood pumps using pressure sensor input.
Bullister, Edward; Reich, Sanford; Sluetz, James
2002-11-01
Hierarchical algorithms have been developed for enhanced physiologic control and monitoring of blood pumps using pressure inputs. Pressures were measured at pump inlet and outlet using APEX pressure sensors (APSs). The APS is a patented, long-term implantable, flow-through blood pressure sensor and designed to control implantable heart pumps. The algorithms have been tested using a Donavan circulatory mock-loop setup, a generic rotary pump, and LabVIEW software. The hierarchical algorithms control pump speed using pump inlet pressure as a primary independent variable and pump outlet pressure as a secondary dependent variable. Hierarchical control algorithms based on feedback from pressure sensors can control the speed of the pump to stably maintain ventricular filling pressures and arterial pressures. Monitoring algorithms based on pressure inputs are able to approximate flow rate and hydraulic power for the pump and the left ventricle. PMID:12406146
A guidance and control algorithm for scent tracking micro-robotic vehicle swarms
Dohner, J.L.
1998-03-01
Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.
An improved filter-u least mean square vibration control algorithm for aircraft framework.
Huang, Quanzhen; Luo, Jun; Gao, Zhiyuan; Zhu, Xiaojin; Li, Hengyu
2014-09-01
Active vibration control of aerospace vehicle structures is very a hot spot and in which filter-u least mean square (FULMS) algorithm is one of the key methods. But for practical reasons and technical limitations, vibration reference signal extraction is always a difficult problem for FULMS algorithm. To solve the vibration reference signal extraction problem, an improved FULMS vibration control algorithm is proposed in this paper. Reference signal is constructed based on the controller structure and the data in the algorithm process, using a vibration response residual signal extracted directly from the vibration structure. To test the proposed algorithm, an aircraft frame model is built and an experimental platform is constructed. The simulation and experimental results show that the proposed algorithm is more practical with a good vibration suppression performance. PMID:25273765
Semi-flocking algorithm for motion control of mobile sensors in large-scale surveillance systems.
Semnani, Samaneh Hosseini; Basir, Otman A
2015-01-01
The ability of sensors to self-organize is an important asset in surveillance sensor networks. Self-organize implies self-control at the sensor level and coordination at the network level. Biologically inspired approaches have recently gained significant attention as a tool to address the issue of sensor control and coordination in sensor networks. These approaches are exemplified by the two well-known algorithms, namely, the Flocking algorithm and the Anti-Flocking algorithm. Generally speaking, although these two biologically inspired algorithms have demonstrated promising performance, they expose deficiencies when it comes to their ability to maintain simultaneous robust dynamic area coverage and target coverage. These two coverage performance objectives are inherently conflicting. This paper presents Semi-Flocking, a biologically inspired algorithm that benefits from key characteristics of both the Flocking and Anti-Flocking algorithms. The Semi-Flocking algorithm approaches the problem by assigning a small flock of sensors to each target, while at the same time leaving some sensors free to explore the environment. This allows the algorithm to strike balance between robust area coverage and target coverage. Such balance is facilitated via flock-sensor coordination. The performance of the proposed Semi-Flocking algorithm is examined and compared with other two flocking-based algorithms once using randomly moving targets and once using a standard walking pedestrian dataset. The results of both experiments show that the Semi-Flocking algorithm outperforms both the Flocking algorithm and the Anti-Flocking algorithm with respect to the area of coverage and the target coverage objectives. Furthermore, the results show that the proposed algorithm demonstrates shorter target detection time and fewer undetected targets than the other two flocking-based algorithms. PMID:25014985
NASA Technical Reports Server (NTRS)
Stoughton, John W.; Mielke, Roland R.
1988-01-01
An overview is presented of a model for describing data and control flow associated with the execution of large-grained, decision-free algorithms in a special distributed computer environment. The ATAMM (Algorithm-To-Architecture Mapping Model) model provides a basis for relating an algorithm to its execution in a dataflow multicomputer environment. The ATAMM model features a marked graph Petri net description of the algorithm behavior with regard to both data and control flow. The model provides an analytical basis for calculating performance bounds on throughput characteristics which are demonstrated here.
NASA Astrophysics Data System (ADS)
Ha, S. H.; Choi, S. B.; Lee, G. S.; Yoo, W. H.
2013-02-01
This paper presents control performance evaluation of railway vehicle featured by semi-active suspension system using magnetorheological (MR) fluid damper. In order to achieve this goal, a nine degree of freedom of railway vehicle model, which includes car body and bogie, is established. The wheel-set data is loaded from measured value of railway vehicle. The MR damper system is incorporated with the governing equation of motion of the railway vehicle model which includes secondary suspension. To illustrate the effectiveness of the controlled MR dampers on suspension system of railway vehicle, the control law using the sky-ground hook controller is adopted. This controller takes into account for both vibration control of car body and increasing stability of bogie by adopting a weighting parameter between two performance requirements. The parameters appropriately determined by employing a fuzzy algorithm associated with two fuzzy variables: the lateral speed of the car body and the lateral performance of the bogie. Computer simulation results of control performances such as vibration control and stability analysis are presented in time and frequency domains.
Algorithm research and realization of the turning control system for heavy transportation vehicle
NASA Astrophysics Data System (ADS)
Mi, Hanguang; Yuan, Haiwen; Wang, Qiusheng; Zhao, Jingpo
2012-05-01
The dynamics of turning system which is a nonlinear system normally has great impact on the transportation speed of the vehicle having heavy load and large size. The dynamics of turning system depends on control algorithm and its implementation, but the existing control algorithms which having high dynamics in the application of heavy transportation vehicle are complex for realization and high hardware requirement. So, the nonlinear turning system is analyzed for improving its dynamics by researching new efficient control algorithm. The models of electromagnetic valve, hydraulic cylinder and turning mechanical part are built individually to get the open-loop model of the turning system following characteristics analyzed. According to the model, a new control algorithm for heavy transportation vehicle which combined PID with Bang-Bang control is presented. Then the close-loop model of turning system is obtained under Matlab/Simulink environment. By comparing the step response of different control algorithms in the same conditions, the new algorithm's validity is verified. On the basis of the analysis results, the algorithm is adopted to implement the turning control system by using CAN field bus and PLC controllers. Furthermore, the turning control system has been applied in one type of heavy transportation vehicle. It reduces the response time of turning system from seconds level to 250 ms, and the speed of heavy transportation vehicle increases from 5 km/h to 30 km/h. The application result shows that the algorithm and turning control system have met all the turning requirements. This new type of turning control algorithm proposed is simple in implementation for fast response of nonlinear and large-scale turning system of heavy transportation vehicle.
NASA Astrophysics Data System (ADS)
Jang, Dong-Doo; Park, Jeongsu; Jung, Hyung-Jo
2013-04-01
The feasibility of an active mass damper (AMD) system employing the time delay control (TDC) algorithm, which is one of the robust and adaptive control algorithms, for effectively suppressing the wind-induced vibration of a building structure is investigated. The TDC algorithm has several attractive features such as the simplicity and the excellent robustness to unknown system dynamics and disturbance. Based on the characteristics of the algorithm, it has the potential to be an effective control system for mitigating excessive vibration of civil engineering structures such as buildings, bridges and towers. However, it has not been used for structural response reduction yet. In order to verify the effectiveness of the proposed active control method combining an AMD system with the TDC algorithm, a series of labscale tests are carried out.
A comparison of force control algorithms for robots in contact with flexible environments
NASA Technical Reports Server (NTRS)
Wilfinger, Lee S.
1992-01-01
In order to perform useful tasks, the robot end-effector must come into contact with its environment. For such tasks, force feedback is frequently used to control the interaction forces. Control of these forces is complicated by the fact that the flexibility of the environment affects the stability of the force control algorithm. Because of the wide variety of different materials present in everyday environments, it is necessary to gain an understanding of how environmental flexibility affects the stability of force control algorithms. This report presents the theory and experimental results of two force control algorithms: Position Accommodation Control and Direct Force Servoing. The implementation of each of these algorithms on a two-arm robotic test bed located in the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE) is discussed in detail. The behavior of each algorithm when contacting materials of different flexibility is experimentally determined. In addition, several robustness improvements to the Direct Force Servoing algorithm are suggested and experimentally verified. Finally, a qualitative comparison of the force control algorithms is provided, along with a description of a general tuning process for each control method.
NASA Astrophysics Data System (ADS)
Saini, J. S.; Jain, V.
2015-03-01
This paper presents a genetic algorithm (GA)-based design and optimization of fuzzy logic controller (FLC) for automatic generation control (AGC) for a single area. FLCs are characterized by a set of parameters, which are optimized using GA to improve their performance. The design of input and output membership functions (mfs) of an FLC is carried out by automatically tuning (off-line) the parameters of the membership functions. Tuning is based on maximization of a comprehensive fitness function constructed as inverse of a weighted average of three performance indices, i.e., integral square deviation (ISD), the integral of square of the frequency deviation and peak overshoot (Mp), and settling time (ts). The GA-optimized FLC (GAFLC) shows better performance as compared to a conventional proportional integral (PI) and a hand-designed fuzzy logic controller not only for a standard system (displaying frequency deviations) but also under parametric and load disturbances.
The DWPF product composition control system at Savannah River: Statistical process control algorithm
Postles, R.L.; Brown, K.G.
1991-01-01
The DWPF Process batch-blends aqueous radwaste (PHA) with solid radwaste (Sludge) in a waste receipt vessel (the SRAT). The resulting SRAT-Batch is transferred to the next process vessel (the SME) and there blended with ground glass (Frit) to produce a batch of feed slurry. The SME-Batch is passed to a subsequent hold tank (the MFT) which feeds a Melter continuously. The Melter produces a molten glass wasteform which is poured into stainless steel canisters for cooling and, ultimately, shipment to and storage in a geologic Repository. The Repository will require that the glass wasteform be resistant to leaching by any underground water that might contact it. In addition, there are processing constraints on Viscosity and Liquidus Temperature of the melt. The Product Composition Control System (PCCS) is the system intended to ensure that the melt will be Processible and that the glass wasteform will be Acceptable. Within the PCCS, the SPC Algorithm is the device which guides control of the DWPF process. The SPC Algorithm is needed to control the multivariate DWPF process in the face of uncertainties (variances and covariances) which arise from this process and its supply, sampling, modeling, and measurement systems.
The DWPF product composition control system at Savannah River: Statistical process control algorithm
Postles, R.L.; Brown, K.G.
1991-12-31
The DWPF Process batch-blends aqueous radwaste (PHA) with solid radwaste (Sludge) in a waste receipt vessel (the SRAT). The resulting SRAT-Batch is transferred to the next process vessel (the SME) and there blended with ground glass (Frit) to produce a batch of feed slurry. The SME-Batch is passed to a subsequent hold tank (the MFT) which feeds a Melter continuously. The Melter produces a molten glass wasteform which is poured into stainless steel canisters for cooling and, ultimately, shipment to and storage in a geologic Repository. The Repository will require that the glass wasteform be resistant to leaching by any underground water that might contact it. In addition, there are processing constraints on Viscosity and Liquidus Temperature of the melt. The Product Composition Control System (PCCS) is the system intended to ensure that the melt will be Processible and that the glass wasteform will be Acceptable. Within the PCCS, the SPC Algorithm is the device which guides control of the DWPF process. The SPC Algorithm is needed to control the multivariate DWPF process in the face of uncertainties (variances and covariances) which arise from this process and its supply, sampling, modeling, and measurement systems.
NASA Technical Reports Server (NTRS)
Battiste, Vernol; Lawton, George; Lachter, Joel; Brandt, Summer; Koteskey, Robert; Dao, Arik-Quang; Kraut, Josh; Ligda, Sarah; Johnson, Walter W.
2012-01-01
Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.
Multiple shooting algorithms for jump-discontinuous problems in optimal control and estimation
NASA Technical Reports Server (NTRS)
Mook, D. J.; Lew, Jiann-Shiun
1991-01-01
Multiple shooting algorithms are developed for jump-discontinuous two-point boundary value problems arising in optimal control and optimal estimation. Examples illustrating the origin of such problems are given to motivate the development of the solution algorithms. The algorithms convert the necessary conditions, consisting of differential equations and transversality conditions, into algebraic equations. The solution of the algebraic equations provides exact solutions for linear problems. The existence and uniqueness of the solution are proved.
Computationally efficient algorithm for high sampling-frequency operation of active noise control
NASA Astrophysics Data System (ADS)
Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati
2015-05-01
In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.
Noise filtering algorithm for the MFTF-B computer based control system
Minor, E.G.
1983-11-30
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions.
40 CFR 85.1504 - Conditional admission.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Conditional admission. 85.1504 Section 85.1504 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM MOBILE SOURCES Importation of Motor Vehicles and Motor Vehicle Engines §...
40 CFR 85.1504 - Conditional admission.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 19 2014-07-01 2014-07-01 false Conditional admission. 85.1504 Section 85.1504 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM MOBILE SOURCES Importation of Motor Vehicles and Motor Vehicle Engines §...
Dynamic Congestion Control using MDB-Routing Algorithm
NASA Astrophysics Data System (ADS)
Anuradha, S.; Raghu Ram, G.
2014-01-01
This paper presents high through put routing algorithm. Modified depth Breadth routing algorithm takes a decision in moving forward packet in the next node which will visit to reach its final destination. Load balancing to improve the performance of distributed by processing power of the entire system to smooth out process of very high congestion at individual nodes, by transferring some of the load of heavily loaded nodes to the other nodes for processing. This achieves a 306.53 average time for packet, compared with the DB routing which achieves 316.13 average time for packet. Results shows that the proposed Modified depth Breadth achieves 348 average time when compared to DB routing which gives 548 for 3500 packets on 5 × 5 grid. Further results show that no of dead packets significantly reduced in the case of MDB. This focuses on Routing Network and Tables. These Network tables includes the information used by a routing algorithm to take a decision in moving forward the packet in the next node which will visit to reach its final destination. Load balancing try to improve the performance of a distributed system by processing power of the entire system to smooth out periods of very high congestion at individual nodes, which is done by transferring some of the load of heavily loaded nodes to other nodes for processing.
NASA Technical Reports Server (NTRS)
Cull, R. C.; Eltimsahy, A. H.
1983-01-01
The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.
Tilt Servo Control by Intelligent Algorithm in Holographic Data Storage System
NASA Astrophysics Data System (ADS)
Kim, Jang Hyun; Jeong, Wooyoung; Yang, Hyunseok
2013-09-01
Tracking servo and tilt servo control are very important research in holographic data storage system. In this paper, we propose intelligent servo control by fuzzy rules in holographic data storage system. Hence, we have found pattern of tilt servo control in holographic data storage system through fuzzy system. Fuzzy rules were generated by subtractive clustering algorithm for controlling tilt servo. Therefore, we control tilt servo using fuzzy rules in holographic data storage system. Consequently, practical pattern of tilt servo control was found by intelligence algorithm in holographic data storage system.
A novel combined cryptographic and hash algorithm based on chaotic control character
NASA Astrophysics Data System (ADS)
Deng, Shaojiang; Xiao, Di; Li, Yantao; Peng, Wenbin
2009-11-01
A novel combined cryptographic and hash algorithm based on chaotic control character is proposed in this paper. The control character is generated by chaotic iteration. The plaintext is pre-processed in terms of control character, and then encrypted by the look-up index table. At the same time, the chaotic trajectory is changed continuously according to the control character, which can avoid the dynamical degradation of chaos. Besides, the look-up index table is updated by utilizing the control character continuously, and the index item of the final look-up index table can be considered as the hash value of the whole paragraph of plaintext. Therefore, the proposed algorithm can perform both encryption/decryption and hash in a combined manner. Compared with Wong's and our former algorithms, the proposed one has decreased the ratio of ciphertext/plaintext to 1, and improved the efficiency greatly. Theoretical analysis and computer simulation verify the validity of the proposed algorithm.
The Probabilistic Admissible Region with Additional Constraints
NASA Astrophysics Data System (ADS)
Roscoe, C.; Hussein, I.; Wilkins, M.; Schumacher, P.
The admissible region, in the space surveillance field, is defined as the set of physically acceptable orbits (e.g., orbits with negative energies) consistent with one or more observations of a space object. Given additional constraints on orbital semimajor axis, eccentricity, etc., the admissible region can be constrained, resulting in the constrained admissible region (CAR). Based on known statistics of the measurement process, one can replace hard constraints with a probabilistic representation of the admissible region. This results in the probabilistic admissible region (PAR), which can be used for orbit initiation in Bayesian tracking and prioritization of tracks in a multiple hypothesis tracking framework. The PAR concept was introduced by the authors at the 2014 AMOS conference. In that paper, a Monte Carlo approach was used to show how to construct the PAR in the range/range-rate space based on known statistics of the measurement, semimajor axis, and eccentricity. An expectation-maximization algorithm was proposed to convert the particle cloud into a Gaussian Mixture Model (GMM) representation of the PAR. This GMM can be used to initialize a Bayesian filter. The PAR was found to be significantly non-uniform, invalidating an assumption frequently made in CAR-based filtering approaches. Using the GMM or particle cloud representations of the PAR, orbits can be prioritized for propagation in a multiple hypothesis tracking (MHT) framework. In this paper, the authors focus on expanding the PAR methodology to allow additional constraints, such as a constraint on perigee altitude, to be modeled in the PAR. This requires re-expressing the joint probability density function for the attributable vector as well as the (constrained) orbital parameters and range and range-rate. The final PAR is derived by accounting for any interdependencies between the parameters. Noting that the concepts presented are general and can be applied to any measurement scenario, the idea
NASA Astrophysics Data System (ADS)
Telban, Robert J.
While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input
Investigations into a new algorithm for calculating H infinity optimal controllers
NASA Technical Reports Server (NTRS)
Irwin, R. Dennis
1989-01-01
A new algorithm for calculating H (sup infinity) optimal controllers is investigated. The algorithm is significantly simpler than existing approaches and yields much simpler controllers. The design equations are first presented. Special system transformations required to apply the algorithm are then presented. The use of the algorithm with sampled-data systems is outlined in detail. Several constraints on the characteristics of the problem formulation are required for the application of the design equations. The consequences of these constraints are investigated by applying the algorithm to a simplified design for a subsystem of a large space structure ground test facility. The investigation of these constraints is continued by application of the design equations and constraints to an extremely simple tracking problem. The result of these investigations is the development of a frequency dependent weighting strategy that allows realistic control problems to be cast in a form compatible with the new algorithm. Further work is indicated in the area of developing strategies for choosing frequency-dependent weights to achieve specific design goals. The use of the freedom in problem formulation to achieve robustness/performance tradeoffs should also be investigated. It is not clear that the algorithm always leads to simpler controllers. The more restrictive formulation may dictate that frequency-dependent weighting adds to the controller order disproportionately. This effect must also be investigated.
Hybrid evolutionary algorithms for network-centric command and control
NASA Astrophysics Data System (ADS)
Khosla, Deepak; Nichols, Tom
2006-05-01
Network-centric force optimization is the problem of threat engagement and dynamic Weapon-Target Allocation (WTA) across the force. The goal is to allocate and schedule defensive weapon resources over a given period of time so as to achieve certain battle management objectives subject to resource and temporal constraints. The problem addresses in this paper is one of dynamic WTA and involves optimization across both resources (weapons) and time. We henceforth refer to this problem as the Weapon Allocation and Scheduling problem (WAS). This paper addresses and solves the WAS problem for two separate battle management objectives: (1) Threat Kill Maximization (TKM), and (2) Asset Survival Maximization (ASM). Henceforth, the WAS problems for the above objectives are referred to as the WAS-TKM and WAS-ASM, respectively. Both WAS problems are NP-complete problem and belong to a class of multiple-resource-constrained optimal scheduling problems. While the above objectives appear to be intuitively similar from a battle management perspective, the two optimal scheduling problems are quite different in their complexity. We present a hybrid genetic algorithm (GA) that is a combination of a traditional genetic algorithm and a simulated annealing-type algorithm for solving these problems. The hybrid GA approach proposed here uses a simulated annealing-type heuristics to compute the fitness of a GA-selected population. This step also optimizes the temporal dimension (scheduling) under resource and temporal constraints and is significantly different for the WAS-TKM and WAS-ASM problems. The proposed method provides schedules that are near optimal in short cycle times and have minimal perturbation from one cycle to the next.
Developments in Human Centered Cueing Algorithms for Control of Flight Simulator Motion Systems
NASA Technical Reports Server (NTRS)
Houck, Jacob A.; Telban, Robert J.; Cardullo, Frank M.
1997-01-01
The authors conducted further research with cueing algorithms for control of flight simulator motion systems. A variation of the so-called optimal algorithm was formulated using simulated aircraft angular velocity input as a basis. Models of the human vestibular sensation system, i.e. the semicircular canals and otoliths, are incorporated within the algorithm. Comparisons of angular velocity cueing responses showed a significant improvement over a formulation using angular acceleration input. Results also compared favorably with the coordinated adaptive washout algorithm, yielding similar results for angular velocity cues while eliminating false cues and reducing the tilt rate for longitudinal cues. These results were confirmed in piloted tests on the current motion system at NASA-Langley, the Visual Motion Simulator (VMS). Proposed future developments by the authors in cueing algorithms are revealed. The new motion system, the Cockpit Motion Facility (CMF), where the final evaluation of the cueing algorithms will be conducted, is also described.
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. PMID:25751878
Unit Template Synchronous Reference Frame Theory Based Control Algorithm for DSTATCOM
NASA Astrophysics Data System (ADS)
Bangarraju, J.; Rajagopal, V.; Jayalaxmi, A.
2014-04-01
This article proposes new and simplified unit templates instead of standard phase locked loop (PLL) for Synchronous Reference Frame Theory Control Algorithm (SRFT). The extraction of synchronizing components (sinθ and cosθ) for parks and inverse parks transformation using standard PLL takes more execution time. This execution time in control algorithm delays the extraction of reference source current generation. The standard PLL not only takes more execution time but also increases the reactive power burden on the Distributed Static Compensator (DSTATCOM). This work proposes a unit template based SRFT control algorithm for four-leg insulated gate bipolar transistor based voltage source converter for DSTATCOM in distribution systems. This will reduce the execution time and reactive power burden on the DSTATCOM. The proposed DSTATCOM suppress harmonics, regulates the terminal voltage along with neutral current compensation. The DSTATCOM in distribution systems with proposed control algorithm is modeled and simulated using MATLAB using SIMULINK and Simpower systems toolboxes.
Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system
Fijany, A.; Milman, M.; Redding, D.
1994-12-31
In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.
A Novel Control algorithm based DSTATCOM for Load Compensation
NASA Astrophysics Data System (ADS)
R, Sreejith; Pindoriya, Naran M.; Srinivasan, Babji
2015-11-01
Distribution Static Compensator (DSTATCOM) has been used as a custom power device for voltage regulation and load compensation in the distribution system. Controlling the switching angle has been the biggest challenge in DSTATCOM. Till date, Proportional Integral (PI) controller is widely used in practice for load compensation due to its simplicity and ability. However, PI Controller fails to perform satisfactorily under parameters variations, nonlinearities, etc. making it very challenging to arrive at best/optimal tuning values for different operating conditions. Fuzzy logic and neural network based controllers require extensive training and perform better under limited perturbations. Model predictive control (MPC) is a powerful control strategy, used in the petrochemical industry and its application has been spread to different fields. MPC can handle various constraints, incorporate system nonlinearities and utilizes the multivariate/univariate model information to provide an optimal control strategy. Though it finds its application extensively in chemical engineering, its utility in power systems is limited due to the high computational effort which is incompatible with the high sampling frequency in these systems. In this paper, we propose a DSTATCOM based on Finite Control Set Model Predictive Control (FCS-MPC) with Instantaneous Symmetrical Component Theory (ISCT) based reference current extraction is proposed for load compensation and Unity Power Factor (UPF) action in current control mode. The proposed controller performance is evaluated for a 3 phase, 3 wire, 415 V, 50 Hz distribution system in MATLAB Simulink which demonstrates its applicability in real life situations.
Distributed concurrency control performance: A study of algorithms, distribution, and replication
Carey, M.J.; Livny, M.
1988-01-01
Many concurrency control algorithms have been proposed for use in distributed database systems. Despite the large number of available algorithms, and the fact that distributed database systems are becoming a commercial reality, distributed concurrency control performance tradeoffs are still not well understood. In this paper the authors attempt to shed light on some of the important issues by studying the performance of four representative algorithms - distributed 2PL, wound-wait, basic timestamp ordering, and a distributed optimistic algorithm - using a detailed simulation model of a distributed DBMS. The authors examine the performance of these algorithms for various levels of contention, ''distributedness'' of the workload, and data replication. The results should prove useful to designers of future distributed database systems.
Supervisory Power Management Control Algorithms for Hybrid Electric Vehicles. A Survey
Malikopoulos, Andreas
2014-03-31
The growing necessity for environmentally benign hybrid propulsion systems has led to the development of advanced power management control algorithms to maximize fuel economy and minimize pollutant emissions. This paper surveys the control algorithms for hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) that have been reported in the literature to date. The exposition ranges from parallel, series, and power split HEVs and PHEVs and includes a classification of the algorithms in terms of their implementation and the chronological order of their appearance. Remaining challenges and potential future research directions are also discussed.
Implementation Of Fuzzy Automated Brake Controller Using TSK Algorithm
NASA Astrophysics Data System (ADS)
Mittal, Ruchi; Kaur, Magandeep
2010-11-01
In this paper an application of Fuzzy Logic for Automatic Braking system is proposed. Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal Depending upon the speed and distance of train. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance depending upon the varying speed and distance of the train.
Evaluation of TCP Congestion Control Algorithms on the Windows Vista Platform
Li, Yee-Ting; /SLAC
2006-07-07
CTCP, an innovative TCP congestion control algorithm developed by Microsoft, is evaluated and compared to HSTCP and StandardTCP. Tests were performed on the production Internet from Stanford Linear Accelerator Center (SLAC) to various geographically located hosts to give a broad overview of the performances. We find that certain issues were apparent during testing (not directly related to the congestion control algorithms) which may skew results. With this in mind, we find that CTCP performed similarly to HSTCP across a multitude of different network environments. However, to improve the fairness and to reduce the impact of CTCP upon existing StandardTCP traffic, two areas of further research were investigated. Algorithmic additions to CTCP for burst control to reduce the aggressiveness of its cwnd increments demonstrated beneficial improvements in both fairness and throughput over the original CTCP algorithm. Similarly, {gamma} auto-tuning algorithms were investigated to dynamically adapt CTCP flows to their network conditions for optimal performance. While the effects of these auto-tuning algorithms when used in addition to burst control showed little to no benefit to fairness nor throughput for the limited number of network paths tested, one of the auto-tuning algorithms performed such that there was negligible impact upon StandardTCP. With these improvements, CTCP was found to perform better than HSTCP in terms of fairness and similarly in terms of throughput under the production environments tested.
Edwards, Becky; López-Lozano, José-Maria; Gould, Ian
2012-01-01
Objectives To describe secular trends in Staphylococcus aureus bacteraemia (SAB) and to assess the impacts of infection control practices, including universal methicillin-resistant Staphylococcus aureus (MRSA) admission screening on associated clinical burdens. Design Retrospective cohort study and multivariate time-series analysis linking microbiology, patient management and health intelligence databases. Setting Teaching hospital in North East Scotland. Participants All patients admitted to Aberdeen Royal Infirmary between 1 January 2006 and 31 December 2010: n=420 452 admissions and 1 430 052 acute occupied bed days (AOBDs). Intervention Universal admission screening programme for MRSA (August 2008) incorporating isolation and decolonisation. Primary and secondary measures Hospital-wide prevalence density, hospital-associated incidence density and death within 30 days of MRSA or methicillin-sensitive Staphylococcus aureus (MSSA) bacteraemia. Results Between 2006 and 2010, prevalence density of all SAB declined by 41%, from 0.73 to 0.50 cases/1000 AOBDs (p=0.002 for trend), and 30-day mortality from 26% to 14% (p=0.013). Significant reductions were observed in MRSA bacteraemia only. Overnight admissions screened for MRSA rose from 43% during selective screening to >90% within 4 months of universal screening. In multivariate time-series analysis (R2 0.45 to 0.68), universal screening was associated with a 19% reduction in prevalence density of MRSA bacteraemia (−0.035, 95% CI −0.049 to −0.021/1000 AOBDs; p<0.001), a 29% fall in hospital-associated incidence density (−0.029, 95% CI −0.035 to −0.023/1000 AOBDs; p<0.001) and a 46% reduction in 30-day mortality (−15.6, 95% CI −24.1% to −7.1%; p<0.001). Positive associations with fluoroquinolone and cephalosporin use suggested that antibiotic stewardship reduced prevalence density of MRSA bacteraemia by 0.027 (95% CI 0.015 to 0.039)/1000 AOBDs. Rates of MSSA bacteraemia were not
Efficient Nonlinear Programming Algorithms for Chemical Process Control and Operations
NASA Astrophysics Data System (ADS)
Biegler, Lorenz T.
Optimization is applied in numerous areas of chemical engineering including the development of process models from experimental data, design of process flowsheets and equipment, planning and scheduling of chemical process operations, and the analysis of chemical processes under uncertainty and adverse conditions. These off-line tasks require the solution of nonlinear programs (NLPs) with detailed, large-scale process models. Recently, these tasks have been complemented by time-critical, on-line optimization problems with differential-algebraic equation (DAE) process models that describe process behavior over a wide range of operating conditions, and must be solved sufficiently quickly. This paper describes recent advances in this area especially with dynamic models. We outline large-scale NLP formulations and algorithms as well as NLP sensitivity for on-line applications, and illustrate these advances on a commercial-scale low density polyethylene (LDPE) process.
An analysis of a candidate control algorithm for a ride quality augmentation system
NASA Technical Reports Server (NTRS)
Suikat, Reiner; Donaldson, Kent; Downing, David R.
1987-01-01
This paper presents a detailed analysis of a candidate algorithm for a ride quality augmentation system. The algorithm consists of a full-state feedback control law based on optimal control output weighting, estimators for angle of attack and sideslip, and a maneuvering algorithm. The control law is shown to perform well by both frequency and time domain analysis. The rms vertical acceleration is reduced by about 40 percent over the whole mission flight envelope. The estimators for the angle of attack and sideslip avoid the often inaccurate or costly direct measurement of those angles. The maneuvering algorithm will allow the augmented airplane to respond to pilot inputs. The design characteristics and performance are documented by the closed-loop eigenvalues; rms levels of vertical, lateral, and longitudinal acceleration; and representative time histories and frequency response.
Van Herpe, Tom; De Brabanter, Jos; Beullens, Martine; De Moor, Bart; Van den Berghe, Greet
2008-01-01
Introduction Blood glucose (BG) control performed by intensive care unit (ICU) nurses is becoming standard practice for critically ill patients. New (semi-automated) 'BG control' algorithms (or 'insulin titration' algorithms) are under development, but these require stringent validation before they can replace the currently used algorithms. Existing methods for objectively comparing different insulin titration algorithms show weaknesses. In the current study, a new approach for appropriately assessing the adequacy of different algorithms is proposed. Methods Two ICU patient populations (with different baseline characteristics) were studied, both treated with a similar 'nurse-driven' insulin titration algorithm targeting BG levels of 80 to 110 mg/dl. A new method for objectively evaluating BG deviations from normoglycemia was founded on a smooth penalty function. Next, the performance of this new evaluation tool was compared with the current standard assessment methods, on an individual as well as a population basis. Finally, the impact of four selected parameters (the average BG sampling frequency, the duration of algorithm application, the severity of disease, and the type of illness) on the performance of an insulin titration algorithm was determined by multiple regression analysis. Results The glycemic penalty index (GPI) was proposed as a tool for assessing the overall glycemic control behavior in ICU patients. The GPI of a patient is the average of all penalties that are individually assigned to each measured BG value based on the optimized smooth penalty function. The computation of this index returns a number between 0 (no penalty) and 100 (the highest penalty). For some patients, the assessment of the BG control behavior using the traditional standard evaluation methods was different from the evaluation with GPI. Two parameters were found to have a significant impact on GPI: the BG sampling frequency and the duration of algorithm application. A higher BG
NASA Technical Reports Server (NTRS)
Robinson, Michael; Steiner, Matthias; Wolff, David B.; Ferrier, Brad S.; Kessinger, Cathy; Einaudi, Franco (Technical Monitor)
2000-01-01
The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. A fundamental and extremely important step in creating high-quality GV products is radar data quality control. Quality control (QC) processing of TRMM GV radar data is based on some automated procedures, but the current QC algorithm is not fully operational and requires significant human interaction to assure satisfactory results. Moreover, the TRMM GV QC algorithm, even with continuous manual tuning, still can not completely remove all types of spurious echoes. In an attempt to improve the current operational radar data QC procedures of the TRMM GV effort, an intercomparison of several QC algorithms has been conducted. This presentation will demonstrate how various radar data QC algorithms affect accumulated radar rainfall products. In all, six different QC algorithms will be applied to two months of WSR-88D radar data from Melbourne, Florida. Daily, five-day, and monthly accumulated radar rainfall maps will be produced for each quality-controlled data set. The QC algorithms will be evaluated and compared based on their ability to remove spurious echoes without removing significant precipitation. Strengths and weaknesses of each algorithm will be assessed based on, their abilit to mitigate both erroneous additions and reductions in rainfall accumulation from spurious echo contamination and true precipitation removal, respectively. Contamination from individual spurious echo categories will be quantified to further diagnose the abilities of each radar QC algorithm. Finally, a cost-benefit analysis will be conducted to determine if a more automated QC algorithm is a viable alternative to the current, labor-intensive QC algorithm employed by TRMM GV.
NASA Technical Reports Server (NTRS)
Acikmese, Behcet A.; Carson, John M., III
2005-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.
NASA Technical Reports Server (NTRS)
Acikmese, Ahmet Behcet; Carson, John M., III
2006-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.
Ringbæk, Thomas; Green, Allan; Laursen, Lars Christian; Frausing, Ejvind; Brøndum, Eva; Ulrik, Charlotte Suppli
2015-01-01
Background and objective Tele monitoring (TM) of patients with chronic obstructive pulmonary disease (COPD) has gained much interest, but studies have produced conflicting results. Our aim was to investigate the effect of TM with the option of video consultations on exacerbations and hospital admissions in patients with severe COPD. Materials and methods Patients with severe COPD at high risk of exacerbations were eligible for the study. Of 560 eligible patients identified, 279 (50%) declined to participate. The remaining patients were equally randomized to either TM (n=141) or usual care (n=140) for the 6-month study period. TM comprised recording of symptoms, saturation, spirometry, and weekly video consultations. Algorithms generated alerts if readings breached thresholds. Both groups received standard care. The primary outcome was number of hospital admissions for exacerbation of COPD during the study period. Results Most of the enrolled patients had severe COPD (forced expiratory volume in 1 second <50%pred in 86% and ≥hospital admission for COPD in the year prior to enrollment in 45%, respectively, of the patients). No difference in drop-out rate and mortality was found between the groups. With regard to the primary outcome, no significant difference was found in hospital admissions for COPD between the groups (P=0.74), and likewise, no difference was found in time to first admission or all-cause hospital admissions. Compared with the control group, TM group patients had more moderate exacerbations (ie, treated with antibiotics/corticosteroid, but not requiring hospital admission; P<0.001), whereas the control group had more visits to outpatient clinics (P<0.001). Conclusion Our study of patients with severe COPD showed that TM including video consultations as add-on to standard care did not reduce hospital admissions for exacerbated COPD, but TM may be an alternative to visits at respiratory outpatient clinics. Further studies are needed to establish the
NASA Astrophysics Data System (ADS)
Dittmore, Andrew; Trail, Collin; Olsen, Thomas; Wiener, Richard J.
2003-11-01
We have previously demonstrated the experimental control of chaos in a Modified Taylor-Couette system with hourglass geometry( Richard J. Wiener et al), Phys. Rev. Lett. 83, 2340 (1999).. Identifying fixed points susceptible to algorithms for the control of chaos is key. We seek to learn about this process in the accessible numerical model of the damped, driven pendulum. Following Baker(Gregory L. Baker, Am. J. Phys. 63), 832 (1995)., we seek points susceptible to the OGY(E. Ott, C. Grebogi, and J. A. Yorke, Phys. Rev. Lett. 64), 1196 (1990). algorithm. We automate the search for fixed points that are candidates for control. We present comparisons of the space of candidate fixed points with the bifurcation diagrams and Poincare sections of the system. We demonstrate control at fixed points which do not appear on the attractor. We also show that the control algorithm may be employed to shift the system between non-communicating branches of the attractor.
LMI-Based Generation of Feedback Laws for a Robust Model Predictive Control Algorithm
NASA Technical Reports Server (NTRS)
Acikmese, Behcet; Carson, John M., III
2007-01-01
This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.
Learning tensegrity locomotion using open-loop control signals and coevolutionary algorithms.
Iscen, Atil; Caluwaerts, Ken; Bruce, Jonathan; Agogino, Adrian; SunSpiral, Vytas; Tumer, Kagan
2015-01-01
Soft robots offer many advantages over traditional rigid robots. However, soft robots can be difficult to control with standard control methods. Fortunately, evolutionary algorithms can offer an elegant solution to this problem. Instead of creating controls to handle the intricate dynamics of these robots, we can simply evolve the controls using a simulation to provide an evaluation function. In this article, we show how such a control paradigm can be applied to an emerging field within soft robotics: robots based on tensegrity structures. We take the model of the Spherical Underactuated Planetary Exploration Robot ball (SUPERball), an icosahedron tensegrity robot under production at NASA Ames Research Center, develop a rolling locomotion algorithm, and study the learned behavior using an accurate model of the SUPERball simulated in the NASA Tensegrity Robotics Toolkit. We first present the historical-average fitness-shaping algorithm for coevolutionary algorithms to speed up learning while favoring robustness over optimality. Second, we use a distributed control approach by coevolving open-loop control signals for each controller. Being simple and distributed, open-loop controllers can be readily implemented on SUPERball hardware without the need for sensor information or precise coordination. We analyze signals of different complexities and frequencies. Among the learned policies, we take one of the best and use it to analyze different aspects of the rolling gait, such as lengths, tensions, and energy consumption. We also discuss the correlation between the signals controlling different parts of the tensegrity robot. PMID:25951199
Development of Algorithms for Control of Humidity in Plant Growth Chambers
NASA Technical Reports Server (NTRS)
Costello, Thomas A.
2003-01-01
Algorithms were developed to control humidity in plant growth chambers used for research on bioregenerative life support at Kennedy Space Center. The algorithms used the computed water vapor pressure (based on measured air temperature and relative humidity) as the process variable, with time-proportioned outputs to operate the humidifier and de-humidifier. Algorithms were based upon proportional-integral-differential (PID) and Fuzzy Logic schemes and were implemented using I/O Control software (OPTO-22) to define and download the control logic to an autonomous programmable logic controller (PLC, ultimate ethernet brain and assorted input-output modules, OPTO-22), which performed the monitoring and control logic processing, as well the physical control of the devices that effected the targeted environment in the chamber. During limited testing, the PLC's successfully implemented the intended control schemes and attained a control resolution for humidity of less than 1%. The algorithms have potential to be used not only with autonomous PLC's but could also be implemented within network-based supervisory control programs. This report documents unique control features that were implemented within the OPTO-22 framework and makes recommendations regarding future uses of the hardware and software for biological research by NASA.
Issues in College Admissions Testing.
ERIC Educational Resources Information Center
Noble, Julie P.; Camara, Wayne J.
College admissions tests provide a standardized and objective measure of student achievement and generalized skills. Unlike high school grades or rank, admission tests are a common measure for comparing students who have attended different high schools, completed different courses, received different grades in courses taught by different teachers,…
The Changing College Admissions Scene.
ERIC Educational Resources Information Center
Sjogren, Cliff
1983-01-01
Discusses the status of college admissions and some of the forces that influenced college admissions policies during each of four three-year periods: the Sputnik Era (1957-60), the Postwar Baby Boom Era (1964-67), the "New Groups" Era (1971-74), and the Stable Enrollment Era (1978-81). (PGD)
Toward More Effective Admissions Interviews.
ERIC Educational Resources Information Center
Maly, Nancy J.
1983-01-01
Suggests ways to improve college admissions interviews. Discusses the purpose, format, technique, and content, of the interview as well as selling the college, concluding the interview, and writing the final interview report. Emphasizes the benefits of good interviewing skills to admissions officers. (WAS)
NASA Astrophysics Data System (ADS)
Tu, Jianwei; Lin, Xiaofeng; Tu, Bo; Xu, Jiayun; Tan, Dongmei
2014-09-01
In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm.
Robust PD Sway Control of a Lifted Load for a Crane Using a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Kawada, Kazuo; Sogo, Hiroyuki; Yamamoto, Toru; Mada, Yasuhiro
PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. For such a problem, the robust controller has been proposed.Although it is important to choose the suitable nominal model in designing the robust controller, it is not usually easy.In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.
Fuzzy Control Hardware for Segmented Mirror Phasing Algorithm
NASA Technical Reports Server (NTRS)
Roth, Elizabeth
1999-01-01
This paper presents a possible implementation of a control model developed to phase a system of segmented mirrors, with a PAMELA configuration, using analog fuzzy hardware. Presently, the model is designed for piston control only, but with the foresight that the parameters of tip and tilt will be integrated eventually. The proposed controller uses analog circuits to exhibit a voltage-mode singleton fuzzifier, a mixed-mode inference engine, and a current-mode defuzzifier. The inference engine exhibits multiplication circuits that perform the algebraic product composition through the use of operational transconductance amplifiers rather than the typical min-max circuits. Additionally, the knowledge base, containing exemplar data gained a priori through simulation, interacts via a digital interface.
A homotopy algorithm for digital optimal projection control GASD-HADOC
NASA Technical Reports Server (NTRS)
Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.
1993-01-01
The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.
A Modern Control Theory Based Algorithm for Control of the NASA/JPL 70-Meter Antenna Axis Servos
NASA Astrophysics Data System (ADS)
Hill, R. E.
1987-09-01
A digital computer-based state variable controller has been designed and applied to the 70-m antenna azis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accomodate intertarget slew, encoder references tracking, and precision tracking modes are described. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm has been successfully implemented and tested in the 70-m antenna at Deep Space Station (DSS) 63 in Spain.
A modern control theory based algorithm for control of the NASA/JPL 70-meter antenna axis servos
NASA Technical Reports Server (NTRS)
Hill, R. E.
1987-01-01
A digital computer-based state variable controller was designed and applied to the 70-m antenna axis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accommodate intertarget slew, encoder referenced tracking, and precision tracking modes are descibed. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm was successfully implemented and tested in the 70-m antenna at Deep Space Network station 63 in Spain.
Distributed topology control algorithm for multihop wireless netoworks
NASA Technical Reports Server (NTRS)
Borbash, S. A.; Jennings, E. H.
2002-01-01
We present a network initialization algorithmfor wireless networks with distributed intelligence. Each node (agent) has only local, incomplete knowledge and it must make local decisions to meet a predefined global objective. Our objective is to use power control to establish a topology based onthe relative neighborhood graph which has good overall performance in terms of power usage, low interference, and reliability.
Optimal Regulator Algorithms For The Control Of Linear Systems (ORACLS)
NASA Technical Reports Server (NTRS)
Frisch, Harold P.
1990-01-01
Control theory design package offers engineer full range of subroutines to manipulate and solve Linear-Quadratic-Gaussian types of problems. ORACLS is rigorous tool, intended for multi-input and multi-output dynamic systems in both continuous and discrete form. Written in FORTRAN.
Graduate and Professional Education (Including Admissions and Financial Aid)
ERIC Educational Resources Information Center
College and University, 1977
1977-01-01
Topics covered at the AACRAO's 63rd annual meeting include: graduate education forecasting, admissions management, aid, and recruitment; quality control in nontraditional graduate education; and financial planning for the professional school student. (LBH)
Validation of space/ground antenna control algorithms using a computer-aided design tool
NASA Technical Reports Server (NTRS)
Gantenbein, Rex E.
1995-01-01
The validation of the algorithms for controlling the space-to-ground antenna subsystem for Space Station Alpha is an important step in assuring reliable communications. These algorithms have been developed and tested using a simulation environment based on a computer-aided design tool that can provide a time-based execution framework with variable environmental parameters. Our work this summer has involved the exploration of this environment and the documentation of the procedures used to validate these algorithms. We have installed a variety of tools in a laboratory of the Tracking and Communications division for reproducing the simulation experiments carried out on these algorithms to verify that they do meet their requirements for controlling the antenna systems. In this report, we describe the processes used in these simulations and our work in validating the tests used.
Impact of electronic reminders on venous thromboprophylaxis after admissions and transfers
Beeler, P E; Eschmann, E; Schumacher, A; Studt, J-D; Amann-Vesti, B; Blaser, J
2014-01-01
Objective Clinical decision support has the potential to improve prevention of venous thromboembolism (VTE). The purpose of this prospective study was to analyze the effect of electronic reminders on thromboprophylaxis rates in wards to which patients were admitted and transferred. The latter was of particular interest since patient handoffs are considered to be critical safety issues. Methods The trial involved two study periods in the six departments of a university hospital, three of which were randomly assigned to the intervention group displaying reminders during the second period. At 6 h after admission or transfer, the algorithm checked for prophylaxis orders within 0–30 h of the patient's arrival, increasing the specificity of the displayed reminders. Results The significant impact of the reminders could be seen by prophylaxis orders placed 6–24 h after admission (increasing from 8.6% (223/2579) to 12% (307/2555); p<0.0001) and transfer (increasing from 2.4% (39/1616) to 3.7% (63/1682); p=0.034). In admission wards, the rate of thromboprophylaxis increased from 62.4% to 67.7% (p<0.0001), and in transfer wards it increased from 80.2% to 84.3% (p=0.0022). Overall, the rate of prophylaxis significantly increased in the intervention group from 69.2% to 74.3% (p<0.0001). No significant changes were observed in the control group. Postponing prophylaxis checks to 6 h after admissions and transfers reduced the number of reminders by 62% and thereby minimized the risk of alert fatigue. Conclusions The reminders improved awareness of VTE prevention in both admission and transfer wards. This approach may contribute to better quality of care and safer patient handoffs. PMID:24671361
Two neural network algorithms for designing optimal terminal controllers with open final time
NASA Technical Reports Server (NTRS)
Plumer, Edward S.
1992-01-01
Multilayer neural networks, trained by the backpropagation through time algorithm (BPTT), have been used successfully as state-feedback controllers for nonlinear terminal control problems. Current BPTT techniques, however, are not able to deal systematically with open final-time situations such as minimum-time problems. Two approaches which extend BPTT to open final-time problems are presented. In the first, a neural network learns a mapping from initial-state to time-to-go. In the second, the optimal number of steps for each trial run is found using a line-search. Both methods are derived using Lagrange multiplier techniques. This theoretical framework is used to demonstrate that the derived algorithms are direct extensions of forward/backward sweep methods used in N-stage optimal control. The two algorithms are tested on a Zermelo problem and the resulting trajectories compare favorably to optimal control results.
Vega roll and attitude control system algorithms trade-off study
NASA Astrophysics Data System (ADS)
Paulino, N.; Cuciniello, G.; Cruciani, I.; Corraro, F.; Spallotta, D.; Nebula, F.
2013-12-01
This paper describes the trade-off study for the selection of the most suitable algorithms for the Roll and Attitude Control System (RACS) within the FPS-A program, aimed at developing the new Flight Program Software of VEGA Launcher. Two algorithms were analyzed: Switching Lines (SL) and Quaternion Feedback Regulation. Using a development simulation tool that models two critical flight phases (Long Coasting Phase (LCP) and Payload Release (PLR) Phase), both algorithms were assessed with Monte Carlo batch simulations for both of the phases. The statistical outcomes of the results demonstrate a 100 percent success rate for Quaternion Feedback Regulation, and support the choice of this method.
On the nature of control algorithms for free-floating space manipulators
NASA Technical Reports Server (NTRS)
Papadopoulos, Evangelos; Dubowsky, Steven
1991-01-01
It is suggested that nearly any control algorithm that can be used for fixed-based manipulators also can be employed in the control of free-floating space manipulator systems, with the additional conditions of estimating or measuring a spacecraft's orientation and of avoiding dynamic singularities. This result is based on the structural similarities between the kinematic and dynamic equations for the same manipulator but with a fixed base. Barycenters are used to formulate the kinematic and dynamic equations of free-floating space manipulators. A control algorithm for a space manipulator system is designed to demonstrate the value of the analysis.
Gain spectrum self controlling device and algorithm for mutiply pumped Raman amplifiers
NASA Astrophysics Data System (ADS)
Wang, Jia Ying
2004-05-01
For both forward- and backward-pumped Raman amplifiers, devices to perform gain-spectrum self-control of multi-laser pumps are depicted in this paper. The algorithm supporting the devices is presented also. The function of automatic control is suitable for on-line maintenance of WDM equipment.
Voltage and Reactive Power Control by Integration of Genetic Algorithm and Tabu Search
NASA Astrophysics Data System (ADS)
Aoki, Hidenori; Yamamoto, Kensei; Mizutani, Yoshibumi
This paper presents on the result of voltage and reactive power control by use of the proposed method. The feature of proposed method is integration of genetic algorithm (GA) and tabu search (TS). This method obtains an excellent fitness at shorter calculation time than GA considering conventional control process. The effectiveness of this method is shown by a practicable 15-bus system.
NASA Technical Reports Server (NTRS)
Boussalis, Dhemetrios; Wang, Shyh J.
1992-01-01
This paper presents a method for utilizing artificial neural networks for direct adaptive control of dynamic systems with poorly known dynamics. The neural network weights (controller gains) are adapted in real time using state measurements and a random search optimization algorithm. The results are demonstrated via simulation using two highly nonlinear systems.
A Sequential Shifting Algorithm for Variable Rotor Speed Control
NASA Technical Reports Server (NTRS)
Litt, Jonathan S.; Edwards, Jason M.; DeCastro, Jonathan A.
2007-01-01
A proof of concept of a continuously variable rotor speed control methodology for rotorcraft is described. Variable rotor speed is desirable for several reasons including improved maneuverability, agility, and noise reduction. However, it has been difficult to implement because turboshaft engines are designed to operate within a narrow speed band, and a reliable drive train that can provide continuous power over a wide speed range does not exist. The new methodology proposed here is a sequential shifting control for twin-engine rotorcraft that coordinates the disengagement and engagement of the two turboshaft engines in such a way that the rotor speed may vary over a wide range, but the engines remain within their prescribed speed bands and provide continuous torque to the rotor; two multi-speed gearboxes facilitate the wide rotor speed variation. The shifting process begins when one engine slows down and disengages from the transmission by way of a standard freewheeling clutch mechanism; the other engine continues to apply torque to the rotor. Once one engine disengages, its gear shifts, the multi-speed gearbox output shaft speed resynchronizes and it re-engages. This process is then repeated with the other engine. By tailoring the sequential shifting, the rotor may perform large, rapid speed changes smoothly, as demonstrated in several examples. The emphasis of this effort is on the coordination and control aspects for proof of concept. The engines, rotor, and transmission are all simplified linear models, integrated to capture the basic dynamics of the problem.
Alavandar, Srinivasan; Nigam, M J
2009-10-01
Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. In this paper, some new hybrid adaptive neuro-fuzzy control algorithms (ANFIS) have been proposed for manipulator control with uncertainties. These hybrid controllers consist of adaptive neuro-fuzzy controllers and conventional controllers. The outputs of these controllers are applied to produce the final actuation signal based on current position and velocity errors. Numerical simulation using the dynamic model of six DOF puma robot arm with uncertainties shows the effectiveness of the approach in trajectory tracking problems. Performance indices of RMS error, maximum error are used for comparison. It is observed that the hybrid adaptive neuro-fuzzy controllers perform better than only conventional/adaptive controllers and in particular hybrid controller structure consisting of adaptive neuro-fuzzy controller and critically damped inverse dynamics controller. PMID:19523623
Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R
1991-04-01
A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049
Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R
1991-01-01
A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049
NASA Astrophysics Data System (ADS)
Lin, Jeng-Wen; Shen, Pu Fun; Wen, Hao-Ping
2015-10-01
The application of a repetitive control mechanism for use in a mechanical control system has been a topic of investigation. The fundamental purpose of repetitive control is to eliminate disturbances in a mechanical control system. This paper presents two different repetitive control laws using individual types of basis function feedback and their combinations. These laws adjust the command given to a feedback control system to eliminate tracking errors, generally resulting from periodic disturbance. Periodic errors can be reduced through linear basis functions using regression and a genetic algorithm. The results illustrate that repetitive control is most effective method for eliminating disturbances. When the data are stabilized, the tracking error of the obtained convergence value, 10-14, is the optimal solution, verifying that the proposed regression and genetic algorithm can satisfactorily reduce periodic errors.
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs
Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan
2015-01-01
In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network. PMID:26571042
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.
Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan
2015-01-01
In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network. PMID:26571042
Multiple Unmanned Air Vehicles Control Using Neurobiologically Inspired Algorithms
NASA Astrophysics Data System (ADS)
Zhang, Yong; Wang, Li
In order to develop and evaluate future Unmanned Air Vehicles for the hazardous environmental monitoring, the comprehensive simulation test and analysis of new advanced concepts is imperative. This paper details an on-going proof of concept focused on development of a neurobiologically-inspired system for the high level control of a Air Vehicle team. This study, entitled Neurobiologically Enabled Autonomous Vehicle Operations, will evaluate initial System-Under-Test concept data by selecting well defined tasks, and evaluating performance based on assignment effectiveness, cooperation, and adaptability of the system. The system will be tested thoroughly in simulation, and if mature, will be implemented in hardware.
Realization of TV guidance gyro stabilized platform and research of control algorithm
NASA Astrophysics Data System (ADS)
Yang, Pu; Li, Qi
2007-11-01
According to the special performance requirements of optoelectronic tracking equipments, a high-precision three-axis TV guidance gyro stabilized platform was designed and realized. The main techniques, including system construction, mechanical resonance and software and hardware implementation, were discussed and analyzed in details. Two hard cores of the system, the TV tracker and the servo controller, were investigated concretely. For the TV tracker, an improved correlation tracking algorithm was proposed and a fast search method based on image multiple resolutions was adopted, by which total computation time of the image processing system was decreased and the capability of target identification was enhanced. For the servo controller, a multiple closed-loops control structure was founded. To the problem of system nonlinear disturbances, some main disturbance-producing causes in the system were explored and a grey sliding mode control algorithm was proposed. With the control algorithm, the anti-disturbance capability of the system was increased effectively and the dynamic performance of the control system was ameliorated. The operating results of the platform show that the whole design of the system is appropriate and the control algorithms adopted are feasible and computationally efficient.
Chanan, Gary; Nelson, Jerry
2009-11-10
The active control systems of segmented mirror telescopes are vulnerable to a malfunction of a few (or even one) of their segment edge sensors, the effects of which can propagate through the entire system and seriously compromise the overall telescope image quality. Since there are thousands of such sensors in the extremely large telescopes now under development, it is essential to develop fast and efficient algorithms that can identify bad sensors so that they can be removed from the control loop. Such algorithms are nontrivial; for example, a simple residual-to-the-fit test will often fail to identify a bad sensor. We propose an algorithm that can reliably identify a single bad sensor and we extend it to the more difficult case of multiple bad sensors. Somewhat surprisingly, the identification of a fixed number of bad sensors does not necessarily become more difficult as the telescope becomes larger and the number of sensors in the control system increases. PMID:19904329
An Energy-Efficient, Application-Oriented Control Algorithm for MAC Protocols in WSN
NASA Astrophysics Data System (ADS)
Li, Deliang; Peng, Fei; Qian, Depei
Energy efficiency has been a main concern in wireless sensor networks where Medium Access Control (MAC) protocol plays an important role. However, current MAC protocols designed for energy saving have seldom considered multiple applications coexisting in WSN with variation of traffic load dynamics and different QoS requirements. In this paper, we propose an adaptive control algorithm at MAC layer to promote energy efficiency. We focus on the tradeoff relation between collisions and control overhead as a reflection of traffic load and propose to balance the tradeoff under the constraints of QoS options. We integrate the algorithm into S-MAC and verify it through NS-2 platform. The results demonstrate the algorithm achieves observable improvement in energy performance while meeting QoS requirement for different coexisting applications in comparison with S-MAC.
Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm
NASA Astrophysics Data System (ADS)
Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung
2016-07-01
In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.
Active suppression of nonlinear composite beam vibrations by selected control algorithms
NASA Astrophysics Data System (ADS)
Warminski, Jerzy; Bochenski, Marcin; Jarzyna, Wojciech; Filipek, Piotr; Augustyniak, Michal
2011-05-01
This paper is focused on application of different control algorithms for a flexible, geometrically nonlinear beam-like structure with Macro Fiber Composite (MFC) actuator. Based on the mathematical model of a geometrically nonlinear beam, analytical solutions for Nonlinear Saturation Controller (NSC) are obtained using Multiple Scale Method. Effectiveness of different control strategies is evaluated by numerical simulations in Matlab-Simulink software. Then, the Digital Signal Processing (DSP) controller and selected control algorithms are implemented to the physical system to compare numerical and experimental results. Detailed analysis for the NSC system is carried out, especially for high level of amplitude and wide range of frequencies of excitation. Finally, the efficiency of the considered controllers is tested experimentally for a more complex autoparametric " L-shape" beam system.
Comparison of Reconstruction and Control algorithms on the ESO end-to-end simulator OCTOPUS
NASA Astrophysics Data System (ADS)
Montilla, I.; Béchet, C.; Lelouarn, M.; Correia, C.; Tallon, M.; Reyes, M.; Thiébaut, É.
Extremely Large Telescopes are very challenging concerning their Adaptive Optics requirements. Their diameters, the specifications demanded by the science for which they are being designed for, and the planned use of Extreme Adaptive Optics systems, imply a huge increment in the number of degrees of freedom in the deformable mirrors. It is necessary to study new reconstruction algorithms to implement the real time control in Adaptive Optics at the required speed. We have studied the performance, applied to the case of the European ELT, of three different algorithms: the matrix-vector multiplication (MVM) algorithm, considered as a reference; the Fractal Iterative Method (FrIM); and the Fourier Transform Reconstructor (FTR). The algorithms have been tested on ESO's OCTOPUS software, which simulates the atmosphere, the deformable mirror, the sensor and the closed-loop control. The MVM is the default reconstruction and control method implemented in OCTOPUS, but it scales in O(N2) operations per loop so it is not considered as a fast algorithm for wave-front reconstruction and control on an Extremely Large Telescope. The two other methods are the fast algorithms studied in the E-ELT Design Study. The performance, as well as their response in the presence of noise and with various atmospheric conditions, has been compared using a Single Conjugate Adaptive Optics configuration for a 42 m diameter ELT, with a total amount of 5402 actuators. Those comparisons made on a common simulator allow to enhance the pros and cons of the various methods, and give us a better understanding of the type of reconstruction algorithm that an ELT demands.
Dual Engine application of the Performance Seeking Control algorithm
NASA Technical Reports Server (NTRS)
Mueller, F. D.; Nobbs, S. G.; Stewart, J. F.
1993-01-01
The Dual Engine Performance Seeking Control (PSC) flight/propulsion optimization program has been developed and will be flown during the second quarter of 1993. Previously, only single engine optimization was possible due to the limited capability of the on-board computer. The implementation of Dual Engine PSC has been made possible with the addition of a new state-of-the-art, higher throughput computer. As a result, the single engine PSC performance improvements already flown will be demonstrated on both engines, simultaneously. Dual Engine PSC will make it possible to directly compare aircraft performance with and without the improvements generated by PSC. With the additional thrust achieved with PSC, significant improvements in acceleration times and time to climb will be possible. PSC is also able to reduce deceleration time from supersonic speeds. This paper traces the history of the PSC program, describes the basic components of PSC, discusses the development and implementation of Dual Engine PSC including additions to the code, and presents predictions of the impact of Dual Engine PSC on aircraft performance.
Algorithm and data support of traffic congestion forecasting in the controlled transport
NASA Astrophysics Data System (ADS)
Dmitriev, S. V.
2015-06-01
The topicality of problem of the traffic congestion forecasting in the logistic systems of product movement highways is considered. The concepts: the controlled territory, the highway occupancy by vehicles, the parking and the controlled territory are introduced. Technical realizabilityof organizing the necessary flow of information on the state of the transport system for its regulation has been marked. Sequence of practical implementation of the solution is given. An algorithm for predicting traffic congestion in the controlled transport system is suggested.
Ma, Shaodong; Wilkinson, Antony J; Paulson, Kevin S
2014-02-01
A non-linear control method, known as Variable Structure Control (VSC), is employed to reduce the duration of ultrasonic (US) transducer transients. A physically realizable system using a simplified form of the VSC algorithm is proposed for standard piezoelectric transducers and simulated. Results indicate a VSC-controlled transmitter reduces the transient duration to less than a carrier wave cycle. Applications include high capacity ultrasound communication and localization systems. PMID:23993746
Machnes, S.; Sander, U.; Glaser, S. J.; Schulte-Herbrueggen, T.; Fouquieres, P. de; Gruslys, A.; Schirmer, S.
2011-08-15
For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions are pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.
The Path-of-Probability Algorithm for Steering and Feedback Control of Flexible Needles
Park, Wooram; Wang, Yunfeng; Chirikjian, Gregory S.
2010-01-01
In this paper we develop a new framework for path planning of flexible needles with bevel tips. Based on a stochastic model of needle steering, the probability density function for the needle tip pose is approximated as a Gaussian. The means and covariances are estimated using an error propagation algorithm which has second order accuracy. Then we adapt the path-of-probability (POP) algorithm to path planning of flexible needles with bevel tips. We demonstrate how our planning algorithm can be used for feedback control of flexible needles. We also derive a closed-form solution for the port placement problem for finding good insertion locations for flexible needles in the case when there are no obstacles. Furthermore, we propose a new method using reference splines with the POP algorithm to solve the path planning problem for flexible needles in more general cases that include obstacles. PMID:21151708
Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units
Fernandez, Nicholas; Brambley, Michael R.; Katipamula, Srinivas
2009-12-31
This report documents the self-correction algorithms developed in the Self-Correcting Heating, Ventilating and Air-Conditioning (HVAC) Controls project funded jointly by the Bonneville Power Administration and the Building Technologies Program of the U.S. Department of Energy. The algorithms address faults for temperature sensors, humidity sensors, and dampers in air-handling units and correction of persistent manual overrides of automated control systems. All faults considered create energy waste when left uncorrected as is frequently the case in actual systems.
Multiparty controlled quantum secure direct communication based on quantum search algorithm
NASA Astrophysics Data System (ADS)
Kao, Shih-Hung; Hwang, Tzonelih
2013-12-01
In this study, a new controlled quantum secure direct communication (CQSDC) protocol using the quantum search algorithm as the encoding function is proposed. The proposed protocol is based on the multi-particle Greenberger-Horne-Zeilinger entangled state and the one-step quantum transmission strategy. Due to the one-step transmission of qubits, the proposed protocol can be easily extended to a multi-controller environment, and is also free from the Trojan horse attacks. The analysis shows that the use of quantum search algorithm in the construction of CQSDC appears very promising.
Chaotic queue-based genetic algorithm for design of a self-tuning fuzzy logic controller
NASA Astrophysics Data System (ADS)
Saini, Sanju; Saini, J. S.
2012-11-01
This paper employs a chaotic queue-based method using logistic equation in a non-canonical genetic algorithm for optimizing the performance of a self-tuning Fuzzy Logic Controller, used for controlling a nonlinear double-coupled system. A comparison has been made with a standard canonical genetic algorithm implemented on the same plant. It has been shown that chaotic queue-method brings an improvement in the performance of the FLC for wide range of set point changes by a more profound initial population spread in the search space.
Design of State-Space-Based Control Algorithms for Wind Turbine Speed Regulation: Preprint
Wright, A.; Balas, M.
2002-01-01
Control can improve the performance of wind turbines by enhancing energy capture and reducing dynamic loads.At the National Renewable Energy Laboratory, we are beginning to design control algorithms for regulation of turbine speed and power using state-space control designs. In this paper, we describe the design of such a control algorithm for regulation of rotor speed in full-load operation (region 3) for a two-bladed wind turbine. We base our control design on simple linear models of a turbine, which contain rotor and generator rotation, drivetrain torsion, and rotor flap degrees of freedom (first mode only). We account for wind-speed fluctuations using disturbance-accommodating control. We show the capability of these control schemes to stabilize the modeled turbine modes via pole placement while using state estimation to reduce the number of turbine measurements that are needed for these control algorithms. We incorporate these controllers into the FAST-AD code and show simulation results for various conditions. Finally, we report conclusions to this work and outline future studies.
Differential Freshman Admission by Sex
ERIC Educational Resources Information Center
Suddick, David E.; McBee, M. Louise
1974-01-01
The authors report on a study whose purpose was to determine if, after adjusting for initial differences in high school averages and SAT scores via separate regression equations, differential admissions criterion by sex is justifiable. No justification is found. (RP)
ED navigators prevent unnecessary admissions.
2012-02-01
RN Navigators in the emergency department at Montefiore Medical Center work with social workers to prevent unnecessary admissions. Program targets the homeless and patients with tenuous living situations. CMs work with the emergency department staff to identify patients who don't meet admission criteria but can't be safely discharged. The hospital collaborates with a local housing assistance agency which sends a van to transport appropriate patients to a shelter. PMID:22299178
NASA Technical Reports Server (NTRS)
Seltzer, S. M.
1976-01-01
The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.
NASA Astrophysics Data System (ADS)
Bhole, Gaurav; Anjusha, V. S.; Mahesh, T. S.
2016-04-01
A robust control over quantum dynamics is of paramount importance for quantum technologies. Many of the existing control techniques are based on smooth Hamiltonian modulations involving repeated calculations of basic unitaries resulting in time complexities scaling rapidly with the length of the control sequence. Here we show that bang-bang controls need one-time calculation of basic unitaries and hence scale much more efficiently. By employing a global optimization routine such as the genetic algorithm, it is possible to synthesize not only highly intricate unitaries, but also certain nonunitary operations. We demonstrate the unitary control through the implementation of the optimal fixed-point quantum search algorithm in a three-qubit nuclear magnetic resonance (NMR) system. Moreover, by combining the bang-bang pulses with the crusher gradients, we also demonstrate nonunitary transformations of thermal equilibrium states into effective pure states in three- as well as five-qubit NMR systems.
Tuning algorithms for fractional order internal model controllers for time delay processes
NASA Astrophysics Data System (ADS)
Muresan, Cristina I.; Dutta, Abhishek; Dulf, Eva H.; Pinar, Zehra; Maxim, Anca; Ionescu, Clara M.
2016-03-01
This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.
NASA Technical Reports Server (NTRS)
Davis, M. W.
1984-01-01
A Real-Time Self-Adaptive (RTSA) active vibration controller was used as the framework in developing a computer program for a generic controller that can be used to alleviate helicopter vibration. Based upon on-line identification of system parameters, the generic controller minimizes vibration in the fuselage by closed-loop implementation of higher harmonic control in the main rotor system. The new generic controller incorporates a set of improved algorithms that gives the capability to readily define many different configurations by selecting one of three different controller types (deterministic, cautious, and dual), one of two linear system models (local and global), and one or more of several methods of applying limits on control inputs (external and/or internal limits on higher harmonic pitch amplitude and rate). A helicopter rotor simulation analysis was used to evaluate the algorithms associated with the alternative controller types as applied to the four-bladed H-34 rotor mounted on the NASA Ames Rotor Test Apparatus (RTA) which represents the fuselage. After proper tuning all three controllers provide more effective vibration reduction and converge more quickly and smoothly with smaller control inputs than the initial RTSA controller (deterministic with external pitch-rate limiting). It is demonstrated that internal limiting of the control inputs a significantly improves the overall performance of the deterministic controller.
Algorithms for a Closed-Loop Artificial Pancreas: The Case for Model Predictive Control
Bequette, B. Wayne
2013-01-01
The relative merits of model predictive control (MPC) and proportional-integral-derivative (PID) control are discussed, with the end goal of a closed-loop artificial pancreas (AP). It is stressed that neither MPC nor PID are single algorithms, but rather are approaches or strategies that may be implemented very differently by different engineers. The primary advantages to MPC are that (i) constraints on the insulin delivery rate (and/or insulin on board) can be explicitly included in the control calculation; (ii) it is a general framework that makes it relatively easy to include the effect of meals, exercise, and other events that are a function of the time of day; and (iii) it is flexible enough to include many different objectives, from set-point tracking (target) to zone (control to range). In the end, however, it is recognized that the control algorithm, while important, represents only a portion of the effort required to develop a closed-loop AP. Thus, any number of algorithms/approaches can be successful—the engineers involved in the design must have experience with the particular technique, including the important experience of implementing the algorithm in human studies and not simply through simulation studies. PMID:24351190
Implementation of a new iterative learning control algorithm on real data.
Zamanian, Hamed; Koohi, Ardavan
2016-02-01
In this paper, a newly presented approach is proposed for closed-loop automatic tuning of a proportional integral derivative (PID) controller based on iterative learning control (ILC) algorithm. A modified ILC scheme iteratively changes the control signal by adjusting it. Once a satisfactory performance is achieved, a linear compensator is identified in the ILC behavior using casual relationship between the closed loop signals. This compensator is approximated by a PD controller which is used to tune the original PID controller. Results of implementing this approach presented on the experimental data of Damavand tokamak and are consistent with simulation outcome. PMID:26931852