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IEEE Annual Conference on Decision and control

作者： Benjamin Reish Girish Chowdhary school of mechanical and aerospace engineering Oklahoma State University Stillwater OK

ISBN: (纸本)9781467360890

Most model reference adaptive control methods assume that the sign of control effectiveness is known. These methods cannot be used in situations that require adaptation in presence of unknown sign of control effectiveness, such as when controls reverse on an flexible aircraft due to wing twist, or when actuator mappings are unknown. To handle such situations, a Concurrent Learning model reference adaptive control method is developed for linear uncertain dynamical systems where the sign of the control effectiveness, and parameters of the control allocation matrix, are unknown. The approach relies on simultaneous estimation of the control allocation matrix using online recorded and instantaneous data concurrently, while the system is being actively controlled using the online updated estimate. It is shown that the tracking error and weight error convergence depends on how accurate the estimates of the unknown parameters are. This is used to establish the necessity for purging the concurrent learning history stacks, and three algorithms for purging the history stack for eventual re-population are presented. It is shown that the system states will not grow unbounded even when the sign of the control effectiveness is unknown, and the control allocation matrix is being estimated online. Simulations validate the theoretical results.

关键词： control effect control systems Unknown model reference adaptive control flexible air vehicles control Methods Signed Standing Orders

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Improved model reference adaptive control for Load Simulator

Improved Model Reference Adaptive Control for Load Simulator

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Asia Simulation Conference/7th International Conference on System Simulation and Scientific Computing

作者： Fan, Jinhua Zheng, Zhiqiang Natl Univ Def Technol Dept Automat Control Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Changsha Hunan Peoples R China

ISBN: (纸本)9781424417865

This study presents an improved model reference adaptive control (MRAC) method for the load simulator. Based on the MRAC method, an adaptive feedforward controller was constructed to eliminate the extraneous torque. By constructing the appropriate form of the feedforward controller and the Lyapunov function, the convergence of the tracking error was proved with Lyapunov stable theorem, and the adaptive law of the controller parameters was achieved. The simulation results indicate that the load simulator with the improved MRAC can get high performance, and its performance can be greatly improved compared with the system under normal MRAC.

关键词： model reference adaptive control

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Gain Margins of model reference adaptive control Systems

Gain Margins of Model Reference Adaptive Control Systems

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7th World Congress on Intelligent control and Automation

作者： Sang, Qian Tao, Gang Univ Virginia Dept Elect & Comp Engn Charlottesville VA 22904 USA

ISBN: (纸本)9781424421138

This paper studies the gain margins of model reference adaptive control (MRAC) systems: the range of a control gain in a designed adaptive control system, which is sufficient for closed-loop signal boundedness and asymptotic tracking. Analytical results are obtained for four MRAC schemes: direct and indirect, continuous-time and discrete-time, applied to single-input single-output LTI systems. Simulation results are presented to illustrate some of the results.

关键词： Gain margin model reference adaptive control high frequency gain

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Robust adaptive model Tracking control for Linear Infinite Dimensional Symmetric Hyperbolic Systems

Robust Adaptive Model Tracking Control for Linear Infinite D...

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IEEE Annual Conference on Decision and control

作者： Mark J. Balas Susan A. Frost Aerospace Engineering Department Embry-Riddle Aeronautical University Daytona Beach FL 32114 USA Intelligent Systems Division NASA Ames Research Center Moffett Field CA 94035 USA

ISBN: (纸本)9781467360890

Symmetric Hyperbolic Systems of partial differential equations describe many physical phenomena such as wave behavior, electromagnetic fields, and quantum fields. The plant is described by a closed densely defined linear operator that generates a continuous semigroup of bounded operators on the Hilbert space of states. Here we show that there exists a stabilizing direct model reference adaptive control law with certain disturbance rejection and robustness properties. The closed loop system is shown to be exponentially convergent to a neighborhood with radius proportional to bounds on the size of the disturbance. We apply the results to control of symmetric hyperbolic systems with coercive boundary conditions.

关键词： hyperbolic systems Hilbert space state space CENTROSYMMETRIC adaptive model Physical Phenomena Disturbance rejection control law model reference adaptive control tracking control

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adaptive control OF PIECEWISE LINEAR SYSTEMS WITH STATE FEEDBACK FOR OUTPUT TRACKING

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ASIAN JOURNAL OF control 2013年第4期15卷 933-943页

作者： Sang, Qian Tao, Gang Univ Virginia Dept Elect & Comp Engn Charlottesville VA 22904 USA

A piecewise linear system consists of a set of linear time-invariant (LTI) subsystems, with a switching sequence specifying an active subsystem at each time instant. This paper studies the adaptive control problem of single-input, single-output (SISO) piecewise linear systems. By employing the knowledge of the time instant indicator functions of system parameter switches, a new controller structure parametrization is proposed for the development of a stable adaptive control scheme with reduced modeling error in the estimation error signal used for parameter adaptive laws. This key feature is achieved by the new control scheme's ability to avoid a major parameter swapping term in the error model, with the help of indicator functions whose knowledge is available in many applications. A direct state feedback model reference adaptive control (MRAC) scheme is presented for such systems to achieve closed-loop signal boundedness and small output tracking error in the mean square sense, under the usual slow system parameter switching condition. Simulation results on linearized NASA GTM models are presented to demonstrate the effectiveness of the proposed scheme.

关键词： model reference adaptive control piecewise linear systems state feedback for output tracking

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Composite adaptive control of Belt Polishing Force for Aero-engine Blade

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Chinese Journal of Mechanical Engineering 2013年第5期26卷 988-996页

作者： ZHsAO Pengbing SHI Yaoyao Key Laboratory of Contemporary Design and Integrated Manufacturing Technology of Ministry of Education Northwestern Polytechnical University

The existing methods for blade polishing mainly focus on robot polishing and manual *** to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot polishing,in particular,quality of the inlet and exhaust edges can not satisfy the processing *** grinding has low efficiency,high labor intensity and unstable processing quality,moreover,the polished surface is vulnerable to burn,and the surface precision and integrity are difficult to *** order to further improve the profile accuracy and surface quality,a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed,which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) *** the mode decision-making mechanism,Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value,and MRACFNN is utilized in smaller error ranges to improve the system robustness and control *** on the mathematical model of the force-exerting mechanism,simulation analysis is implemented on *** results show that the output polishing force can better track the given ***,the blade polishing experiments are carried out on the designed polishing *** results show that DSCAC can effectively mitigate the influence of gas compressibility,valve dead-time effect,valve nonlinear flow,cylinder friction,measurement noise and other interference on the control precision of polishing force,which has high control precision,strong robustness,strong anti-interference ability and other advantages compared with *** proposed research achieves high-precision control of the polishing force,effectively improves the blade machining precision and surface consistency,and significantly reduces the surface roughness.

关键词： blade polishing force Bang-Bang control fuzzy neural network model reference adaptive control

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adaptive Vectored Thrust Deorbiting of Space Debris

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JOURNAL OF SPACECRAFT AND ROCKETS 2013年第2期50卷 394-401页

作者： Tewari, Ashish Indian Inst Technol Dept Aerosp Engn Kanpur 208016 Uttar Pradesh India

A novel but simple deorbiting control system is proposed for cleaning up space debris in a low Earth orbit. The method consists of employing a low-thrust spacecraft tug with a continuously varying thrust direction for collecting and decelerating debris items at a given orbital radius. A time-linear thrust-direction profile is the outcome of the nominal, two-point boundary-value problem for deceleration by a given velocity magnitude. Three simple model reference adaptive control strategies are proposed for driving the velocity error from nominal to zero in the presence of uncertain debris mass and rocket thrust variation. Although linear time-varying control with velocity feedback and a dead-zone is sufficient to minimize tracking error in most cases, it is improved significantly by a Lyapunov-based controller that guarantees asymptotic stability in the presence of a random but bounded acceleration disturbance. A nonlinear feedback adaptation law based upon the MIT rule achieves the fastest error decay rate error of the three techniques and is seen to have a logarithmic relationship between the steady-state value of controller parameter and adaptation gain.

关键词： control strategy velocity feedback Dead band deceleration Space debris Nominal model reference adaptive control Reentry into atmosphere asymptotic stability region velocity errors

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Discrete-Time Parameter Identification of a Surface-Mounted Permanent Magnet Synchronous Machine

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2013年第11期60卷 4869-4880页

作者： Gatto, Gianluca Marongiu, Ignazio Serpi, Alessandro Univ Cagliari Dept Elect & Elect Engn I-09123 Cagliari Italy

A novel online discrete-time parameter identification algorithm suitable for surface-mounted permanent magnet synchronous machines (SPMs) is presented in this paper. It is developed by means of the model reference adaptive system technique and the Popov Hyperstability Criterion in order to identify SPM discrete-time model parameters. In particular, good accuracy of discrete-time parameters is required by digital control systems, particularly by predictive control algorithms, which present a low robustness against parameter mismatches. Hence, an extensive simulation study is first carried out in the Matlab Simulink environment with the aim of testing the effectiveness and robustness of the proposed identification algorithm against inverter unidealities. Then, the proposed identification procedure is experimentally validated on a predictive controlled radial-flux SPM, driven by a field programmable gate arrays control board.

关键词： Field programmable gate arrays (FPGAs) model reference adaptive control parameter identification permanent magnet machines predictive control

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Concurrent learning adaptive control of linear systems with exponentially convergent bounds

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INTERNATIONAL JOURNAL OF adaptive control AND SIGNAL PROCESSING 2013年第4期27卷 280-301页

作者： Chowdhary, Girish Yucelen, Tansel Muehlegg, Maximillian Johnson, Eric N. Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30318 USA Tech Univ Munich D-80290 Munich Germany

Concurrent learning adaptive controllers, which use recorded and current data concurrently for adaptation, are developed for model reference adaptive control of uncertain linear dynamical systems. We show that a verifiable condition on the linear independence of the recorded data is sufficient to guarantee global exponential stability. We use this fact to develop exponentially decaying bounds on the tracking error and weight error, and estimate upper bounds on the control signal. These results allow the development of adaptive controllers that ensure good tracking without relying on high adaptation gains, and can be designed to avoid actuator saturation. Simulations and hardware experiments show improved performance. Copyright (C) 2012 John Wiley & Sons, Ltd.

关键词： model reference adaptive control persistency of excitation uncertain multivariable linear dynamical systems

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adaptive control in series load PWM induction heating inverters

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INTERNATIONAL JOURNAL OF ELECTRONICS 2013年第12期100卷 1714-1723页

作者： Szelitzky, Tibor Dulf, Eva Henrietta Tech Univ Cluj Napoca Dept Automat Control Fac Automat & Comp Sci Cluj Napoca Romania

Permanent variations of the electric properties of the load in induction heating equipment make difficult to control the plant. To overcome these disadvantages, the authors propose a new approach based on adaptive control methods. For real plants it is enough to present desired performances or start-up variables for the controller, from which the algorithms tune the controllers by itself. To present the advantages of the proposed controllers, comparisons are made to a PI controller tuned through Ziegler-Nichols method.

关键词： model reference adaptive control self-tuning adaptive control PI control Ziegler-Nichols controller tuning induction heating inverter frequency control resonant inverters

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