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OPTIMAL control FOR TWO-DIMENSIONAL LINEAR systems WITH VARIABLE COEFFICIENTS

Asian Journal of control 2008年第4期1卷

作者： Jimshone Li Jason Sheng-Hong Tsai Leang-San Shieh Control System Laboratory Department of Electrical Engineering National Cheng Kung University Tainan 701 Taiwan R.O.C. Jim-Shone Li was born in Taiwan R. O.C. on April 20 1967. He received B.S. and M.S. degrees in Electrical Engineering from the Chung-Cheng Institute of Technology Taoyuan Taiwan R.O.C. in 1989 and 1993 respectively. He is currently a Ph.D. student at National Cheng-Kung University Tainan Taiwan R.O.C. His research interests include analysis and design of multidimensional systems and nonlinear system control. Department of Electrical and Computer Engineering University of Houston Houston TX 77004-4793 U.S.A.

An optimal control method for two-dimensional (2-D) linear systems with variable coefficients and free boundary conditions in Roesser's model is proposed in this paper. Based on Roesser's model, an equivalent general 1-D model of the 2-D system is presented, and the problem of minimizing a 2-D linear quadratic (LQ) cost function is solved for the case where complete state information is available. The solution is obtained by using the proposed dynamic programming in 1-D descriptor form to solve the Riccati equation and then arriving at the optimal control law and minimum cost. The proposed control methodology can be applied to discrete-time models of systems described by partial differential equations and can also be used in the field of signal processing.

关键词： Two-dimensional system optimal control Roesser's model Riccati equation

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Adaptive SDRE-Based Nonlinear Sensorless Speed control for PMSM Drives

Adaptive SDRE-Based Nonlinear Sensorless Speed Control for P...

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Annual North-American Power Symposium

作者： Peda V. Medagam Tansel Yucelen Farzad Pourboghrat Embedded Control Systems Laboratory Department of Electrical and Computer Engineering Southem Illinois University Carbondale Carbondale IL USA Department of Electrical and Computer Engineering Southem Illinois University Carbondale Carbondale IL USA

This paper presents a new adaptive nonlinear control approach for permanent magnet synchronous motor (PMSM) drives, without requiring speed sensors. The proposed approach is based on state-dependent Riccati equation (SDRE) control technique and its real-time computation method by gradient-type neural networks, that allows one to control PMSM online. For this purpose, the unknown parameters of the PMSM drive; stator resistance, load torque, and motor speed, are also estimated using an extended Kalman filter (EKF) algorithm. The resulted adaptive algorithm is independent from any initial conditions, relatively fast to achieve nonlinear system speed tracking control, numerically not complex, and easily applicable to real-time control of PMSM drives. This new adaptive approach for sensorless control of PMSM drives is demonstrated through an illustrative simulation for the proof of concept.

关键词： Programmable control Adaptive control Velocity control Sensorless control Riccati equations Nonlinear control systems control systems Permanent magnet motors Magnetic sensors Nonlinear equations

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Nonlinear Quadratic Optimal control for Cascaded Multilevel Static Compensators

Nonlinear Quadratic Optimal Control for Cascaded Multilevel ...

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Annual North-American Power Symposium

作者： Tansel Yucelen Peda V. Medagam Farzad Pourboghrat Embedded Control Systems Laboratory Department of Electrical and Computer Engineering Southem Illinois University Carbondale Carbondale IL USA Department of Electrical and Computer Engineering Southem Illinois University Carbondale Carbondale IL USA

This paper presents a novel nonlinear quadratic optimal control technique for multiple-input, multiple-output (MIMO) cascaded multilevel static compensators (STATCOM), based on state-dependent Riccati equation (SDRE) technique. The proposed approach is applied online, using a gradient-type neural network algorithm for the computation of SDRE based nonlinear control. The algorithm is fast, computationally simple, and independent of initial conditions. This new control strategy is applied, in a detailed simulation, to the average d-q model of STATCOM to track a desired DC voltage and a reactive current, that demonstrates a relatively fast control ability and good dynamic performance.

关键词： Optimal control STATCOM Automatic voltage control Riccati equations Voltage control MIMO Nonlinear equations Neural networks computer networks Computational modeling

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A Study On Iterative Learning control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup-Norm

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Asian Journal of control 2008年第1期4卷

作者： Kwang-Hyun Park Zeungnam Bien Division of EE Department of EECS Korea Advanced Institute of Science and Technology 373–1 Kusong-dong Yusong-gu Taejon 305–701 Korea. Zeungname Bien:received the B.S. degree in electronics engineering from Seoul National University Seoul Korea in 1969 and the M.S. and Ph.D. degrees in electrical engineering from the University of Iowa Iowa City Iowa U.S.A. in 1972 and 1975 respectively. During 1976–1977 academic years he taught as assistant professor at the Department of Electrical Engineering University of Iowa. Then Dr. Bien joined Korea Advanced Institute of Science and Technology summer 1977 and is now Professor of Control Engineering at the Department of Electrical Engineering and Computer Science KAIST. Dr. Bien was the president of the Korea Fuzzy Logic and Intelligent Systems Society during 1990–1995 and also the general chair of IFSA World Congress 1993 and for FUZZ-IEEE99 respectively. He is currently co-Editor-in-Chief for International Journal of Fuzzy Systems (IJFS) Associate Editor for IEEE Transactions on Fuzzy Systems and a regional editor for the International Journal of Intelligent Automation and Soft Computing. He has been serving as Vice President for IFSA since 1997 and is now Chief Chairman of Institute of Electronics Engineers of Korea and Director of Humanfriendly Welfare Robot System Research Center. His current research interests include intelligent control methods with emphasis on fuzzy logic systems service robotics and rehabilitation engineering and large-scale industrial control systems. Kwang-Hyun Park:received the B.S. M.S. and Ph.D. degrees in electrical engineering and computer science from KAIST Korea in 1994 19997 and 2001 respectively. He is now a researcher at Human-friendly Welfare Robot System Research Center. His research interests include learning control machine learning human-friendly interfaces and service robotics.

It has been found that some huge overshoot in the sense of sup-norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ-norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup-norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.

关键词： Iterative learning control monotone convergence learning interval sup-norm

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MODELING AND control OF ELEVATORS BY STATECHARTS

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Asian Journal of control 2008年第2期6卷

作者： Yi-Sheng Huang Sheng-Luen Chung Mu-Der Jeng Department of Aeronautical Engineering Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit

Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.

关键词： Statechart interactive systems elevator

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Online H∞ speed control of sensorless induction motors with rotor resistance estimation

Online H∞ speed control of sensorless induction motors with...

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International Conference on Power Electronics and Drive systems (PEDS)

作者： Peda V Medagam Farzad Pourboghrat Embedded Control Systems Laboratory Southem Illinois University Carbondale USA Electrical & Computer Engineering Department Southem Illinois University Carbondale USA

This paper proposes an online technique for the H ∞ control of speed and flux norm of current-fed induction motors (IM). Integrals of the speed and flux norm tracking errors are considered as elements of the state variables. A robust H ∞ , optimal control strategy for this problem is determined by solving the algebraic Riccati equation (ARE), using multilayer recurrent neural networks. The proposed controller allows for the simultaneous and independent control of both speed and flux norms of the induction motors. The control implementation involves estimating the rotor flux, rotor resistance, and speed of the induction motor, using continuous-time extended Kalman filter (EKF). The simulation results show the effectiveness of the proposed controller even in the presence of rotor resistance and load torque disturbances.

关键词： Induction motors Rotors Sliding mode control Sensorless control Optimal control Robust control Riccati equations Torque control Stators control systems

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control design for unmanned sea surface vehicles: hardware-in-the-loop simulator and experimental results

Control design for unmanned sea surface vehicles: hardware-i...

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2007 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： P. Krishnamurthy F. Khorrami T. L. Ng IntelliTech Microsystems Inc. Bowie MD USA Control/Robotics Research Laboratory CRRL Department of Electrical and Computer Engineering Polytechnic University Brooklyn NY USA

We address the control design problem for stabilization and tracking of unmanned sea surface vehicles (USSVs). To this end, we describe the design and implementation of a high-accuracy real-time six degree-of-freedom (DOF) hardware-in-the-loop (HITL) simulation platform for use in development and evaluation of controllers for USSVs. The HITL platform incorporates a nonlinear dynamic model of the USSV, emulation of sensors and instrumentation onboard the USSV, and the actual hardware and software components used for control of the USSV in the experimental testbed. Detailed models of hydrodynamic effects, actuators including thrusters/propellers and control surfaces, and disturbances including ocean currents, waves, and wind are included in the dynamic simulation. The fidelity of the developed HITL simulator is demonstrated through comparisons with experimental data collected from a USSV. We also propose a nonlinear backstepping-based controller for stabilization and tracking for USSVs and present closed-loop results from HITL simulation and experimental testing.

关键词： control design Sea surface Vehicle dynamics Emulation Instruments Hardware Software testing Hydrodynamics Actuators Propellers

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Global Output-Feedback Stabilization for a Class of Stochastic Non-Minimum-Phase Nonlinear systems

Global Output-Feedback Stabilization for a Class of Stochast...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Shu-Jun Liu Zhong-Ping Jiang Ji-Feng Zhang Laboratory of Systems and Control Academy of Mathematics and Systems Science슠Chinese Academy of Sciences China Department of Electrical and Computer Engineering Polytechnic University Brooklyn NY USA Laboratory of Systems and Control Academy of Mathematics and Chinese Academy of Sciences China

In this paper, the output-feedback stabilization problem is investigated for the first time for a class of stochastic nonlinear systems whose zero dynamics may be unstable. Under the assumption that the inverse dynamics of the system is stochastic input-to-state stabilizable, a stabilizing output-feedback controller is constructively designed by the integrator backstepping method together with a new reduced-order observer design and the technique of changing supply functions. It is shown that, under small-gain type conditions, the resulting closed-loop system is globally asymptotically stable in the probabilistic sense. The obtained results extend the existing methodology from deterministic systems to stochastic systems.

关键词： Stochastic systems Nonlinear systems control systems Nonlinear control systems Backstepping Nonlinear dynamical systems Mathematics control theory Linear systems Programmable control

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Level-triggered control of a scalar linear system

Level-triggered control of a scalar linear system

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Mediterranean Conference on control and Automation (MED)

作者： Maben Rabi John S. Baras Automatic Control Laboratory School of Electrical Engineering Royal Institute of Technology Stockholm Sweden Institute for Systems Research and Department of Electrical and Computer Engineering University of Maryland College Park MD USA

In networked control systems, because of limits on communication rates, control waveforms are frequently piece-wise constant with limits on rates at which they can switch levels. It is, therefore, natural to expect event-triggered control switchings to perform more efficiently than time-triggered ones. This article verifies the validity of this supposition. A method for designing good level-triggered control schemes is obtained by reducing the continuous time problem to one in discrete time. Then, by numerical procedures, the performance of the level-triggered scheme is computed for comparison with that of the periodically switched control scheme.

关键词： control systems Linear systems Communication system control Automatic control Switches Communication switching Signal sampling Signal processing Laboratories Educational institutions

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LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR control

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Asian Journal of control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

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