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American control Conference (ACC)

作者： P. Krishnamurthy F. Khorrami Control/Robotics Research Laboratory(CRRL) Department of Electrical and Computer Engineering Six Metrotech Center Polytechnic University Brooklyn NY USA

In a result by P. Krishnamurthy and F. Khorrami (2004), we proposed a dynamic high-gain observer/controller architecture for nonlinear systems of the generalized output-feedback canonical form. The design of P. Krishnamurthy and F. Khorrami (2004) utilized the dual architecture of a high-gain observer and controller and incorporated a single dynamic scaling. The designed output-feedback controller was shown to be robust to functional and parametric uncertainties coupled with all states. However, a magnitude bound on the unknown parameters was required. In this paper, we propose a time-varying output-feedback controller that can handle time-varying nonlinear parametric uncertainty coupled with all states without requiring any a priori magnitude bounds on the unknown parameters. This is achieved using a novel time-varying dynamics of the high-gain scaling parameter. The proposed observer/controller structure provides a globally asymptotically stabilizing output-feedback solution for the benchmark open problem proposed in our earlier work with no magnitude bounds or sign information on the unknown parameter being necessary.

关键词： Nonlinear systems control systems Observers Uncertainty Riccati equations Lyapunov method Nonlinear control systems Robust control Couplings Programmable control

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Self-organized motion in a class of anisotropic swarms: convergence vs oscillation

Self-organized motion in a class of anisotropic swarms: conv...

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American control Conference (ACC)

作者： Tianguang Chu Long Wang Tongwen Chen Center for Systems and Control Department of Mechanics and Engineering ScienceFirst Hospital Peking University Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (纸本)0780390989

We study an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of a reciprocal swarm aggregates and eventually form a cohesive cluster of finite size around the swarm center within finite time. Under mild conditions on attraction and repulsion functions, the swarm is also completely stable, i.e., every motion converges to the equilibrium point set of the system. These results are further extended to a class of nonreciprocal swarms under the detailed balance condition on coupling weights. We also present numerical simulations demonstrating complex oscillatory behavior in general nonreciprocal swarms. These results provide more insight into the effect of the interaction pattern on collective behavior of swarms.

关键词： Anisotropic magnetoresistance Convergence control systems Stability Numerical simulation Multiagent systems Pattern formation Distributed control Motion control Aggregates

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ROBUST ADAPTIVE control OF TRANSVERSE FLUX PERMANENT MAGNET MACHINES USING NEURAL NETWORKS

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IFAC Proceedings Volumes 2005年第1期38卷 169-174页

作者： A Babazadeh H.R. Karimi N Parspour Institute of Electrical Drives Power Electronics and Devices University of Bremen Bremen Germany Control and Intelligent Processing Center of Excellence Dept. of Electrical and Computer Engineering Faculty of Engineering University of Tehran Tehran Iran DAAD Scholarship Holder at the Institute of Automation University of Bremen Germany

This paper deals with modelling and adaptive output tracking of a Transverse Flux Permanent Magnet Machine (TFPM) as a non-linear system with unknown nonlinearities by utilizing High Gain Observer (HGO) and Radial Basis Function (RBF) networks. The technique of feedback linearization and H ∞ control are used to design an adaptive control law for compensating the unknown nonlinearity parts, such the effect of cogging torque, as a disturbance is decreased onto the rotor angle and angular velocity tracking performances. Finally, the capability of the proposed method is shown in the simulation results.

关键词： High gain observer transverse flux permanent magnet machine H ∞ control RBF neural network output tracking

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Fuzzy sliding mode control applied to low noise switched reluctance motor control

Fuzzy sliding mode control applied to low noise switched rel...

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International Conference on control and Automation (ICCA)

作者： H. Rouhani C. Lucas R.M. Milasi M.N. Bahrami Iranian Applied Design Center of Excellence Mechanical Engineering Department University of Tehran Tehran Iran Iranian Control & Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

In this paper, fuzzy sliding mode controller is designed to govern the dynamics of switched reluctance motor. First, magnetic characteristics data of the motor obtained by finite element method (FEM) is utilized for a fuzzy estimation. Next, fuzzy sliding mode control approach has been utilized as a nonlinear robust control algorithm to deal with a highly nonlinear system with an unknown model and a variable load torque. Simulation results show an excellent tackling the problem with an acceptable control effort. Finally, an effective commutation algorithm has been coupled with the proposed controller which can reduce the acoustic noise resources.

关键词： Sliding mode control Fuzzy control Reluctance motors Magnetic noise Nonlinear dynamical systems Finite element methods Fuzzy systems Robust control Nonlinear systems Commutation

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Delay-dependent robust stability and H/sub /spl infin// control for jump linear systems with delays

Delay-dependent robust stability and H/sub /spl infin// cont...

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American control Conference (ACC)

作者： Jing Wu Tongwen Chen Long Wang Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Center for Systems and Control Department of Mechanics and Engineering ScienceFirst Hospital Peking University Beijing China

ISBN: (纸本)0780390989

This paper considers robust stochastic stability, stabilization and H/sub /spl infin// control problems for a class of jump linear systems with time delays. By taking some zero equations, neither model transformation nor bounding for cross terms is required to obtain the delay-dependent results, which are given in terms of linear matrix inequalities (LMIs). Maximum sizes of time delays are also studied for system stability. Furthermore, solvability conditions and corresponding H/sub /spl infin// control laws are given which provide robust stabilization with a prescribed H/sub /spl infin// disturbance attenuation level /spl gamma/. Numerical examples show that our proposed methods are much less conservative than existing results.

关键词： Robust stability control systems Linear systems Delay systems Delay lines Delay effects Equations Stability analysis control system synthesis Robust control

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Evolutionary algorithms for parameter determination of patched conic approximation

Evolutionary algorithms for parameter determination of patch...

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IEEE Conference on Aerospace

作者： B.B.K. Reddy B. Kimiaghalam A. Homaifar NASA Autonomous Control and Information Technology Center Department of Electrical and Computer Engineering North Carolina Agriculture and Technical State University NC USA

The objective of this research is to investigate the utility of micro genetic algorithms (GA) to determine the initial conditions of a spacecraft at the point of departure from Earth's orbit to make a successful lunar landing or a lunar flyby. The states of the spacecraft at the point at the destination are then obtained using the patched-conic approximation. As demonstrated in this work, faster convergence is obtained using micro genetic algorithms. This methodology can also be extended to interplanetary translation by utilizing the intermediate thrust of the spacecraft.

关键词： Evolutionary computation Space vehicles Moon Planets Earth Genetic algorithms Sun NASA Information technology Convergence

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On consistency of stochastic gradient algorithms for ARMAX models with disturbances

On consistency of stochastic gradient algorithms for ARMAX m...

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American control Conference (ACC)

作者： Feng Ding Tongwen Chen Research Associate University of Alberta Edmonton Canada Control Science and Engineering Research Center Southern Yangtze University Wuxi China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (纸本)0780390989

In this paper, we give a new method to prove in detail the consistency of the residual based and innovation based stochastic gradient algorithms for identifying CARMA/ARMAX models with disturbances under weaker conditions on statistical properties of the noise, e.g., the mean value is non-zero, and the variance is time-varying, and/or high-order moments are possibly nonexistent. The analysis indicates that the parameter estimation error is consistently bounded, and consistently converges to zero under persistent excitation conditions.

关键词： Stochastic processes Stochastic resonance Parameter estimation Convergence Adaptive control Differential equations Technological innovation Least squares approximation Algorithm design and analysis Least squares methods

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control design implementation for Sawyer motors used in manufacturing systems

Control design implementation for Sawyer motors used in manu...

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American control Conference (ACC)

作者： P. Krishnamurthy F. Khorrami T.L. Ng I. Cherepinsky Control/Robotics Research Laboratory(CRRL) Department of Electrical and Computer Engineering Six Metrotech Center Polytechnic University Brooklyn NY USA Sikorsky in Stratford CT USA

In this paper, hardware integration and control design for a dual-axis linear stepper (Sawyer) motor are addressed. In particular, the Sawyer motor used in the Yaskawa/MotoMan manufacturing system which is utilized in various applications such as assembly, packaging, sorting, and probing, is considered. These motors are equipped with four optical sensors with a position resolution of 0.25 microns. We develop a detailed model of the motor for control validation and provide a comparison of two control designs, namely, a PD (or PID) and a robust adaptive nonlinear controller. To achieve high performance, a number of practical issues (such as delay/latency, finite sampling time, sensor noise, commutation rate, etc.) need to be considered. Effects of these factors are outlined and experimentally demonstrated. Both the considered controllers utilize knowledge of motor position and velocity in all axes. Current measurements are not required. Either numerical differentiation or a dynamic observer can be used to construct the velocity signals from the measured position data. The designed nonlinear controller provides practical stabilization of position tracking errors and achieves better overall performance. Adaptations are utilized so that no knowledge of the electromechanical system parameters is required. The proposed nonlinear controller is robust to load torques, friction, cogging forces, and other disturbances satisfying certain bounds. Furthermore, the controller corrects for the unintended yaw and achieves synchrony of the motor and rotor teeth. We have also observed that if the rotational motion is not corrected for, the performance is very poor for both controllers. This is also true in the case of delay/latency and higher rates of commutation.

关键词： control design Manufacturing systems Delay Robust control Commutation Hardware Assembly systems Packaging Sorting Micromotors

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A neuro-fuzzy based approach for output tracking of transverse flux machines

A neuro-fuzzy based approach for output tracking of transver...

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IEEE Conference on control Technology and Applications (CCTA)

作者： A. Babazadeh H.R. Karimi B. Moshiri Institute of Electrical Drives Power Electronics and Devices University of Brethemen Bremen Germany Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering Faculty ofEngineering University of Tehran Tehran Iran

This paper describes a design for adaptive control of transverse flux permanent magnet machines as nonlinear systems with unknown nonlinearities by utilizing Takagi-Sugeno-Kang type neuro-fuzzy networks. The technique of feedback linearization and H infin control are used to design the adaptive control law for compensating the unknown nonlinear parts, such the effect of cogging torque, as a disturbance on the rotor angle and angular velocity tracking performances. Finally, the capability of the proposed method is shown by the simulation results

关键词： Adaptive control Permanent magnet machines Nonlinear systems Takagi-Sugeno-Kang model Fuzzy neural networks Neurofeedback Linear feedback control systems Torque control Angular velocity control Forging

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APPROXIMATED OPTIMAL control OF SINGULARLY PERTURBED SYSTEMS VIA HAAR WAVELETS

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IFAC Proceedings Volumes 2005年第1期38卷 353-358页

作者： H.R. Karimi P. Jabedar Maralani B Moshiri B Lohmann Control and Intelligent Processing Center of Excellence Dept. of Electrical and Computer Engineering University of Tehran Tehran Iran Institute of Automation University of Bremen Otto-Hahn-Allee NW1 D-28359 Bremen Germany

This paper deals with the implementation of Haar wavelet to the optimal control of linear singularly perturbed systems. The approximated composite control and the slow and fast trajectories with respect to a quadratic cost function by solving only the linear algebraic equations are calculated. The results are illustrated with a simple example.

关键词： Singularly perturbed systems Haar wavelet and optimal control

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