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Gain Matrices (gain + matrix)
Selected AbstractsConvergence theory for multi-input discrete-time iterative learning control with Coulomb friction, continuous outputs, and input boundsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2004Brian J. Driessen Abstract In this paper we consider the problem of discrete-time iterative learning control (ILC) for position trajectory tracking of multiple-input, multiple-output systems with Coulomb friction, bounds on the inputs, and equal static and sliding coefficients of friction. We present an ILC controller and a proof of convergence to zero tracking error, provided the associated learning gain matrices are scalar-scaled with a sufficiently small positive scalar. We also show that non-diagonal learning gain matrices satisfying the same prescribed conditions do not lead to the same convergence property. To the best of our knowledge, for problems with Coulomb friction, this paper represents a first convergence theory for the discrete-time ILC problem with multiple-bounded-inputs and multiple-outputs; previous work presented theory only for the single-input, single-output problem. Copyright © 2004 John Wiley & Sons, Ltd. [source] Robustness improvement of a nonlinear H, controller for robot manipulators via saturation functionsJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 8 2005Manuel G. Ortega In this paper, previous works on nonlinear H, control for robot manipulators are extended. In particular, integral terms are considered to cope with persistent disturbances, such as constant load at the end-effector. The extended controller may be understood as a computed-torque control with an external PID, whose gain matrices vary with the position and velocity of the robot joints. In addition, in order to increase the controller robustness, an extension of the algorithms with saturation functions has been carried out. This extension deals with the resulting nonlinear equation of the closed-loop error. A modified expression for the required increment in the control signal is provided, and the local closed-loop stability of this approach is discussed. Finally, simulation results for a two-link robot and experimental results for an industrial robot are presented. The results obtained with this technique have been compared with those attained with the original controllers to show the improvements achieved by means of the proposed method. © 2005 Wiley Periodicals, Inc. [source] Identification based adaptive iterative learning controllerASIAN JOURNAL OF CONTROL, Issue 5 2010Suhail Ashraf Abstract In recent years, more research in the control field has been in the area of self-learning and adaptable systems, such as a robot that can teach itself to improve its performance. One of the more promising algorithms for self-learning control systems is Iterative Learning Control (ILC), which is an algorithm capable of tracking a desired trajectory within a specified error limit. Conventional ILC algorithms have the problem of relatively slow convergence rate and adaptability. This paper suggests a novel approach by combining system identification techniques with the proposed ILC approach to overcome the aforementioned problems. The ensuing design procedure is explained and results are accrued from a number of simulation examples. A key point in the proposed scheme is the computation of gain matrices using the steepest descent approach. It has been found that the learning rule can be guaranteed to converge if certain conditions are satisfied. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] ESA in high-order linear systems via output feedback,ASIAN JOURNAL OF CONTROL, Issue 3 2009Hai-Hua Yu Abstract This paper considers eigenstructure assignment in high-order linear systems via output feedback. Parametric expressions for the left and right closed-loop eigenvectors associated with the finite closed-loop eigenvalues and two simple and complete parametric solutions for the feedback gain matrices are obtained on the basis of the parametric solutions of the generalized high-order Sylvester matrix equations. This approach does not impose any restrictions on the closed-loop eigenvalues. An illustrative example shows the effect of the proposed approach. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] ROBUST CONTROL FOR A CLASS OF UNCERTAIN STATE-DELAYED SINGULARLY PERTURBED SYSTEMSASIAN JOURNAL OF CONTROL, Issue 2 2005H.R. Karimi ABSTRACT This paper considers the problem of robust control for a class of uncertain state-delayed singularly perturbed systems with norm-bounded nonlinear uncertainties. The system under consideration involves state time-delay and norm-bounded nonlinear uncertainties in the slow state variable. It is shown that the state feedback gain matrices can be determined to guarantee the stability of the closed-loop system for all , , (0, ,00) and independently of the time-delay. Based on this key result and some standard Riccati inequality approaches for robust control of singularly perturbed systems, a constructive design procedure is developed. We present an illustrative example to demonstrate the applicability of the proposed design approach. [source] On-line identification of non-linear hysteretic structural systems using a variable trace approachEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 9 2001Jeng-Wen Lin Abstract In this paper, an adaptive on-line parametric identification algorithm based on the variable trace approach is presented for the identification of non-linear hysteretic structures. At each time step, this recursive least-square-based algorithm upgrades the diagonal elements of the adaptation gain matrix by comparing the values of estimated parameters between two consecutive time steps. Such an approach will enforce a smooth convergence of the parameter values, a fast tracking of the parameter changes and will remain adaptive as time progresses. The effectiveness and efficiency of the proposed algorithm is shown by considering the effects of excitation amplitude, of the measurement units, of larger sampling time interval and of measurement noise. The cases of exact-, under-, over-parameterization of the structural model have been analysed. The proposed algorithm is also quite effective in identifying time-varying structural parameters to simulate cumulative damage in structural systems. Copyright © 2001 John Wiley & Sons, Ltd. [source] | ||||||||||