Adaptive and Learning Systems: Theory and ApplicationsKumpati S. Narendra This volume offers a glimpse of the status of research in adaptive and learning systems in 1985. In recent years these areas have spawned a multiplicity of ideas so rapidly that the average research worker or practicing engineer is overwhelmed by the flood of information. The Yale Workshop on Applications of Adaptive Systems Theory was organized in 1979 to provide a brief respite from this deluge, wherein critical issues may be examined in a calm and collegial environment. The fourth of the series having been held in May 1985, it has now become well established as a biennial forum for the lively exchange of ideas in the ever changing domain of adaptive systems. The scope of this book is broad and ranges from theoretical investigations to practical applications. It includes twenty eight papers by leaders in the field, selected from the Pro ceedings of the Fourth Yale Workshop and divided into five sections. I have provided a brief introduction to each section so that it can be read as a self-contained unit. The first section, devoted to adaptive control theory, suggests the intensity of activity in the field and reveals signs of convergence towards some common themes by workers with rather different moti vation. Preliminary results concerning the reduced order model problem are dramatically changing the way we view the field and bringing it closer to other areas such as robust linear control where major advances have been recently reported. |
Contents
ADAPTIVE CONTROL THEORY | 1 |
Methods of Averaging for Adaptive Systems | 33 |
A Robust Indirect Adaptive Control Approach | 47 |
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action actuator adaptive control adaptive law adaptive system application approach AR-P assumption asymptotic asymptotically stable automaton behavior bounded disturbances boundedness classifier closed loop Computer constant control design control law control problem control system control theory convergence coordinate data compression dead zone defined dynamic parameters dynamic robot model end-effector environment exponentially feedback Figure finite follows frequency genetic algorithm global Hence identification IEEE IEEE Trans inverse dynamics joint K.S. Narendra kinematic Lagrange-Euler lattice filter learning automata Lemma linear Lyapunov equation M-line manipulator Markov chain matrix method modal mode shapes Model Reference Adaptive modes mover's problem Newton-Euler nonlinear obstacle obtained operator optimal output parameter estimates parameter vector performance persistent excitation PID controller positive real Praly Proc recursive Reference Adaptive Control shown signals simulation solution space stability Stochastic structure Theorem theory torque/force transfer function Wm(s wwww zero
