Implementation of self-tuning controllers by Kevin Warwick
By Kevin Warwick
Recursive estimation schemes for self-tuning regulate. LOG dependent self-tuning controllers. Simplified self-tuning regulate algorithms. Implementation of continuous-time controllers. Numerical difficulties in adaptive keep an eye on. Self-tuning keep watch over utilizing prolonged prediction horizons. software program features of self-tuning keep an eye on. program of lengthy diversity predictive keep an eye on. Self adaptive nation variable suggestions keep watch over with program to glasshouse structures. Self-tuning keep watch over - a case research. LQG adaptive autopilots
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The condition required for optimality of the implied reference equation is that A&, the reference generator denominator, must divide the plant input-output transfer-function W . 2). 3 we can ensure that the problem i£ solvable) then the implied reference diophantine equation will uniquely determine the optimal reference controller. The conditions required for optimality of the feedforward diophantine equation are that A and B must be coprime and that A«, the measurable disturbance generator denominator, must divide both A and D.
J. 1 INTRODUCTION There are several approaches to the design of control systems using stochastic optimal control theory (fLQGf control). The method followed in this chapter is the polynomial equation approach developed by Ku£era (1979) in which the design procedure reduces to the solution of polynomial equations. These equations can be solved using fast and efficient numerical algorithms. The polynomial approach to LQG control offers a flexible design method which can be readily used as the basis of a self-tuning control algorithm.
Landau (1986). Practical implications of recent results in robustness of adaptive control schemes. 1986 CDC Proc, Athens, Greece, 477-481 and private communication (1987). (16) Noble, B. (1969). Prentice Hall. Applied Linear algebra. , L. D. Landau (1985). Robustness of discrete-time adaptive controllers, IEEE Trans, of Auto. Control, 30, 1179-1187. L. (1950). Some theorems in Least Squares, ometrika, Vol. 37, p. 149. (19) Praly, L. (1983) Robustness of Model reference adaptive control. Proc. of 3rd Yale Workshop on Adaptive Control, New Haven, CT.