Robust and simple adaptive control systems

Abstract

Robust and simple adaptive control systems Z. IW AIt and 1. MIZUMOTOt This paper deals with two problems for the improvement of the control performance of simple adaptive control (SAC) techniques. First, it is discussed that the introduction of a robust adaptive control term much robustifies the SAC system concerning plant uncertainties such as state dependent disturbance. Second, a practical procedure is described for designing the parallel feedforward compensator, which is necessary for the actual realization of the SAC system, given prior information concerning the plant such that: (I) the plant is minimum phase; (2) an upper bound on the relative degree exists; and (3) approximate values of high and low frequency gains are known. The effectiveness of the proposed methods is confirmed through the simulation of typical examples of adaptive control systems.

An Adaptive Dynamic Controller for Output Control of a System

“…The initial problem is reduced to a well-known problem [13], viz., stabilization of the generalized adjusted system (6). Obviously, if x p (t) → 0 as t → ∞, then the aim condition (2) is satisfied.…”

“…Only after the determination of this system, algorithms can be designed for tuning the parameters of the control device. Different methods, for example, the extended error method [1][2][3], high-order algorithms [4,5], bypassing methods [6,7], etc., have been designed for solving this problem. Detailed analysis and bibliography on different control system designs are given in [8][9][10].…”

Parallel Feedforward Model for Improving Estimates of Unknown Disturbances to Non-Minimum-Phase Systems

“…Theorem 1 [11] If an SISO transfer function, G(s), is SPR, then G(s) is stable and has minimum phase.…”

Simple Adaptive Control for MIMO Nonlinear Continuous-Time Systems Using Neural Networks

“…If the plant parameters are known and Assumptions 1 and 2 are satisfied, then we can construct the optimal control which satisfies the perfect output following condition (4) …”

“…For linear plants with unknown structures, SAC is an important class of adaptive control scheme (3) (4) . However, for nonlinear plants with unknown structures, it may not be possible to ensure perfect plant output that follows the output of a reference model by using conventional SAC (5) .…”