Adaptive fuzzy control of MIMO nonlinear systems

Designing MIMO controller by neuro-traveling particle swarm optimizer approach

“…Yi, Sheng, and Xu (2003) proposed two artificial neural networks, which are to be used in the predictive model and control model, but are only limited to use in multiple input-single output system. There are other controllers based on the fuzzy model being used in the MIMO system (Lian & Huang, 2001;Zhang & Bien, 2000). The ultimate goal of these approaches is to construct an efficient controller.…”

Fuzzy adaptive output feedback control for MIMO nonlinear systems

“…The main property of the fuzzy adaptive control scheme is summarized in the following theorem: (18) and (19). If Assumptions 2 and 3 are satisfied, andĜ(x| 2 ) is a definite matrix, then the proposed fuzzy control scheme can guarantee the following properties:…”

“…By the parameter adaptive law (18) and (19), and because e T P 2 Bu a = e T P 2 BK T 0 P 1ê =ê T P 1 K 0 C T e, then (24) can be formulated aṡ…”

“…Based on the universal approximation theorem [17], many stable fuzzy adaptive control schemes have been developed for unknown single-input-single-output (SISO) nonlinear systems [17,16,2,12,11,13], and multiple-input-multiple-output (MIMO) nonlinear systems [7,14,19,1], and achieve stable performance criteria. However, these adaptive fuzzy control methods are limited only to systems whose states are assumed to be available for measurements; thus, they are called fuzzy adaptive state feedback control.…”

A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems

“…Substituting (11) and (19) • If a positive-definite does not exist for (19), then (17) ( , , ) can be converted to the strictly positive-real (SPR) system by using the same way as in [21]. The details are as follows.…”