Adaptive Fuzzy Identification and Control for a Class of Nonlinear Pure-Feedback MIMO Systems With Unknown Dead Zones

• Published in: IEEE transactions on fuzzy systems 2015-10, Vol.23 (5), p.1387-1398
• Main Authors: Liu, Yan-Jun, Tong, Shaocheng
• Format: Article
• Language: English
• Subjects: Adaptive control systems; adaptive fuzzy control; Adaptive systems; Approximation methods; Backstepping; Control systems; Controllers; dead-zone inputs; Fuzzy; Fuzzy control; Fuzzy logic; Fuzzy logic systems; Fuzzy set theory; MIMO; Nonlinear systems; Nonlinearity; Observers; the tracking control; Theorems; uncertain nonlinear systems
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2014.2360954

The adaptive fuzzy identification and control problems are considered for a class of multi-input multi-output nonlinear systems with unknown functions and unknown dead-zone inputs. The main characteristics of the considered systems are that 1) they are composed of n subsystems and each subsystem is in nested lower triangular form, 2) dead-zone inputs are in nonsymmetric nonlinear form, and 3) dead-zone inputs appear nonlinearly in the systems and their parameters are not required to be known. The controller design for this class of systems is a difficult and complicated task because of the existences of unknown functions, the couplings among the nested subsystems, and the dead-zone inputs. In the controller design, the fuzzy logic systems are employed to approximate the unknown functions and the differential mean value theorem is used to separate dead-zone inputs. To compensate for dead-zone inputs, the compensative terms are designed in the controllers. The stability of the closed-loop system is proved via the Lyapunov stability theorem. A simulation example is provided to validate the feasibility of the approach.