Decentralized Model Reference Adaptive Control for Systems With Time Delays and Dead Zones
Zhengqiang Zhang, Chen Yang, Xinkai Chen
Abstract
The decentralized robust model reference adaptive control (MRAC) problem is studied for a class of large-scale systems with unknown plant parameters, unknown time-varying delayed interconnections, and unknown dead-zone inputs. Two robust adaptive control schemes are proposed for the cases of symmetric dead-zone input and asymmetric dead-zone input under the assumption of moderate time-delay nonlinearity and the matching conditions of the plant model and the reference model matrix, respectively. The control gain function is explicitly expressed, and its useful properties are established. The Lyapunov-Krasovskii functional with two integral functions is constructed. It is shown that all signals in the closed-loop system are bounded and the state tracking error converges exponentially to a tunable region. The effectiveness and feasibility of the proposed design approach is illustrated by a simulation example.