Decentralized observer‐based controller design for large‐scale systems with quantized measurements and actuator faults

This paper is focused on designing observer‐based decentralized memory feedback controller for ensuring the asymptotic mean square stability of the large‐scale systems with minimum H∞ performance index. Precisely, the unknown interconnection between each subsystems of a large‐scale system is assumed to satisfy quadratic bounds, and measured output is quantized by a logarithmic quantizer. Also, the signals are transmitted through the actuator component wherein the occurrence of fault is indispensable. Thus, the impact of faults in actuator is considered in control design to tolerate the fault effects and also for ensuring robust performance. A state space representation of the system is formulated to reconstruct the unmeasurable states via the available informations of input/output dynamics. Based on the designed observer, a decentralized memory feedback controller is developed. Specifically, in terms of linear matrix inequalities, the stability conditions are derived and which are sufficient to guarantee the desired result. At last, simulations are carried out for two numerical examples to validate the potential of the theoretical result.