Data-Driven Fault-Tolerant Tracking Control for Linear Parameter-Varying Systems

Abstract

This article proposes a data-driven passive fault-tolerant tracking controller for single-input single-output (SISO) discrete-time linear systems with slowly-varying unknown parameters in the presence of actuator faults. Initially, a parameterized controller is considered. Using the internal model principle, the controller structure is determined such that the passive-fault-tolerance and tracking objectives are achieved. The obtained fixed-structure controller is utilized for both normal and faulty conditions without using any feedback from the fault information. Thus, the controller is simple to implement and responds fast to the effects of faults. Then, using a data-driven technique and based on the input/output (I/O) data, the controller parameters are adjusted online to tackle the problem of parameter variation. A data-based constraint on the controller parameters is proposed for ensuring the stability of the closed-loop system. The proposed technique is extended to multi-input multi-output (MIMO) systems using the sequential loop closing concept and the relay auto-tuning method. Simulation results of applying the proposed controller to a direct current (DC) servo motor and a three-tank system demonstrate its effectiveness.INDEX TERMS Data-driven control, fault-tolerant control, internal model principle, linear parametervarying systems, tracking control.

Event-Triggered Adaptive Neural Network Tracking Control with Dynamic Gain and Prespecified Tracking Accuracy for a Class of Pure-Feedback Systems

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Koopman fault‐tolerant model predictive control

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