access icon free Adaptive dynamic programming method-based synchronisation control of a class of complex dynamical networks with unknown dynamics and actuator faults

© The Institution of Engineering and Technology
Received 04/08/2017, Accepted 02/11/2017, Revised 16/10/2017, Published 06/11/2017

This study is concerned with the adaptive fault-tolerant synchronisation control problem for a class of complex dynamic networks with unknown internal dynamics and actuator faults. A controller which consists of adaptive fault-tolerant control laws and a static feedback gain is designed to achieve the synchronisation. A modified iterative algorithm via adaptive dynamic programming technique is developed to compute the static feedback gain, and based on which adaptive fault-tolerant control laws are then designed, without requiring the a priori knowledge of the system matrices, to compensate the actuator faults. Furthermore, the asymptotic convergence of synchronisation errors is rigidly analysed by combining graph theory and Lyapunov theory, and all the other signals in synchronised error system are also proved to be bounded. Finally, a simulation example is illustrated to demonstrate the effectiveness of the proposed method.

Inspec keywords: adaptive control; compensation; iterative methods; feedback; graph theory; dynamic programming; fault tolerant control; convergence of numerical methods; control system synthesis; complex networks; synchronisation; Lyapunov methods

Other keywords: adaptive fault-tolerant control laws; graph theory; Lyapunov theory; static feedback gain; modified iterative algorithm; adaptive dynamic programming method-based synchronisation control; adaptive fault-tolerant synchronisation control problem; unknown internal dynamics; synchronisation errors; actuator faults; asymptotic convergence; actuator fault compensation; complex dynamical networks

Subjects: Optimisation techniques; Control system analysis and synthesis methods; Combinatorial mathematics; Interpolation and function approximation (numerical analysis); Self-adjusting control systems; Stability in control theory

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