Fault-tolerant sampled-data control of flexible spacecraft with probabilistic time delays
- 467 Downloads
In this paper, fault-tolerant sampled-data control for flexible spacecraft in the presence of external disturbances, partial actuator failures and probabilistic time delays is investigated. In particular, unlike the common assumptions on continuous-time information on control input, a more realistic sampled-data communication strategy is proposed with probabilistic occurrence of time-varying delays which is modeled by introducing Bernoulli distributed sequences. The main purpose of this paper is to derive fault-tolerant sampled-data control law which makes the closed-loop system robustly asymptotically stable with a prescribed upper bound of the cost function about its equilibrium point for all possible actuator failures. More precisely, by constructing an appropriate Lyapunov–Krasovskii functional involving the lower and upper bound of the probabilistic time delay, a new set of sufficient conditions are derived in terms of linear matrix inequalities for achieving the required result. Numerical simulations are presented by taking the real parameters to the considered aircraft model, which is not only highlighting the ensured closed-loop performance by the proposed control law, but also illustrates its superior fault tolerance, fast convergence and robustness in the presence of external disturbances and actuator faults when compared with the conventional controller. The simulation result reveals the effectiveness and potential of the proposed new design techniques.
KeywordsFlexible spacecraft Fault-tolerant control Sampled-data system Probabilistic time delays
- 14.Sakthivel, R., Vadivel, P., Mathiyalagan, K., Arunkumar, A.: Fault-distribution dependent reliable \(H_\infty \) control for TS fuzzy systems. J. Dyn. Syst. Meas. Control 136, 021021 (2014)Google Scholar
- 15.Singh, S.N.: Robust nonlinear attitude control of flexible spacecraft. IEEE Trans. Aerosp. Electron. Syst. 23, 380–387 (1987)Google Scholar
- 25.Zhu, Q., Cao, J.: Exponential stability of stochastic neural networks with both Markovian jump parameters and mixed time delays. IEEE Trans. Syst. Man Cybern. B 41(2), 341–353 (2011)Google Scholar