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Based on a sliding mode control, a multi-area decentralised load frequency control power system with time-varying delays and non-linear perturbations is designed in this study. Due to the destabilising effect of delay on the global system, it is necessary to design a control system to accommodate vast time delays so as to manage the deviation in frequency and interchange power. By taking advantage of the system structure and disturbance bounds, robustness is improved. A sliding surface is designed, and the stability of the corresponding sliding motion is analysed based on Lyapunov–Razumikhin function. A delay dependent decentralised sliding mode control is synthesised to drive the system to the sliding surface and maintain a sliding motion afterwards. The obtained results are applied to a two-area interconnected power system to demonstrate the effectiveness of the proposed method.

This work focuses on modelling and fault tolerant algorithm design of a damaged near space vehicle. A novel radial basis function (RBF) neural network backstepping fault-tolerant control methodology is developed for attitude control system with damage, which can make system stable and accurately track the desired signals in the presence of vertical tail loss. First, the changing aerodynamic parameters caused by vertical tail loss are used to model damaged attitude dynamics. Second, in view of the established damaged model, a nominal backstepping controller is designed. Then a RBF neural network technology is designed to update the related parameters, which can compensate effects caused by damage and make the system still stable and track the desired signals. Finally, simulation results are provided to show the effectiveness of the proposed RBF neural network backstepping fault-tolerant control scheme.

This paper deals with the design of robust fault detection for networked control systems with large transfer delays, in which it is impossible to totally decouple the fault effects from unknown inputs (including model uncertainties and external plant disturbances). First, we employ the multirate sampling method together with the augmented state matrix method to model the long random delay networked control systems as Markovian jump systems. Then, a Hinfin fault detection filter is designed based on the model developed. Through the appropriate choice of the filter gain, the filter is convergent if there is no disturbance in the system, meanwhile the effect of disturbances on the residual will satisfy a prescribed Hinfin performance. The problem of achieving satisfactory sensitivity of the residual to fault is formulated and its solution is given. Finally, a numerical example is presented to illustrate the effectiveness of the proposed techniques.