Security-based dynamic output-feedback model predictive control for nonlinear systems in T-S fuzzy form subject to deception attacks

Abstract

This paper is concerned with the security-based fuzzy model predictive control (FMPC) problem for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems with deception attacks on the measured outputs. With respect to the unmeasurable system states, the nonlinearity of the system and the destructiveness of deception attacks, the dynamic output-feedback control in the framework of FMPC is adopted, meanwhile, the worst-case optimization problem over the infinite moving horizon is formulated for the performance analysis and control synthesis. By means of the quadratic function approach and the singular value decomposition technique, the non-convexity caused by couplings between decisive variables is coped with and conditions are derived to suffice the terminal constraint set. In addition, to mitigate the destruction of attacks to the recursive feasibility, the inequality analysis technique is applied with the aid of the introduction of special scalars. Based on the establishments, a certain auxiliary optimization problem with solvability is put forward to find the desired controllers, and sufficient conditions are obtained to guarantee that the underlying system subject to deception attacks under the proposed FMPC-based controllers is mean square secure in H2-sense. Finally, an illustrative example is used to demonstrate the validity of the proposed methods.