Observer-based model predictive control for uncertain NCS subject to hybrid attacks via interval type-2 T–S fuzzy model - Wang, Cancan; Geng, Qing; Meng, Aiwen; Liu, Fucai (ISA transactions, 2023)
In this study, an observer-based model predictive control (MPC) algorithm is addressed for an uncertain discrete-time nonlinear networked control system (NCS) subject to hybrid malicious attacks by using interval type-2 Takagi–Sugeno (IT2 T–S) fuzzy theory. Hybrid malicious attacks, including two typical attacks, i.e., denial-of-service (DoS) attacks and false data injection (FDI) attacks, are considered in the communication networks. Under DoS attacks, the control signals will be interfered, which cause the degradation of signal-to-interference-plus-noise ratio, then lead to packets loss. Under FDI attacks, the false signals are injected and output signals are modified so that the system performance is deteriorated. For the NCS subject to hybrid attacks, a secure observer that can resist FDI attacks is devised and a fuzzy MPC algorithm that can solve the controller gains is proposed. Besides, by updating the bound of augmented estimation error, the recursive feasibility can be guaranteed. Finally, illustrative examples are given to show the effectiveness of proposed scheme. •The IT2 T–S fuzzy MPC scheme for NCS subject to uncertainties and hybrid attacks is investigated in this paper.•The uncertainties for the NCS appear not only in the membership functions but in both state and input matrices.•The hybrid attacks (DoS attack and FDI attack) in the communication channels of the NCS are considered.•The probability of packets loss depending on SINR is given and a secure observer is designed to estimate system states and FDI attacks.•By optimizing the performance objective function, an on-line fuzzy MPC algorithm is presented.