Adaptive Fuzzy Security Constraint Control for Interconnected Nonlinear Systems With Deception Data Injection Attacks

In this article, an adaptive security-constrained tracking control technique is developed for interconnected nonlinear systems subjected to deception data injection attacks and dead-zone inputs. To avoid the constraint control system from crashing in the event of being attacked, a security constraint function with switchable constraints has been developed to enable the control system to pass through the attack phase securely. An adaptive compensation strategy was designed to reduce the influence of the control system from the impact of the dynamics of the error conversion design process and attacks. Compound uncertain dynamics consisting of unknown interconnection dynamics and system dynamics are accurately estimated by the designed adaptive fuzzy logic estimation law. In addition, the dead-zone input gain parameter estimation law and the control input event triggering mechanism are designed to reduce the impact of dead-zone inputs on the control system and save the communication resources of the input channels. The stability analysis of the proposed control framework is carried out, and it is proved that all signals are ultimately bounded. Compared with the traditional control strategy, the designed control strategy does not require assumptions about the interconnection dynamics and can easily switch the constraints
on
and
off
. Crucially, the designed control scheme was successfully implemented in an actual experimental setup, and its effectiveness and superiority were verified.