Data-Driven Optimal Control of Linear Discrete Systems With Sensor Fault via a Performance Triggering Approach

This article is devoted to data-driven optimal control of linear discrete systems with sensor fault via a performance triggering approach. A quadratic inequality is introduced to equivalently describe systems subject to a fault. A barrier function is provided by the input and output to treat the gain constraint. An optimal control law is built on the adaptive dynamic programming (ADP) method to improve control performance. A dynamic triggering mechanism is constructed by instantaneous data and performance index to balance triggering frequency and control performance, especially under an emergent situation. Sufficient conditions are supplied to ensure the ultimately uniform boundedness of the closed-loop systems. An illustrative example is presented to verify the validity of the proposed strategy.