Data-Driven Design of Feedback-Feedforward Control Systems for Dynamic Processes

摘要

This paper presents a new solution for the design of a controller for a process using exclusively input/output (I/O) data, which enables the overall system to exhibit high control performance including tracking performance and system robustness in case of deterministic additive disturbances. First, a data-driven model is constructed based on deadbeat diagnostic observer/residual generator. Next, a new state, which is equivalent to the integral of the system tracking error, combined with process input and output information is used to define the performance criterion. Minimising this performance criterion using an online control policy gives an optimal feedback and feedforward controller. The effectiveness of the proposed approach for industrial implementations is shown using a DC-motor simulation.