Extremum seeking predictive control of LTI systems based on numerical optimization

In this paper, we proposed a new extremum seeking predictive control scheme, in which a numerical optimization algorithm is first employed to provide a search sequence of the unknown extremum, then a predictive controller using the search sequence as its terminal constrain is designed and implemented in a receding horizon manner to simultaneously achieve the optimization of economic objective and transient performance. It is shown that the scheme is able to drive the system states to unknown desired states that optimize the value of an objective function with much better transient performance and is expected to be more robust to external disturbance due to its receding horizon closed-loop control property.