Contrained nonliner model predictive control of hybrid dymnamic system

Abstract EN

In this paper, a nonlinear model predictive control law of hybrid dynamic system is presented.

An optimal switching strategy is obtained by an exhaustive search.

It is shown that the online optimization of a non convex optimal control problem is not required.

In fact, by using a Taylor series expansion of the output tracking error, the solution of the optimal control law can arise from a convex quadratic programming problem which incorporates rigorously inputs constraints.

The main feature of the proposed method is its ability to reduce computational burden as it can be efficiently solved online.

The controller performances are validated on hydrographic process for which the levels of their two bottom tanks are accurately tracked to prescribed references trajectories.