It has been shown that the closed-loop transfer function representation of the unconstrained model predictive control (MPC) for single input single output systems is similar to a two-degree-of-freedom controller, which is capable of improving the tracking performance of positioning systems. Conventionally, the optimal parameters of the above-mentioned transfer function are result of a quite complicated MPC tuning. This paper proposes a new approach to obtain the parameters directly instead, where the input/output constraints are not considered. The method combines conventional feedback and adaptive feedforward techniques to minimize the tracking error as well as mitigate the influence of the load disturbance. Experiments on an ultra precision positioning system actuated by piezoelectric actuator show that the proposed method achieves much better tracking performance over a well-tuned conventional MPC.
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering