Model predictive control with integral control and constraint handling for mechatronic systems

In this paper, we present a model predictive control (MPC) method which combines integral control and constraint handling simultaneously. The state observer using pole placement is designed for output feedback control and real-time implementation. By appropriately augmenting the integrator dynamics, the original MPC problem is transformed to a quadratic programming problem with constraints. The proposed MPC controller was applied to a piezo-actuated system and implemented at a 10 kHz sampling rate for step tracking. Several controller design parameters affecting the control performance were analyzed and discussed through the experimental results presented. In particular, the constraint handling results demonstrate the effectiveness and potential of the proposed method for mechatronic systems.