A model predictive controller based on a novel structure selection criterion for the vapor compression cycle(VCC) of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed which exert significant influences on the system performance. Then the structure selection criterion, a trade-off between computation complexity and model performance, is applied to different model structures, and the results are utilized to determine the optimized model structure for controller design. The controller based on multivariable model predictive control(MPC) strategy is designed, and the optimization problem for the reduced order models is formulated as a constrained minimization problem. The effectiveness of the proposed MPC controller is verified on the experimental rig.
We investigate the trajectory tracking problem of vertical take-off and landing(VTOL) unmanned aerial vehicles(UAV), and propose a practical disturbance rejection control strategy. Firstly, the nonlinear error model is established completely by the modified Rodrigues parameters, while considering dynamics of the servo actuators. Then, a hierarchical control scheme is applied to design the translational and rotational controllers based on the time-scale property of each subsystem,respectively. And the linear extended state observer and auxiliary observer are used to deal with the uncertainties and saturation.At last, global stability of the closed-loop system is analyzed based on the singular perturbation theory. Simulation results show the effectiveness of the proposed control strategy.
