input constraint

Active vehicle suspension system is designed to increase the ride comfort and road holding of vehicles. Due to limitations in the external force produced by actuator, the design problem encounters the constraint on the control input. In this paper, a novel nonlinear controller with the input constraint is designed for the active suspension system. In the proposed method, at first, a constrained multi-objective optimization problem is defined. In this problem, a performance index is defined as a weighted combination of the predicted responses of the nonlinear suspension system and control input. Then, this problem is solved by the modified firefly optimization algorithm to find the constrained optimal control input. To evaluate the performance of the proposed method, the results of the unconstrained and constrained controllers are provided and discussed for various road excitations. The results show a remarkable increase in the ride comfort with the limited force, while other suspension outputs including the suspension travel and tire deflection being in the acceptable ranges. In addition, these controllers are compared with Sliding Mode Control (SMC) and Nonlinear Model Predictive Control (NMPC) in the presence of model uncertainty.

In this paper, a new constraint predictive PID controller is proposed and simulated for a flight vehicle with too many operating points. In this approach, the PID and the incremental predictive control methods are combined in order to use the benefits and resolve the disadvantages of the both methods. The constrained optimal signal of the new method is calculated by a simple algorithm without need to generate large matrices. Simplicity of the presented controller with small dimensions is the reason for the implementation capability of the method for flight vehicle control system with many operating points. Since the generalized incremental predictive control has high robustness in the presence of the unmodeled uncertainties, the presented predictive based controller covers many operating points. The designed method is implemented for three channels of a flight vehicle and then, successfully tested in the hardware in the loop lab. Simulation results show high robust performance and real time implementation capability.