PSO Based PID Controller Design for a Precise Tracking of Two-Axis Piezoelectric Micro positioning Stage

In this paper the design of an optimal PID controller for single and double axis piezoelectric micropositioning stage system is presented. The Particle Swarm Optimization (PSO) method is used to tune the parameters of the PID controller subject to specific objective function. The proposed controller provides a high performance trajectory tracking responses of the piezoelectric micropositioner stage.A simulation results are presented to show the effectiveness of the proposed control algorithm

Optimal Quantitative Controller Design for Twin Rotor MIMO System

In this paper, the control approach is used for achieving the desired performance and stability of the twin-rotor MIMO system. This system is considered one of the complex multiple inputs of multiple-output systems. The complexity because of the high nonlinearity, significant cross-coupling and parameter uncertainty makes the control of such systems is a very challenging task. The dynamic of the Twin Rotor MIMO System (TRMS) is the same as that in helicopters in many aspects. The Quantitative Feedback Theory (QFT) controller is added to the control to enhance the control algorithm and to satisfy a more desirable performance. QFT is one of the frequency domain techniques that is used to achieve a desirable robust control in presence of system parameters variation. Therefore, a combination between control and QFT is presented in this paper to give a new efficient control algorithm. On the other hand, to obtain the optimal values of the controller parameters, Particle Swarm Optimization (PSO) which is one of the powerful optimization methods is used. The results show that the proposed quantitative control can achieve more desirable performance in comparison to control especially in attenuating the cross-coupling and eliminating the steady-state error