Input-Shaping with GA-Tuned PID for Target Tracking and Vibration Reduction

This paper presents an investigation into the development of an augmented control scheme for vibration suppression and rigid body motion of a twin rotor multi-input multi-output system (TRMS) in hovering mode. The augmented control scheme comprises feedforward and feedback control methods. A 4-impulse input shaper is used as a feedforward control method to pre-process the command signal applied to the system, based on the identified modes of vibration. Two closed loop compensators based on PID and PID with acceleration feedback (PIDA) are designed and used as feedback controllers. Genetic algorithm (GA) optimization is also used in this work to tune the parameters of feedback compensators. A multi objective function is formulated within the augmented control scheme to improve the system's time domain response. Simulation results of the response of the TRMS with the controllers are presented in time and frequency domains. The performance of the proposed control scheme is assessed in terms of input tracking and level of vibration reduction. This is accomplished by comparing the system response to open loop system performance without the feedforward components (i.e. open loop system response to the unshaped input). The approach has shown to result in satisfactory vibration reduction. The GA-tuned controllers have shown a significant improvement in time domain specifications

[1]  M. O. Tokhi,et al.  Vibration control of pitch movement using command shaping techniques , 2003, EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696).

[2]  M. O. Tokhi,et al.  Modelling and Open-Loop Control of a Single-Link Flexible Manipulator with Genetic Algorithms , 2001 .

[3]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[4]  William A. Sethares,et al.  Nonlinear parameter estimation via the genetic algorithm , 1994, IEEE Trans. Signal Process..

[5]  Warren P. Seering,et al.  Preshaping Command Inputs to Reduce System Vibration , 1990 .

[6]  M. O. Tokhi,et al.  Dynamic modelling and open-loop control of a twin rotor multi-input multi-output system , 2002 .

[7]  Warren P. Seering,et al.  Inhibiting Multiple Mode Vibration in Controlled Flexible Systems , 1991, 1991 American Control Conference.

[8]  M. O. Tokhi,et al.  GENETIC MODELLING AND VIBRATION CONTROL OF A TWIN ROTOR SYSTEM , 2004 .

[9]  Z Mohamed,et al.  Vibration control of a single-link flexible manipulator using command shaping techniques , 2002 .

[10]  Warren P. Seering,et al.  Figure 1: Input Shaping by Convolving Desired Input with an Impulse Sequence. Comparison of Command Shaping Methods for Reducing Residual Vibration , 1995 .

[11]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[12]  François Kubica,et al.  Robust Autopilot Design for a Highly Flexible Aircraft , 1996 .

[13]  Peter J. Fleming,et al.  Parallel Genetic Algorithms: A Survey , 1994 .