Modelling and control of horizontal flexible plate using particle swarm optimization

This paper presents the modeling and active vibration control using an evolutionary swarm algorithm known as particle swarm optimization. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges as boundary conditions constrained at horizontal position. The purpose of the experimental rig development is to collect the input-output vibration data. Next, the data acquisition and instrumentation system were designed and integrated with the experimental rig. Several procedures were conducted to acquire the input-output vibration data. The collected vibration data were then utilized to develop the system model. The parametric modeling using particle swarm optimization was devised using an auto regressive model with exogenous model structure. The developed model was validated using mean square error, one step ahead prediction, correlation tests and pole-zero diagram stability. Then, the developed model was used for the development of controller using an active vibration control technique. It was found that particle swarm optimization based on the active vibration control using Ziegler-Nichols method has successfully suppressed the unwanted vibration of the horizontal flexible plate system. The developed controller achieved the highest attenuation value at the first mode of vibration which is the dominant mode in the system with 34.37 dB attenuation.

[1]  Mohamed Abdel-Baset,et al.  A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems , 2014 .

[2]  Paolo Gardonio,et al.  Smart panel with multiple decentralized units for the control of sound transmission. Part I: theoretical predictions , 2004 .

[3]  M. O. Tokhi,et al.  PSO-Based Parametric Modelling of a Thin Plate Structure , 2009, 2009 Third UKSim European Symposium on Computer Modeling and Simulation.

[4]  M. O. Tokhi,et al.  Active Vibration Control of Flexible Structures Using Genetic Optimisation , 2006 .

[5]  Intan Zaurah Mat Darus,et al.  Modeling flexible plate structure system with free-free-clamped-clamped (FFCC) edges using Particle Swarm Optimization , 2013, 2013 IEEE Symposium on Computers & Informatics (ISCI).

[6]  M O Tokhi,et al.  Self-Tuning Active Vibration Control in Flexible Beam Structures , 1994 .

[7]  M. O. Tokhi,et al.  SISO and SIMO active vibration control of a flexible plate structure using real-coded genetic algorithm , 2010, 2010 IEEE 9th International Conference on Cyberntic Intelligent Systems.

[8]  Keshav P. Dahal,et al.  Intelligent Learning Algorithms for Active Vibration Control , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[9]  Hishamuddin Jamaluddin,et al.  Effect of penalty function parameter in objective function of system identification , 2013 .

[10]  Intan Z. Mat Darus,et al.  Genetic algorithm-based identification of transfer function parameters for a rectangular flexible plate system , 2010, Eng. Appl. Artif. Intell..

[11]  F. AbRashidM.F.,et al.  Parametric Optimization Of Magneto-Rheological Fluid Damper Using Particle Swarm Optimization , 2015 .

[12]  Intan Zaurah Mat Darus,et al.  Intelligence Swarm Model Optimization of Flexible Plate Structure System , 2013 .

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

[14]  M. Osman Tokhi,et al.  Control of a flexible plate structure using particle swarm optimization , 2009, 2009 IEEE Congress on Evolutionary Computation.

[15]  Paolo Gardonio,et al.  Smart panel with multiple decentralized units for the control of sound transmission. Part III: control system implementation , 2004 .

[16]  Stephen J. Elliott,et al.  Smart panel with multiple decentralized units for the control of sound transmission. Part II: design of the decentralized control units , 2004 .

[17]  Laura Menini,et al.  Active vibration control of an elastic plate using multiple piezoelectric sensors and actuators , 2003, Simul. Model. Pract. Theory.

[18]  Terrence L. Blevins PID Advances in Industrial Control , 2012 .

[19]  M. O. Tokhi,et al.  Active noise control systems , 1987 .

[20]  M. O. Tokhi,et al.  a Unified Adaptive Active Control Mechanism for Noise Cancellation and Vibration Suppression , 1996 .

[21]  Hanim Mohd. Yatim,et al.  Evolutionary algorithms for active vibration control of flexible manipulator , 2016 .

[22]  Magdalene Marinaki,et al.  Fuzzy control optimized by PSO for vibration suppression of beams , 2010 .

[23]  Intan Z. Mat Darus,et al.  Non-parametric modelling of a rectangular flexible plate structure , 2012, Eng. Appl. Artif. Intell..

[24]  Intan Z. Mat Darus,et al.  Soft computing-based active vibration control of a flexible structure , 2005, Eng. Appl. Artif. Intell..