Position Control of Electro-hydraulic Actuator System Using Fuzzy Logic Controller Optimized by Particle Swarm Optimization

The position control system of an electro-hydraulic actuator system (EHAS) is investigated in this paper. The EHAS is developed by taking into consideration the nonlinearities of the system: the friction and the internal leakage. A variable load that simulates a realistic load in robotic excavator is taken as the trajectory reference. A method of control strategy that is implemented by employing a fuzzy logic controller (FLC) whose parameters are optimized using particle swarm optimization (PSO) is proposed. The scaling factors of the fuzzy inference system are tuned to obtain the optimal values which yield the best system performance. The simulation results show that the FLC is able to track the trajectory reference accurately for a range of values of orifice opening. Beyond that range, the orifice opening may introduce chattering, which the FLC alone is not sufficient to overcome. The PSO optimized FLC can reduce the chattering significantly. This result justifies the implementation of the proposed method in position control of EHAS.

[1]  Yahaya Md Sam,et al.  Modeling and controller design of an industrial hydraulic actuator system in the presence of friction and internal leakage , 2011 .

[2]  Engang Tian,et al.  Delay-dependent stability analysis and synthesis of uncertain T-S fuzzy systems with time-varying delay , 2006, Fuzzy Sets Syst..

[3]  P. J. Angeline,et al.  Using selection to improve particle swarm optimization , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[4]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[5]  L. Reznik Fuzzy Controllers , 2004 .

[6]  Li Bo,et al.  Automatization of Excavator and Study of its Autocontrol , 2011, 2011 Third International Conference on Measuring Technology and Mechatronics Automation.

[7]  J.M.G. Sá da Costa,et al.  A DESIGN APPROACH TO FDI/FTC OF COMPLEX NETWORKED CONTROL SYSTEMS , 2007 .

[8]  M. Wiercigroch,et al.  Hysteretic effects of dry friction: modelling and experimental studies , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[9]  Nguyen Hong Quang,et al.  Robust low level control of robotic excavation , 2000 .

[10]  M. F. Rahmat,et al.  Application Of Self-Tuning Fuzzy Pid Controller On Industrial Hydraulic Actuator Using System Identification Approach , 2009 .

[11]  José Manuel Andújar Márquez,et al.  Stability analysis and synthesis of multivariable fuzzy systems using interval arithmetic , 2004, Fuzzy Sets Syst..

[12]  Frank Klawonn,et al.  Fuzzy Control - Fundamentals, Stability and Design of Fuzzy Controllers , 2006, Studies in Fuzziness and Soft Computing.

[13]  Carlos Canudas de Wit,et al.  Friction Models and Friction Compensation , 1998, Eur. J. Control.

[14]  Michio Sugeno,et al.  On improvement of stability conditions for continuous Mamdani-like fuzzy systems , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[15]  Clarence W. de Silva,et al.  Tracking control of an electrohydraulic manipulator in the presence of friction , 1998, IEEE Trans. Control. Syst. Technol..

[16]  Bruce H. Wilson,et al.  Combining Leakage and Orifice Flows in a Hydraulic Servovalve Model , 2000 .

[17]  Peter Kwong-Shun Tam,et al.  Lyapunov-function-based design of fuzzy logic controllers and its application on combining controllers , 1998, IEEE Trans. Ind. Electron..

[18]  Han Me Kim,et al.  A position control of electro-hydraulic actuator systems using the adaptive control scheme , 2009, 2009 7th Asian Control Conference.

[19]  Hao Ying,et al.  Structure and stability analysis of general Mamdani fuzzy dynamic models , 2005, Int. J. Intell. Syst..

[20]  R. Eberhart,et al.  Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[21]  Carlos Canudas de Wit,et al.  A new model for control of systems with friction , 1995, IEEE Trans. Autom. Control..

[22]  Li Bo,et al.  High performance control of hydraulic excavator based on Fuzzy-PI soft-switch controller , 2011, 2011 IEEE International Conference on Computer Science and Automation Engineering.

[23]  Mete Kalyoncu,et al.  Mathematical modelling and fuzzy logic based position control of an electrohydraulic servosystem with internal leakage , 2009 .

[24]  Hugh Durrant-Whyte,et al.  Impedance control of a hydraulically actuated robotic excavator , 2000 .

[25]  Peter Kwong-Shun Tam,et al.  A fuzzy sliding controller for nonlinear systems , 2001, IEEE Trans. Ind. Electron..

[26]  任璐风 典型模糊控制器(Fuzzy controller)的设计 , 2010 .

[27]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[28]  HighWire Press Philosophical Transactions of the Royal Society of London , 1781, The London Medical Journal.

[29]  Rudolf Kruse,et al.  Fuzzy Control , 2015, Handbook of Computational Intelligence.

[30]  Hugh F. Durrant-Whyte,et al.  Fuzzy sliding-mode controllers with applications , 2001, IEEE Trans. Ind. Electron..