Canonical Particle Swarm Optimization Algorithm Based a Hybrid Vehicle

This paper deals with the modeling and optimization of a PID 2 DOF controller design for a Hybrid vehicle. Such a Particle Swarm Optimization (PSO) based PID 2Dof controller is investigated in order to stabilize both the velocity of studied vehicle. The aim goal of this paper is to improve the effectiveness of synthesized control using the strategy of a canonical PSO optimization to tune its weighting matrices instead to configure it by a trials-errors method. This work reminds firstly to describe all aerodynamic forces and moments of the hybrid vehicle within an inertial frame and a dynamical model is obtained thanks to the Lagrange formalism. A 2Dof PID controller is then designed for the Velocity stabilization of the studied vehicle. Several PSO updating strategies are proposed to enhance the stability and the rapidity of our studied system through minimizing a definite cost function of’ controller’s weighting matrices. The obtained results are carried out in order to show the effectiveness and robustness of the different PSO updating strategies based the 2Dof PID Controller.

[1]  Ramón Vilanova,et al.  Conversion formulae and performance capabilities of two-degree-of-freedom PID control algorithms , 2012, Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012).

[2]  Finn Haugen.  The Good Gain method for simple experimental tuning of PI controllers , 2012 .

[3]  Vandana Patel,et al.  Two Degree of Freedom PID Controller For speed control of DC Motor , 2015 .

[4]  S. Amir Ghoreishi,et al.  Optimal Design of LQR Weighting Matrices based on Intelligent Optimization Methods , 2011 .

[5]  José A. Romero,et al.  Cargo securement methods and vehicle braking performance , 2016 .

[6]  R. Eberhart,et al.  Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[7]  Rochdi Trigui,et al.  Vehicle trajectory optimization for application in ECO-driving , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[8]  M. Araki,et al.  Two-Degree-of-Freedom PID Controllers , 2003 .

[9]  Barjeev Tyagi,et al.  Modelling and Simulation for Optimal Control of Nonlinear Inverted Pendulum Dynamical System Using PID Controller and LQR , 2012, 2012 Sixth Asia Modelling Symposium.

[10]  Aleksandar Simonović,et al.  Free vibration control of smart composite beams using particle swarm optimized self-tuning fuzzy logic controller , 2014 .

[11]  J. Hamidi.  Control System Design Using Particle Swarm Optimization (PSO) , 2012 .

[12]  Mituhiko Araki,et al.  Two-Degree-of-Freedom PID Controllers — Their Functions and Optimal Tuning , 2000 .