Stabilization of inverted pendulum using LQR, PID and fractional order PID controllers: A simulated study

In this paper, a simulated study of three different control strategies; Linear Quadratic Regulator (LQR), Integer order PID and Fractional order PID (FOPID), is performed in order to stabilize an inverted pendulum on a cart. First, a nonlinear model of the cart-pendulum system is presented which is used later in the simulations. The tuning parameters of all three controllers are obtained using the Particle Swarm Optimization (PSO) technique, with the Integral of the Squared Error (ISE) index as fitting function and employing a unit step as reference. The simulation results, when applying a unit step reference (same as in the PSO tuning process), show a better performance for the FOPID when using the cost function of the LQR as performance index. However, in a more general case of a sequence of step references, the LQR exhibits a better behavior.

[1]  Concepción A. Monje,et al.  Introducción al Control Fraccionario , 2006 .

[2]  M Bettayeb,et al.  Stabilization of an inverted pendulum-cart system by fractional PI-state feedback. , 2014, ISA transactions.

[3]  N. Selvaganesan,et al.  Design of fractional controller for cart-pendulum SIMO system , 2012, 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT).

[4]  J. Ngamwiwit,et al.  Implementation of Swinging-up and Stabilizing Controllers for Inverted Pendulum on Cart System , 2008, 2008 International Symposium on Communications and Information Technologies.

[5]  Amit Patra,et al.  Swing-up and stabilization of a cart-pendulum system under restricted cart track length , 2002, Syst. Control. Lett..

[6]  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.

[7]  Jia-Jun Wang,et al.  Simulation studies of inverted pendulum based on PID controllers , 2011, Simul. Model. Pract. Theory.

[8]  Boris Tovornik,et al.  Swinging up and stabilization of a real inverted pendulum , 2006, IEEE Transactions on Industrial Electronics.

[9]  Hui Ding,et al.  An investigation on the design and performance assessment of double-PID and LQR controllers for the inverted pendulum , 2012, Proceedings of 2012 UKACC International Conference on Control.

[10]  I. Podlubny Fractional-Order Systems and -Controllers , 1999 .

[11]  Zhou Wan,et al.  The simulation of double inverted pendulum control based on particle swarm optimization LQR algorithm , 2010, 2010 IEEE International Conference on Software Engineering and Service Sciences.

[12]  Tatsuya Kai,et al.  A new discrete mechanics approach to swing-up control of the cart-pendulum system , 2014, Commun. Nonlinear Sci. Numer. Simul..

[13]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[14]  Orlando Beytia,et al.  Conical Tank Level Control with Fractional PID , 2016, IEEE Latin America Transactions.

[15]  Alexander G. Chefranov,et al.  An effective hybrid swing-up and stabilization controller for the inverted pendulum-cart system , 2010, 2010 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR).

[16]  Katsuhisa Furuta,et al.  Swinging up a pendulum by energy control , 1996, Autom..

[17]  M. Nour,et al.  Fuzzy logic control vs. conventional PID control of an inverted pendulum robot , 2007, 2007 International Conference on Intelligent and Advanced Systems.