Optimization of LQR controller for inverted pendulum system with artificial bee colony algorithm

2013 ◽  
Author(s):  
Haiquan Wang ◽  
Huaqiang Zhou ◽  
Dongyun Wang ◽  
Shengjun Wen
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Inverted Pendulum ◽  
Pendulum System ◽  
Bee Colony ◽  
Inverted Pendulum System ◽  
Lqr Controller

Optimal Design of LQR Controller Based on Improved Artificial Bee Colony Optimization Algorithm

2014 ◽  
Vol 971-973 ◽  
pp. 1272-1275 ◽  
Author(s):  
Huai De Yang
Keyword(s):  
Artificial Bee Colony ◽  
Inverted Pendulum ◽  
Balance Control ◽  
Pendulum System ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Inverted Pendulum System ◽  
Lqr Controller ◽  
Bee Colony Optimization ◽  
The Mathematical Model

The inverted pendulum system is characterized as a typical nonlinear, fast multi-variable, essentially unstable system. It is difficult to control because of its instability .In order to improve balance control, the mathematical model of the single inverted pendulum is established, a LQR controller is designed which is based on improved artificial bee colony. Experiments show that the improved algorithm has better performance than standard artificial bee colony algorithm on convergence and rate balance control to meet the requirements of the single inverted pendulum.

scholarly journals Improved Artificial Bee Colony Algorithm and Its Application in LQR Controller Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Haiquan Wang ◽  
Lei Liao ◽  
Dongyun Wang ◽  
Shengjun Wen ◽  
Mingcong Deng
Keyword(s):  
Artificial Bee Colony ◽  
Linear Quadratic Regulator ◽  
Food Sources ◽  
Linear Quadratic ◽  
Pendulum System ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Inverted Pendulum System ◽  
Fitness Value ◽  
Lqr Controller

In order to get the optimal performance of controller and improve the design efficiency, artificial bee colony (ABC) algorithm as a metaheuristic approach which is inspired by the collective foraging behavior of honey bee swarms is considered for optimal linear quadratic regulator (LQR) design in this paper. Furthermore, for accelerating the convergence speed and enhancing the diversities of population of the traditional ABC algorithm, improved solution searching approach is proposed creatively. The proposed approach refers to the procedure of differential mutation in differential evolutionary (DE) algorithm and produces uniform distributed food sources in employed bee phase to avoid local optimal solution. Meanwhile, during the onlooker bees searching stage where the solution search area has been narrowed by employed bees, new solutions are generated around the solution with higher fitness value to keep the fitness values increasing monotonously. The improved ABC algorithm is applied to the optimization of LQR controller for the circular-rail double inverted pendulum system, and the simulation results show the effect on the proposed optimization problem.

scholarly journals Optimal design of an adaptive robust controller using a multi-objective artificial bee colony algorithm for an inverted pendulum system

2021 ◽  
Author(s):  
Mohammad Javad Mahmoodabadi ◽  
Sadegh Hadipour Lakmesari
Keyword(s):  
Artificial Bee Colony ◽  
Inverted Pendulum ◽  
Sliding Mode ◽  
Heuristic Method ◽  
Adaptive Robust Control ◽  
Control Technique ◽  
Pendulum System ◽  
Multi Objective ◽  
Bee Colony ◽  
Inverted Pendulum System

In this paper, a multi-objective artificial bee colony (MOABC) optimization algorithm is utilized to improve the performance of an adaptive robust control technique. This approach is implemented on an inverted pendulum system. More precisely, the proposed controller is a combination of a decoupled sliding mode controller (DSMC) and adaption laws based on the gradient descent approach. In order to achieve the optimum control operation, the MOABC, as a novel meta-heuristic method simulated from the smart foraging activity of honey bee groups, is employed to optimize the coefficients of the suggested controller. In this regard, the objective functions are determined as the integral time of the absolute value of the pole angle and cart position errors. Finally, the time responses of the system states and control effort are presented to prove the effectiveness and feasibility of the suggested strategy compared to other contemporary studies referenced in the paper.

scholarly journals Multibody Modeling and Balance Control of a Reaction Wheel Inverted Pendulum Using LQR Controller

2021 ◽  
Vol 1 (1) ◽  
pp. 84-89
Author(s):  
Ümit Önen ◽  
Abdullah Çakan
Keyword(s):  
State Space ◽  
Inverted Pendulum ◽  
Balance Control ◽  
Space Representation ◽  
Reaction Wheel ◽  
Linear Quadratic ◽  
Pendulum System ◽  
State Space Representation ◽  
Inverted Pendulum System ◽  
Lqr Controller

In this study, modeling and LQR control of a reaction wheel inverted pendulum system is described. The reaction wheel inverted pendulum model is created by using a 3D CAD platform and exported to Simscape Multibody. The multibody model is linearized to derive a state-space representation. A LQR (Linear-quadratic regulator) controller is designed and applied for balance control of the pendulum. The results show that deriving a state-space representation from multibody is an easy and effective way to model dynamic systems and balance control of the reaction wheel inverted pendulum is successfully achieved by LQR controller. Results are given in the form of graphics.

scholarly journals USING GENETIC ALGORITHM IN OPTIMIZING THE MATRIX OF LQR CONTROLLER FOR NONLINEAR INVERTED PENDULUM SYSTEM

2019 ◽  
Vol 1 (28) ◽  
pp. 50-55
Author(s):  
Tan Thanh Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Inverted Pendulum ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Pendulum Model ◽  
The Matrix ◽  
Lqr Controller ◽  
Genetic Algorithm Method

In this article, the author used the matlab software to simulate and then compared the results between the classical LQR (Linear Quadratic Regulator) controller and another method to adjust the matrix parameters toward optimization of the LQR controller. It is the GA (Genetic Algorithm) method to optimize the matrix of the LQR controller, and the results have  been verified on the nonlinear pendulum model. The Genetic Algorithm is a modern control algorithm, which is widely applied in research and practice. The main objective of this article is to use the GA algorithm in order to optimize the matrix parameters of LQR controller, whichcontrolled the position and angle of the nonlinear inverted pendulum at the stable balance point. The matlab-based simulating results showed that  the system has operated properly to the requirements and the output response has reached an equilibrium position of about 2.5 seconds.

MBPOA-based LQR controller and its application to the double-parallel inverted pendulum system

2014 ◽  
Vol 36 ◽  
pp. 262-268 ◽  
Author(s):  
Ling Wang ◽  
Haoqi Ni ◽  
Weifeng Zhou ◽  
Panos M. Pardalos ◽  
Jiating Fang ◽  
...  
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Lqr Controller
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