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Research On Improved Particle Swarm Optimization Algorithm In Double Stage Inverted Pendulum Control System

Posted on:2017-04-29Degree:MasterType:Thesis
Country:ChinaCandidate:H G PengFull Text:PDF
GTID:2308330503960602Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
Many problems of the control theory are embodied in the double inverted pendulum system,such as common servo,natural not stability,robustness,and nonlinear problem. These problems are many practical engineering’s typical research object,at the same time,a lot of control objects are modeled based on the inverted pendulum system,such as the space shuttle and the gait planning of biped robot physical system,and so the research of inverted pendulum system has very important theoretical significance and practical significance.LQR controller is commonly used for double inverted pendulum system,and it has good dynamic characteristics and robustness,and the LQR controller is needed to add the optimal weighting matrix Q and R to achieve optimal control. The traditional way is to rely on artificiality to set Q and R value,and it is difficult to meet the requirements of precision and the efficiency is very low,and this will affect the stability of the double inverted pendulum control system,the response speed and the overshoot of system.Based on the above problems this study puts forward an improved particle swarm optimization algorithm for the weighted matrix Q and R of LQR controller optimization,and to obtain the optimal value of Q and R and to achieve the optimal control for double inverted pendulum system.This paper around the improved particle swarm optimization algorithm is used in the double inverted pendulum control system,and to realize the optimal control of inverted pendulum control system to do the following work:1)This paper introduces the research background and significance of the inverted pendulum control system,the research status at home and abroad,and the commonly used control methods and the advantages and disadvantages of various methods. In the second chapter,the double inverted pendulum control system is modeled,and the performance of the inverted pendulum system is analyzed,and improved particle optimization group of algorithm applied in the control system of the inverted pendulum is feasibility;2)Analyzing advantages and disadvantages of particle swarm optimization algorithm and local search ability is insufficient and “premature” convergence and other problems,the inertial weight in this study and learning factors and the current local optimal value is improved,and it improves the search performance of algorithm and conducts on numerical experiment,and the experimental results verify the advantages of improved particle swarm optimization algorithm;3)Analyzing the shortcoming of the traditional LQR controller,the improved particle swarm optimization algorithm is applied to the LQR controller on the optimization of Q and R value,and contrast analysis shows that the improved particle swarm optimization algorithm through the experiment of LQR controller on the control of double inverted pendulum can improve the response speed and precision of the inverted pendulum control system,reducing the overshoot amount. Also to further illustrate that this improved particle swarm algorithm is effective and feasible.4)Seting the double inverted pendulum and hardware experiment platform.
Keywords/Search Tags:inverted pendulum, LQR, particle swarm algorithm
PDF Full Text Request
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