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Research on a Novel Control Strategy for Inverted Pendulum

Author: LiShengQuan
Tutor: ZhangShaoDe
School: Anhui University of
Course: Control Theory and Control Engineering
Keywords: inverted pendulum LQ controller chaos optimization neural network inverse control NNMRAC performance index
CLC: TP13
Type: Master's thesis
Year: 2008
Downloads: 52
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Abstract


Inverted pendulum system is a kind of typical fast nonlinear, strong couple, multi-variable non-minimum phase and inherent volatile system. The means of controlling this system are wildly used in the fields of war industry, spaceflight and the control of ordinary industry and so on. Inverted pendulum is an experiment platform of verifying a great variety of advanced control strategies. In the paper, the main innovatory researches are studied to realize chaotic optimization linear quadratic controller (LQ) and to put forward a neural network inverse controller for the nonlinear non-minimum phase system, based on the different characteristic of the multilevel linear inverted pendulum.The main contributions of these dissertations are following:1, The mathematical models based on instability equilibrium point of triple inverted pendulum and double inverted pendulum are proposed by using the Lagrange Equation, which are taken by the Googol Thchnology linear inverted pendulums as research objects. The characteristics which include controllability, observability, non-minimum phase and so on are analysed.2, The dissertation provides basic theories of chaos optimization by quantificational analyzing the ergodicity and statistic properties of chaos series generated by logistic map. A method is proposed for the weight matrix parameters tuning of LQ controller with chaos variables. The LQ controller is globally optimized with chaos ergodic searching. The scheme of a direct project significance performance index was introduced, in order to improve dynamic characteristic of the system. So the control law not only satisfies the quadratic functional performance indicator, but also has transient response of the system. Simulations prove the effectiveness of our method.3, The method of chaos optimization algorithm is extended to multi-variables LQ control system for the controller weight matrix parameters, by importing a novel synthesis performance index which fully considers each output and dynamic characteristics and stability of the system. In order to improve the speed of chaos optimization, the chaotic variable is applied to get global optimum right coefficient by means of combination global and partial chaos searching. We achieved the studies of experiments of double inverted pendulum and simulations of triple inverted pendulum. This performance of multivariable chaos optimization LQ control system was demonstrated rationally.4, Through constructing pseudo-plant, two methods of neural network direct inverse control and neural network model reference adaptive control were proposed for the nonlinear non-minimum phase characteristic of inverted pendulum. In this paper, the nearest neighbor clustering algorithm based on variable clustering radius was used for training RBFNN, in order to improve the training speed of network. Simulations prove that the two schemes have not only feasibility and resistance to disturbance, but also have robustness

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