基于人工蜂群算法的倒立摆线性二次最优控制

B. Ata, Ramazan Coban
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引用次数: 6

摘要

本文的主要目的是确定合适的权重矩阵,利用人工蜂群算法设计倒立摆的线性二次最优控制器。对于线性二次型最优控制系统,如何选择合适的权重矩阵是一个挑战,目前还没有相关的系统技术来解决这个问题。一般情况下,这些权重的选择是基于设计师的经验和时间的试错法进行的。此外,加权矩阵的值与稳定时间、超调量和稳态误差等时域指标之间也没有直接关系。本文采用人工蜂群算法选择加权矩阵来克服这些困难。人工蜂群算法是一种基于群体智能的优化算法,其灵感来自于蜜蜂在蜂巢周围的蜂群。它可以有效地用于多变量、多模态的函数优化。仿真结果表明,与试错法相比,人工蜂群算法具有较好的鲁棒性和有效性。
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Linear quadratic optimal control of an inverted pendulum using the artificial bee colony algorithm
The main purpose of this paper is determination of suitable weighting matrices to design a linear quadratic optimal controller for an inverted pendulum using the artificial bee colony algorithm. It is challenging to select appropriate weighting matrices for a linear quadratic optimal control system and there is no relevant systematic techniques presented for this goal. Generally, selecting these weights is performed by trial and error method which is based on designer's experience and time consuming. Also there is no direct relation between weighting matrices' values and time domain specifications like settling time, overshoot and steady state error. In this paper, the artificial bee colony algorithm has been used for selecting weighting matrices to overcome these difficulties. The artificial bee colony algorithm is a swarm intelligence based optimization algorithm and inspired by honey bees' swarming around their hive. It can be efficiently used for multivariable, multimodal function optimization. Simulation results show that the artificial bee colony algorithm is very efficient and robust in comparison with trial and error method.
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