智能系统学报Issue(5)：602-607,6.DOI:10.3969/j.issn.1673-4785.201304071
改进教与学优化算法的 LQR 控制器优化设计
Optimal design of a linear quadratic regulator (LQR) controller based on the modified teaching-learning-based optimization algorithm
摘要
Abstract
To determine the weighting matrix Q and R for a linear quadratic regulator ( LQR) , a modified teaching-learning-based optimization ( MTLBO) algorithm is proposed to tune weighting factors for active suspension LQR controller.The “Teaching” phase and“learning” phase are modified using MTLBO based on the basic TLBO algo-rithm.A novel“self-learning” strategy is employed in MTLBO.The simulation results showed that the MTLBO algo-rithm has distinct advantages in convergence, precision and stability than basic TLBO, PSO and genetic algorithms.关键词
教与学优化算法/LQR控制器/优化控制/主动悬架/粒子群优化算法/遗传算法Key words
teaching-learning-based optimization algorithm/LQR controller/optimal control/active suspension/particle swarm optimization/genetic algorithm分类
信息技术与安全科学引用本文复制引用
拓守恒,邓方安,雍龙泉..改进教与学优化算法的 LQR 控制器优化设计[J].智能系统学报,2014,(5):602-607,6.基金项目
国家自然科学基金资助项目（11401357）；陕西省教育厅基金资助项目（14JK1141）；汉中市科技局基金资助项目（2013hzzx-39）． （）
