基于蚁群算法的机器人系统LQR最优控制研究

针对两轮自平衡机器人线性二次最优控制器(LQR)中的权参数选择问题,提出了一种基于自适应蚁群算法的权矩阵优化参数策略.利用LQR控制器,采用自适应蚁群算法对LQR权矩阵Q的各位参数进行数字寻优,将得到的数字序列进行划分,寻找到最优参数值,从而对两轮自平衡机器人的俯仰属性进行有效的系统控制.仿真实验结果表明:采用蚁群算法优化后的控制器比人工选择参数策略有更好的控制效果,验证了方法的稳定性和有效性.

Research on LQR optimal control of robot based on ant colony algorithm

Aiming at problem of parameter selection for linear quadratic optimal controller(linear quadratic regulator,LQR)of the two-wheeled self-balancing robot,a weight matrix parameters optimization strategy based on adaptive ant colony algorithm is proposed.The method uses LQR controller,and all parameters of LQR weighting matrices Q are digitally optimized using adaptive ant colony algorithm.The obtained digital sequence is divided to find the optimal parameter,and the pitch properties of two-wheeled self-balancing robot are used to control the system.The simulation results show that the proposed method has better control effect than the artificial selection parameters strategy,and the stability and effectiveness of the proposed method is verified by using ant colony algorithm.