摘要
研究了电液负载模拟器的自适应最优控制问题。将线性二次型最优控制与GCMAC神经网络相结合,提出了一种自适应最优控制策略。该控制策略把最优控制器作为辅助控制器,采用GCMAC神经网络在线学习使闭环系统满足理想性能要求的控制量。Lyapunov稳定性分析证明该控制策略具有渐近稳定性。仿真结果表明系统具有较好的动态性能和较高的载荷谱跟踪精度。
An adaptive optimal control method on electro-hydraulic loading simulator was investigated. After combining the optimal control theory with GCMAC neural network, an optimal control strategy was proposed. This control strategy uses optimal controller as an assistant controller, and uses GCMAC neural network online to study the control to satisfy the perfect performance request of the closeloop system. The Lyapunov stability analyse proved this close-loop system is gradually stable. The simulation results illustrate that the system has better dynamic performance and higher instruct tracking accuracy.
出处
《机床与液压》
北大核心
2007年第6期134-136,共3页
Machine Tool & Hydraulics
关键词
电液负载模拟器
小脑模型神经网络
自适应
最优控制
Electro-hydraulic loading simulator
Cerebellar model articulation controller neural network
Adaptation
Optimal control
