基于CMAC的电液负载模拟器自学习控制

通过建立某飞行器舵机电液负载模拟器与操舵系统联动的数学模型，分析了电液负载模拟器的多余力产生原理。提出了采用结构不变性原理设计补偿环节的基于CMAC神经网络的控制结构和算法。通过对系统的动态仿真表明，该方法可有效地抑制多余力，明显改善电液负载模拟器的动态加载性能。

CMAC-based self-learning control for the electrohydraulic load simulator

The dynamic model of the electrohydraulic load simulator combined with an aircraft steering electrohydraulic position servo system is established. The principle of the superfluous force of the electrohydraulic load simulator is analyzed. On the basis of using the structure invariance principle to design the compensation network, an adaptive self-learning control scheme based on CMAC neural network is proposed. Simulation results show that the proposed controller can effectively eliminate the superfluous force and fairly improve the dynamic loading performances of the electrohydraulic load simulator.