基于神经网络的反馈线性化非对称系统

针对对称阀控非对称缸电液伺服系统的非线性,为了提高系统的控制精度,在分析该系统的固有特性的基础上提出了反馈线性化控制策略,分析了反馈线性化系统的稳定性,并采用神经网自适应补偿控制对不确定参数进行补偿,最后选择合理参数进行仿真实验。实验表明:基于神经网络技术的反馈线性化阀控非对称系统不但稳定性好、控制精度高,而且系统的跟踪性能优越,适用于实时控制的场合。

Feedback Linearization Asymmetric System Based on Neural Network

Considering the symmetric valve controlled asymmetrical cylinder electro-hydraulic servo system of nonlinear and in order to improve the control precision of the system, a novel feedback linearization control strategy is put forward based on the analysis of the inherent property of the system.The feedback linearization stability of the system is analyzed, and adaptive compensation control for uncertain parameters is introduced by using the neural networks. Finally reasonable parameters are chosen for the simulation.Experimental results show that the neural network technique based feedback linearization valve control system not only has good stability, high control accuracy, also the system tracking performance is superior, which is applicable to real time control situation.