虚拟直流电机技术参数分析及虚拟惯量自适应控制

Parameters Analysis and Virtual Inertia Adaptive Control of Virtual DC Motor Technique

建立了虚拟直流电机控制系统的闭环传递函数,分析了虚拟直流电机惯量系数和阻尼系数对性能的影响,并建立了基于模糊神经网络的虚拟惯量自适应控制器,解决了虚拟惯量导致的电压恢复缓慢问题。基于虚拟直流电机控制系统的闭环传递函数,根据伯德图、极点分布图以及阶跃响应曲线分析了惯量系数和阻尼系数变化对虚拟直流电机控制系统性能的影响。根据惯量系数和阻尼系数变化对控制系统性能的影响,以及虚拟直流电机控制算法,设计了基于模糊神经网络的虚拟惯量自适应控制器,并通过对系统超调量的限定,设计了阻尼系数的整定方法。通过计算机仿真分析,验证了基于模糊神经网络的虚拟惯量自适应算法的正确性,证明了该自适应控制器的有效性。

The closed-loop transfer function of control system for a virtual DC motor(VDM)is established,and the influences of its inertial coefficient and damping coefficient on its performance are analyzed.In addition,a virtual inertia adaptive controller based on the adaptive neuro-fuzzy inference system is established,and the problem of slow voltage recovery caused by virtual inertia is solved.Based on the closed-loop transfer function,the influences of variations in inertial coefficient and damping coefficient on the performance of the control system are analyzed according to the Bode diagram,pole map and step response curve.Based on these influences and the control algorithm for VDM,the virtual inertia adaptive controller based on the adaptive neuro-fuzzy inference system is designed.Moreover,an adjusting method for the damping coefficient is designed by limiting the overshoot of the system.The correctness of the virtual inertia adaptive algorithm based on the adaptive neuro-fuzzy inference system is verified by computer simulation analysis,and the effectiveness of the designed adaptive controller is also proved by simulations.