基于模糊神经网络算法的交流伺服系统DSP控制

将神经网络与模糊逻辑控制结合起来,设计模糊神经网络控制器应用于交流伺服系统中的转速调节器,克服交流调速系统中参数漂移、非线性和耦合等因素的影响.针对模糊神经网络控制器运算量大、收敛慢的特点,硬件采用数字信号处理器(DSP)作为控制器运算单元,并在DSP上实现模糊神经控制算法,提高了系统实时性.实验结果表明,采用该控制器的调速系统具有较快的响应速度、较高的稳态精度和较强的鲁棒性.

DSP control for AC servo system based on algorithm of fuzzy neural network

Applying the fuzzy neural network control produced by the combination of fuzzy control and neural network control to the speed control of AC servo system can overcome the negative impact of parameter variations, nonlinear and coupled in AC servo motor. According to the characteristics of abundant calculation and slow convergence of fuzzy neural network conlroller, DSP chip is used by the hardware as its controller computing unit. It achieves the application of DSP successfully to its controller and improves the control of AC speed regulating system. The experimental results show that the system has characteristics of fast response speed, high steady accuracy and good robustness.