CAJ | 학술논문

起重机起重过程中吊物摇摆系统模型的复杂性，非线性，时变性导致传统PID控制在此过程中存在控制效果不理想，控制参数难以整定等问题。利用模糊控制不依赖精确数学建模，以及神经网络的自学习性等优点。提出一种将起重机传统PID控制与模糊神经网络相结合的控制方法。通过仿真对比发现改进后的控制方法能够有效降低系统稳定的调节时间，吊装货物的摆幅也得到减少。
기중궤기중과정중조물요파계통모형적복잡성，비선성，시변성도치전통PID공제재차과정중존재공제효과불이상，공제삼수난이정정등문제。이용모호공제불의뢰정학수학건모，이급신경망락적자학습성등우점。제출일충장기중궤전통PID공제여모호신경망락상결합적공제방법。통과방진대비발현개진후적공제방법능구유효강저계통은정적조절시간，조장화물적파폭야득도감소。
The swing of crane lifting process is complexity,nonlinear, time-varying cause the traditional PID control in this process control effect is not ideal,control parameters tuning difficult .So present a new method about that based on the traditional PID control optimization with fuzzy neural network control. Combine with the adventage of fuzzy control does not depend on the ac-curate mathematical modeling and the neural network self-learning etc. The simulation results that the improved control method re-duce the system adjusting time, crane swing angle is also reduced.