A decentralized PID neural network(PIDNN) control scheme was proposed to a quadrotor helicopter subjected to wind disturbance. First, the dynamic model that considered the effect of wind disturbance was established vi...A decentralized PID neural network(PIDNN) control scheme was proposed to a quadrotor helicopter subjected to wind disturbance. First, the dynamic model that considered the effect of wind disturbance was established via Newton-Euler formalism.For quadrotor helicopter flying at low altitude in actual situation, it was more susceptible to be influenced by the turbulent wind field.Therefore, the turbulent wind field was generated according to Dryden model and taken into consideration as the disturbance source of quadrotor helicopter. Then, a nested loop control approach was proposed for the stabilization and navigation problems of the quadrotor subjected to wind disturbance. A decentralized PIDNN controller was designed for the inner loop to stabilize the attitude angle. A conventional PID controller was used for the outer loop in order to generate the reference path to inner loop. Moreover, the connective weights of the PIDNN were trained on-line by error back-propagation method. Furthermore, the initial connective weights were identified according to the principle of PID control theory and the appropriate learning rate was selected by discrete Lyapunov theory in order to ensure the stability. Finally, the simulation results demonstrate that the controller can effectively resist external wind disturbances, and presents good stability, maneuverability and robustness.展开更多
针对液压弯辊控制系统的时变性、非线性和不确定性等特点,设计利用G A(遗传算法)优化的P I D神经网络(P I D N N)液压弯辊控制系统。P I D N N控制器不仅具有不依赖被控对象数学模型的优点,而且有很好的动态性能,结构简单易于设计。利用...针对液压弯辊控制系统的时变性、非线性和不确定性等特点,设计利用G A(遗传算法)优化的P I D神经网络(P I D N N)液压弯辊控制系统。P I D N N控制器不仅具有不依赖被控对象数学模型的优点,而且有很好的动态性能,结构简单易于设计。利用G A代替B P算法对P I D N N权值进行优化,克服了B P算法易陷于局部极小的不足。2种优化方法的仿真结果对比表明:G A-P I D N N控制器能够使液压弯辊力快速达到目标值,并且具有较强的抗干扰能力。展开更多
基金Project(2011ZA51001)supported by National Aerospace Science Foundation of China
文摘A decentralized PID neural network(PIDNN) control scheme was proposed to a quadrotor helicopter subjected to wind disturbance. First, the dynamic model that considered the effect of wind disturbance was established via Newton-Euler formalism.For quadrotor helicopter flying at low altitude in actual situation, it was more susceptible to be influenced by the turbulent wind field.Therefore, the turbulent wind field was generated according to Dryden model and taken into consideration as the disturbance source of quadrotor helicopter. Then, a nested loop control approach was proposed for the stabilization and navigation problems of the quadrotor subjected to wind disturbance. A decentralized PIDNN controller was designed for the inner loop to stabilize the attitude angle. A conventional PID controller was used for the outer loop in order to generate the reference path to inner loop. Moreover, the connective weights of the PIDNN were trained on-line by error back-propagation method. Furthermore, the initial connective weights were identified according to the principle of PID control theory and the appropriate learning rate was selected by discrete Lyapunov theory in order to ensure the stability. Finally, the simulation results demonstrate that the controller can effectively resist external wind disturbances, and presents good stability, maneuverability and robustness.
文摘针对液压弯辊控制系统的时变性、非线性和不确定性等特点,设计利用G A(遗传算法)优化的P I D神经网络(P I D N N)液压弯辊控制系统。P I D N N控制器不仅具有不依赖被控对象数学模型的优点,而且有很好的动态性能,结构简单易于设计。利用G A代替B P算法对P I D N N权值进行优化,克服了B P算法易陷于局部极小的不足。2种优化方法的仿真结果对比表明:G A-P I D N N控制器能够使液压弯辊力快速达到目标值,并且具有较强的抗干扰能力。
