针对电站载物爬楼机器人动态稳定性的控制问题,根据爬楼特点归纳出机器人可能出现的运动模式,并利用几何与运动学等关系构建被控对象的数学模型。根据电站载物爬楼机器人上下两部分的重心距离与期望距离间的误差、误差变化率及电动推杆...针对电站载物爬楼机器人动态稳定性的控制问题,根据爬楼特点归纳出机器人可能出现的运动模式,并利用几何与运动学等关系构建被控对象的数学模型。根据电站载物爬楼机器人上下两部分的重心距离与期望距离间的误差、误差变化率及电动推杆伸缩速度之间的关系,设计动态稳定性控制系统的控制器,即一型模糊逻辑控制器(1 type of fuzzy logic,T1FLC)。针对模糊规则参数难以确定的问题,通过量子粒子群优化(quantum particle swarm optimization,QPSO)算法优化隶属度函数参数,将QPSO优化的T1FLC与粒子群优化(particles swarm optimization,PSO)算法优化的T1FLC、未优化的T1FLC、比例-积分-微分(proportion-integral-derivative,PID)控制方法进行对比,并进一步考虑外部干扰的影响。仿真和实验结果验证了模型的准确性及控制优化方法的有效性。展开更多
A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, th...A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.展开更多
Improving rollover and stability of the vehicles is the indispensable part of automotive research to prevent vehicle rollover and crashes.The main objective of this work is to develop active control mechanism based on...Improving rollover and stability of the vehicles is the indispensable part of automotive research to prevent vehicle rollover and crashes.The main objective of this work is to develop active control mechanism based on fuzzy logic controller(FLC) and linear quadratic regulator(LQR) for improving vehicle path following,roll and handling performances simultaneously.3-DOF vehicle model including yaw rate,lateral velocity(lateral dynamic) and roll angle(roll dynamic) were developed.The controller produces optimal moment to increase stability and roll margin of vehicle by receiving the steering angle as an input and vehicle variables as a feedback signal.The effectiveness of proposed controller and vehicle model were evaluated during fishhook and single lane-change maneuvers.Simulation results demonstrate that in both cases(FLC and LQR controllers) by reducing roll angle,lateral acceleration and side slip angles remain under 0.6g and 4° during maneuver,which ensures vehicle stability and handling properties.Finally,the sensitivity and robustness analysis of developed controller for varying longitudinal speeds were investigated.展开更多
文摘针对电站载物爬楼机器人动态稳定性的控制问题,根据爬楼特点归纳出机器人可能出现的运动模式,并利用几何与运动学等关系构建被控对象的数学模型。根据电站载物爬楼机器人上下两部分的重心距离与期望距离间的误差、误差变化率及电动推杆伸缩速度之间的关系,设计动态稳定性控制系统的控制器,即一型模糊逻辑控制器(1 type of fuzzy logic,T1FLC)。针对模糊规则参数难以确定的问题,通过量子粒子群优化(quantum particle swarm optimization,QPSO)算法优化隶属度函数参数,将QPSO优化的T1FLC与粒子群优化(particles swarm optimization,PSO)算法优化的T1FLC、未优化的T1FLC、比例-积分-微分(proportion-integral-derivative,PID)控制方法进行对比,并进一步考虑外部干扰的影响。仿真和实验结果验证了模型的准确性及控制优化方法的有效性。
基金Project(51005253) supported by the National Natural Science Foundation of ChinaProject(2007AA04Z344) supported by the National High Technology Research and Development Program of China
文摘A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.
文摘Improving rollover and stability of the vehicles is the indispensable part of automotive research to prevent vehicle rollover and crashes.The main objective of this work is to develop active control mechanism based on fuzzy logic controller(FLC) and linear quadratic regulator(LQR) for improving vehicle path following,roll and handling performances simultaneously.3-DOF vehicle model including yaw rate,lateral velocity(lateral dynamic) and roll angle(roll dynamic) were developed.The controller produces optimal moment to increase stability and roll margin of vehicle by receiving the steering angle as an input and vehicle variables as a feedback signal.The effectiveness of proposed controller and vehicle model were evaluated during fishhook and single lane-change maneuvers.Simulation results demonstrate that in both cases(FLC and LQR controllers) by reducing roll angle,lateral acceleration and side slip angles remain under 0.6g and 4° during maneuver,which ensures vehicle stability and handling properties.Finally,the sensitivity and robustness analysis of developed controller for varying longitudinal speeds were investigated.
