电站载物爬楼机器人的动态稳定性建模与控制

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。

Dynamic Stability Modeling and Control of Power Station Loaded Climbing Robot

Aiming at the control problem of the dynamic stability of the power station loaded climbing robot, this paper summarized the possible motion modes of the robot according to the characteristics of the climbing building, and constructed the mathematical model of the controlled object by the relationship between geometry and kinematics. According to the relationship among the distance error between the gravity center of the power station climbing robot and the expected distance, the error change rate and the telescopic speed of the electric push rod, a controller of the dynamic stability control system, T1FLC, was designed. In order to solve the problem that the fuzzy rule parameters were difficult to determine, QPSO was used to optimize the membership function parameters. Then this paper compared the QPSO optimized T1FLC with the PSO optimized T1FLC, the unoptimized T1FLC, and the PID control method, and further considered the external interference influence. Finally, the simulation results verify the accuracy of the model and the effectiveness of the control optimization method.