基于免疫优化的平面Acrobot线性自抗扰鲁棒镇定

针对受不确定性影响的平面Acrobot机器人,提出一种基于免疫优化的线性自抗扰鲁棒控制设计方法,实现机器人末端点从任意初始位置到达并镇定在目标位置.首先,借助驱动关节与被动关节角度之间的状态约束获取机器人末端点位置与驱动关节角度的对应关系,使末端点的位置控制转换为驱动关节的角度控制;其次,为缩短运动路径加入最小角度位移限制条件,设计免疫算法求解目标位置所对应的驱动关节角度的最小期望值;再次,引入线性自抗扰控制技术,把机器人的模型不确定性、未知干扰等因素视为一个新的扩张状态变量,设计线性扩张状态观测器和基于状态误差的反馈控制器,在仅驱动关节角度可测的情况下实现Acrobot的鲁棒镇定;最后,通过仿真实验验证所提出方法具有更好的鲁棒控制性能.

Robust stabilization of planar Acrobot using linear active disturbance rejection control with immune optimization

A robust stabilization design method based on linear active disturbance rejection control(ADRC) with immune optimization is proposed for a planar Acrobot affected by uncertainties such that the end point of the robot can reach and be stabilized at the target position from any initial position. Firstly, the relationship between the position of the end point of the robot and the angle of the actuated joint is obtained by means of the state constraint relationship between the angle of the actuated joint and the angle of the underactuated joint. After that, the position control of the end point is converted to the angle control of the actuated joint. Secondly, in order to shorten the motion path, a condition of minimum angular displacement restriction is defined, and an immune algorithm is designed to obtain the minimum desired angle of the actuated joint corresponding to the target position. Thirdly, the linear ADRC control technique is introduced, and the uncertainties such as model uncertainties and unknown disturbances are regarded as an extended state of the system. A linear extended state observer and a feedback controller based on state error are designed to realize the robust stabilization of the Acrobot when only the angle of the actuated joint is measurable. Finally, simulations are conducted to show that the proposed method has better robust control performance.