基于扩展卡尔曼滤波的移动机器人变结构线性化复合跟踪控制

Compound Tracking Control with Variable Structure Linearization for Mobile Robots Based on Extended Kalman Filter

  • 摘要: 研究了移动机器人轨迹跟踪控制问题,通过坐标变换将轨迹跟踪问题转化为误差系统的镇定问题.基于反馈线性化和变结构控制思想提出一种复合有限时间变结构线性化跟踪控制算法,其首先使误差系统驶向角初始误差快速收敛到滑模边界层,然后采用连续状态反馈控制律来实现驶向角误差的无抖振快速镇定,同时将原误差系统转化为低阶系统;其次针对低阶系统设计了位置误差的状态反馈控制律,实现了位置误差的有限时间镇定.针对有系统噪声和量测噪声的误差系统,利用扩展卡尔曼滤波(EKF)进行误差状态估计,并以估计值构成反馈控制律.通过数值仿真验证了控制策略的有效性.

     

    Abstract: The trajectory-tracking control problem for mobile robot is considered,and the trajectory tracking problem is transformed into the state stabilization problem of error-system through coordinate transformation.A compound finite-time tracking control linearization algorithm based on feedback linearization and variable structure is proposed,the reachingcontrol law is firstly used to drive the steering angle trajectory with initial error to quickly converge to the neighborhood of given switching surface,and then the steering angle error is stabilized quickly by a chattering-free control law based on continuous-time state-feedback,while the nonlinear system is converted into a reduced system.The state-feedback control law for the reduced-rank system is designed to stabilize the position error in finite time.For the error-system with system noise and measurement noise,extended Kalman filter(EKF) is used to estimate the states of the error-system,and the estimated states are used to construct the feedback control law.Numerical simulations show the effectiveness of the control scheme.

     

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