In this paper, the dynamics-based high-performance robot motion control technology has been mainly studied, and the overall structure is controlled via dynamics forward, given the nonlinearity, strong coupling and time-variability of robots. Considering the unavailability of precise robot model parameters and the uncertain disturbance in real operation, we put forward an active disturbance rejection control (ADRC) strategy based on dynamic feedforward, aiming to improve the control robustness and combining the simple structure, strong anti- disturbance ability, and no restriction from the control model of ADRC. Given the multi-joint coupling of robots, controlled decoupling is conducted by using dynamic characteristics. The ADRC cascade control structure and algorithm based on dynamic feedforward have been studied and the closed-loop stability of the system is investigated by analyzing the system dynamic linearization compensation and the anti-disturbance ability of the extended state observer. Experiments have shown the new strategy is more robust over uncertain disturbance than the conventional proportional-integral-derivative control strategy.

Purpose: This paper aims to present a method for improving the state estimation of a robot in the presence of noise measurement, which can improve the performance of the robot controller. Design/methodology/approach: In this work, a novel nonlinear tracking differentiator (NTD) was formulated to solve the problems of phase lag, low stability and amplitude attenuation faced by traditional tracking differentiators, which can be used for the state estimation of a robot. Based on the user-defined function stu() with linear and nonlinear characteristics, the authors establish a new acceleration function of NTD and confirm its global asymptotic stability by using the Lyapunov method and the system equivalence method. Phase plane analysis shows that the origin is its stable nodal point or focus point and uncovers the basic constraint conditions for parameter regulation. In addition, the convergence property and robustness performance against noises are studied by describing function method. Findings: Comparative simulations, robot state estimation experiments and joint trajectory tracking experiments have indicated that NTD proposed integrates tracking rapidness, accuracy and transitional stability and has high approximation and filtering effects on generalized derivatives of the signal, which contribute to an excellent performance of robot controller in stability and response speed in practice. Originality/value: The main contribution of this paper lies in the design of a novel NTD, which successfully improves the state estimation of a robot joint in noisy surroundings, the tracking performance of robot controller and the stability of the system.