This paper aims to highlight the critical role of robot manipulators in industrial applications and elucidate the challenges associated with achieving high-precision control. In particular, the detrimental effects of nonlinear friction on manipulators are discussed. To overcome this challenge, a novel friction compensation controller (FCC) that combines time-delay estimation (TDE) and an adaptive fuzzy logic system (AFLS) is proposed in this paper. The friction compensation controller is designed to take advantage of the time-delay estimation algorithm’s strengths in eliminating and estimating unknown dynamic functions of the system using information from the previous sampling period. Simultaneously, the adaptive fuzzy logic system compensates for the hard nonlinearities in the system and suppresses the errors generated by time-delay estimation, thus improving the accuracy of the robotic arm’s tracking. The numerical experimental results demonstrate that the proposed friction compensation controller can significantly enhance the tracking accuracy of the robotic arm, with the addition of the adaptive fuzzy logic system improving time delay estimation’s performance by an average of 90.59%. Moreover, the proposed controller is more straightforward to implement than existing methods and performs exceptionally well in practical applications.

Nuclear power plant emergency robots are robots used to respond to significant public safety incidents, such as uncontrolled radioactive sources and nuclear catastrophe leaks. However, there are no standardized evaluation criteria for the optimal design of the robots. We offer a quantitative analytic algorithm for optimizing nuclear power plant emergency robots to address this issue. The method optimizes the structural parameters of the robot in accordance with the workspace by analyzing, comparing, and evaluating the workspace. The approach comprises constructing a kinematic model of the mechanical arm and proposing an optimization algorithm based on the alpha shape to accurately describe the manipulator workspace; employing the proposed convex hull algorithm to quantitatively analyze and evaluate the workspace generated by different solutions in terms of area, volume, task demand, Structural Length Index and Global Conditioning Index; and determining the robotic arm joint parameters by selecting the optimum workspace design solution. Using the suggested algorithm, we optimize the design of the master and slave robotic arms of the nuclear power plant emergency robots. Theoretical calculations and simulation results demonstrate that the method is an effective and practical evaluation technique that not only accurately describes the workspace but also optimizes the design of the nuclear power plant emergency robots.

In order to realize the problem of tracking control of the trajectory of robot manipulators under variable load conditions, this paper proposes a non-singular fast terminal sliding mode tracking control design for robot manipulators based on integrated dynamic compensation. First, in the model, the friction torque under the influence of speed is considered while combined with the joint torque estimation for integrated dynamic compensation. Second, a novel non-singular fast terminal sliding mode controller is proposed, which helps to overcome the singularity problem and has been analyzed for stability using the Lyapunov method. Finally, trajectory tracking experiments are conducted on an experimental platform and compared with the PID algorithm, demonstrating the superior control performance of the proposed algorithm.