This article proposes a method with a potential field for optimizing the configuration of angular velocity to avoid joint limitations while following the desired orientation of the end effector of a redundant manipulator. In the practical application of inverse kinematics for redundant manipulators, the most important tasks include avoiding collisions and maintaining the workspace. The null space projection method has been used to solve inverse kinematics from redundancy with the additional task of avoiding angle limitations. However, because such tasks vary, they can interfere in maintaining the desired orientation and following the end effector's desired trajectory. Furthermore, because of the use of a pseudoinverse matrix, singular value decomposition is applied to each calculation to avoid singularity; however, this increases the calculation time. To resolve these problems, the proposed method optimizes the error between the desired and actual tasks using the potential field method and angular limitation value function. This renders the proposed method more intuitive for assigning additional tasks to the manipulator while avoiding joint limitations and obstacles in real time. In the simulation, the calculation time using the proposed method is confirmed to be shorter than that of the conventional method. Finally, the proposed approach is verified to be capable of avoiding obstacles and angle limitations when the method is applied to a manipulator with seven degrees of freedom in the experiment.

This paper proposes a novel controller, fast fractional-order terminal sliding mode control (FFOTSMC), for a seven-degree-of-freedom (7-DOF) robot manipulator with tracking control. The new controller applies the fractional-order derivative on both the sliding surface design and the sliding control/reaching law. Compared to previous research, which only applies the fractional-order derivative on the sliding surface design, the proposed controller has a faster convergence for reaching the sliding surface and maintaining stay on it because of the new fractional-order control law, which helps the tracking accuracy. To implement the controller on the robot with less chattering, a sliding perturbation observer (SPO) is used to estimate the disturbance and uncertainties. Stability analysis is analyzed using Lyapunov functions for fractional-order systems. The controller performance is evaluated by a simulation of a single-input and single-output (SISO) system in MATLAB Simulink and experiments on the robot manipulator.

A new perturbation estimator, using radial basis function (RBF) neural networks (RBFNN) to modify the sliding perturbation observer (SPO), is proposed with the fast fractional-order terminal sliding mode control (FFOTSMC). It aims to control a seven-degree-of-freedom (7-DOF) robot manipulator. The new perturbation estimator applies the data-driven method RBFNN to compensate for the estimation error in the conventional SPO for the first time. The modified SPO estimates the perturbation, which contains the disturbance, dynamic uncertainties, and modeling errors. The estimated perturbation is used to design with the FFOTSMC, which improves the tracking accuracy and reduces the chattering. The FFOTSMC was designed using the fractional-order derivative to design the sliding surface and the reaching/law for reaching the sliding surface. In experiments on the robot, the proposed estimation method has been evaluated by comparing with the conventional SPO or only RBFNN with the same controller, FFOTSMC. The asymptotic stability of the controller with the new estimator is proved using Lyapunov functions for fractional-order systems.

In this study, a fuzzy logic system to tune the parameters of terminal sliding mode control with a sliding perturbation observer (TSMCSPO) in real-time is proposed according to the system’s state changes to improve the control performance of TSMCSPO for a 5-DOF robot manipulator used for nuclear reactor dismantlement. Accurate trajectory tracking control is required when using a multi-DOF robot manipulator to cut the decommissioned nuclear reactor. A TSMCSPO scheme using TSMC in SPO has been proposed in previous research, which improves the estimation and convergence performance of traditional SMCSPO. In TSMCSPO, the parameters of the controller are important to enhance the control performance. Moreover, due to the influence of the working environment and the uncertainty of the system, the characteristics of the system will be changed during the trajectory tracking control of the multi-degree-of-freedom robot manipulator. Therefore, real-time optimal parameter tuning is required. In this regard, using fuzzy logic to tune the parameters is an effective method. By designing fuzzy rules, the controller parameters can be optimized. In this study, the proposed algorithm and, the trajectory tracking control simulation of the robot manipulator in the nuclear reactor vessel internal (RVI) are implemented in MATLAB/Simulink environment. The control algorithm is verified by the experiments on a real robot manipulator platform. The outstanding control performance of the algorithm is demonstrated by comparing the trajectory tracking error between the proposed fuzzy TSMCSPO scheme and TSMCSPO with fixed parameters.

This article introduces a novel method for calibrating serial robots using the Linearized Finite Screw Deviation (LFSD) model, aiming to minimize errors within the robot's workspace with a few end-effector postures. In contrast to prior studies that require several end-effector posture measurements, our proposed method presents a more resource-efficient approach suitable for practical applications. The proposed LFSD model stands out by enabling the identification of axis deviations with significantly fewer end-effector points compared to previous studies. This reduction in measurement points not only enhances applicability but also reduces the potential possibilities of noise arising from end-effector measurements. Moreover, the method's simple affine structure extends its applicability to the calibration of redundant robots. To validate the effectiveness of our proposed method, simulations and experiments with wire-encoder-based stereotactic devices were conducted on serial robots with five and six degrees of freedom