Huakai Zhang
Robotic arm, whale algorithm, particle swarm optimisation algorithm, fuzzy sliding-mode controller, trajectory planning; tracking control
In recent years, the use of robotic arms in the automation industry has become increasingly prevalent due to advances in science and technology. This paper aims to enhance the control accuracy of manipulators by designing a hybrid optimisation algorithm. The whale algorithm has been optimised and combined with the particle swarm optimisation (PSO) algorithm to achieve this goal. The trajectory of the manipulator is planned through the utilisation of the hybrid algorithm. The membership function of the fuzzy controller is optimised via the hybrid whale PSO algorithm, and combined with the sliding-mode controller, resulting in the design of a fuzzy sliding-mode controller. The results show that in the convergence curve, the iterations for the hybrid algorithm to reach the global optimal solution is 52, 75, and 183. The rate of convergence is faster. In the joint angle change curve, the total time of optimised B-spline interpolation is 19.95 s. The working efficiency of the manipulator is improved. In the calculation of tracking error, the optimised controller has a tracking error between -0.25 and 0.25, resulting in higher trajectory tracking accuracy. Therefore, the hybrid algorithm has good convergence, and the optimised controller has high accuracy, providing good technical support for trajectory planning and tracking control of robotic arms.
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