Adaptive memetic differential evolution-back propagation-fuzzy neural network algorithm for robot control - Zheng, Kunming; Zhang, Qiuju; Peng, Li; Zeng, Shuisheng (Information sciences, 2023)
•A novel intelligent control approach AMDE-BP-FNN to control complex robot system.•There is layer upon layer of optimal structure for AMDE-BP-FNN.•Making the best of the advantages of AMDE algorithm and BP algorithm, to optimize FNN.•The superiority of AMDE-BP-FNN is highlighted by quantitative comparison. This study established an adaptive memetic differential evolution-back propagation-fuzzy neural network (AMDE-BP-FNN) control method to achieve high-efficiency and precise control of robots with complex dynamic characteristics while reducing control costs. The adaptive differential evolution (ADE) method was applied to search the optimal parameters in the global scope and delimited the pseudo-global search scope. The memetic differential evolution (MDE) method was used to search for optimal parameters in the pseudo-global scope, and the probability factor was set to decide whether to use the back propagation (BP) algorithm for online optimization. Finally, simulations, experiments, and real-world applications were conducted. The results indicated the high efficiency, high precision, and viability of the proposed AMDE-BP-FNN method.