The method of multi objective design of nonlinear electromechanical tracking systems based on neural network controller using hybrid metaheuristic optimization algorithm

• Datum: 2026
• Hauptverfasser: Kuznetsov, B. I., Nikitina, T. B., Bovdui, I. V., Voloshko, O. V., Kolomiets, V. V., Kobylianskyi, B. B.
• Format: Artikel
• Sprache: Englisch
• Veröffentlicht: National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine 2026
• Schlagworte: nonlinear electromechanical tracking system; neural network controller; multi objective design; computer simulation; experimental research
• Online Zugang: https://eie.khpi.edu.ua/article/view/366076
• Назва журналу: Electrical Engineering & Electromechanics

Problem. Most research on the design of nonlinear electromechanical tracking systems has been conducted using typical proportional-differential controllers, but there is no methodology for designing nonlinear electromechanical tracking system based on neural network controller to meet different requirements that are imposed on the operation of the system in different modes. Goal. To develop the method of multi objective design of nonlinear electromechanical tracking system based on neural network controller to satisfy different requirements that are imposed on the operation of the system in various modes. Methodology. The designed nonlinear electromechanical tracking system based on neural network controller implements the dynamics of a reference model by training a neural network controller for a given model of a nonlinear control object. Multi objective design of the reference model reduces to solving a vector nonlinear programming problem, in which the components of the vector objective function are direct different requirements that are imposed on the operation of the system in various modes. The solution to the vector nonlinear programming problem is calculated using a hybrid heuristic optimization algorithm, incorporating particle swarm optimization and stochastic sequential quadratic programming. Results. The results multi objective design of two-mass nonlinear electromechanical tracking systems based on neural network controller in which different requirements that are imposed on the operation of the system in various modes were satisfied are given. Based on the results of modeling and experimental studies it is established, that with the help of synthesized neural network controllers, it is possible to improve of quality indicators of two-mass nonlinear electromechanical tracking system in comparison with the system with standard regulators. Scientific novelty. For the first time the method of multi objective design of nonlinear electromechanical tracking systems based on neural network controller to satisfy different requirements that are imposed on the operation of the system in various modes is developed. Practical value. From the point of view of the practical implementation the possibility of solving the problem of multi objective design of nonlinear electromechanical tracking systems based on neural network controller to satisfy different requirements that are imposed on the operation of the system in various modes is shown. References 43, figures 8.