The paper is devoted to the problem of optimizing the trajectories of parallel robots in the positioning process. The problem of minimizing the duration of the robot positioning cycle in order to increase its productivity is discussed. A new optimization problem has been formulated, aimed at minimizing the total mileage of electric drives during the cycle in order to increase the energy efficiency of the robot. The objective functions of optimization problems based on modified metrics are proposed: Manhattan and Chebyshev. A comparison of the efficiency of using optimal trajectories instead of the "obvious" ones was carried out for various parallel robots: planar, tripod, and delta robots. Conclusions are drawn about the basic requirements for the trajectory of the robot to ensure maximum productivity and energy efficiency.

Keywords: parallel robot, performance, duration of the positioning cycle, energy efficiency, electric drive mileage, objective function, Chebyshev metric, Manhattan metric, optimal trajectory, comparative modeling, planar robot, tripod robot, delta robot

within the framework of the conducted research, the task of controlling a robot of a parallel structure was considered. This paper presents a model of a 3-RPR type flat parallel robot in the Matlab package, developed for conducting computational experiments. Implementation of two types motion trajectories have been simulated in order to determine the optimal structure of the position regulators of the drive joint used in the robot control system. Six structure of regulators were compared: three classical ones: PD, PID, PDD and three of their fractional-degree analogues: FOPD, FOPID, FOPDD. The FOMCON tool was used to model fractional-degree regulators. The best results for type 3-PPR robot were shown by a control system with a FOPID regulator, which indicates the expediency of using fractional-degree regulators to control parallel robots.

Keywords: parallel robot, inverse kinematics problem, 3-RPR robot, computational experiment, working out the trajectory of movement, control system accuracy, fractional-degree regulator, parametric optimization of the regulator, comparative modeling, FOMCON tool

The aim of the work is to increase the productivity of the iron ore concentrate dehydration process. In the course of previous research, an automated system with individual control of each vacuum filter technological parameters was developed. In this paper, it is proposed to supplement this system of an extreme step regulator hybrid intelligent control unit. A structural and functional scheme and an algorithm for the functioning of the control system have also been developed. The implementation of the developed control system will improve the productivity of the vacuum filter, reduce the wear of the actuators, reduce the specific consumption of energy resources used, and save the financial resources of the enterprise. The proposed control system can be adapted for a large class of technological units of a similar principle of operation used in various industries.

Keywords: iron ore concentrate dehydration, disk vacuum filter, artificial neural network, fuzzy neural network, automated control system, individual regulation, extreme regulator, vacuum, pulp density, vacuum filter productivity sludge moisture