Developing a quasi-optimal, in terms of transition time and energy consumption, closed-loop control system for an electrical installation

Introduction. The efficiency and normal work of electrotechnological processes and installations in their operation dynamic modes is characterized by the time of transition from initial to final state, low energy consumption, accuracy in transients and stability of the desired final state. It is proposed, from a single position on the basis of special optimal control, to combine transition and stabilization systems both in terms of determining the control algorithm with minimal energy consumption in the function of the object states and determining the parameters and conditions of movement with minimal deviation from a given trajectory providing the optimal transmission time and energy saving in a stable closed system of an object control. Materials and Methods. The principle of maximum is used as the main method for finding optimal program control, which for the study of special modes was supplemented with the apparatus of the position generality conditions for nonlinear objects with the coordinate space expansion, taking into account the occurrence of time and optimality criterion. The position generality apparatus is also used to solve energy-saving problems through using linearization in a large source object. Quasi-optimality in terms of transition time and energy consumption is achieved through minimizing energy according to the program motion parameter, which has a contradictory effect on the transition time and control amplitude. Results. To assess computational difficulties, transition time, energy saving, accuracy and stability, an example of inertial object control according to various criteria is given. The structure of a closed quasi-optimal system with stationary feedback, which is simple in technical implementation, is obtained. Discussion and Conclusion. The formalization of the approach to the construction of quasi-optimal systems based on the position generality allows it to be used in multi-criteria optimization tasks and computer-aided design systems for energy-intensive industrial, transport, and agricultural electrical installations.