Lifting and Transport Mechanisms with Intelligent Control Systems

Starting and stopping of many mechanisms is a problematic phenomenon that causes a load on the mechanical and electrical part of the object. The use of standard regulators does not always make it possible to achieve the necessary starting characteristics and speed indicators of braking. The paper proposes the use of a regulator, the principle of operation of which is based on the rules of fuzzy logic. In the course of the research, a rule base was developed that reflects the functioning of a real object. A neural network controller with the ability to train the network and adjust it when changing the system parameters is proposed. Based on the analysis of several types of regulators, optimal indicators of the start and stop processes were obtained when a supervisor was introduced into the system. Use of the proposed regulators allows to ensure the stability of the control system.