Sistema de controle fuzzy-ótimo aplicado ao problema de balanço pendular da carga em pontes rolantes

Abstract

Cranes are tools for transportation throughout the history of mankind, enabling the activities of the productive states of civilizations. Practically in all sectors of human activity, such as: ports, railways and the automotive industry, demanding platforms for the development of its activities. The operation of cranes is complex and dangerous to be human, as well as improper operation can damage the load. Among the problems related to the operation of the crane, the problem of load evaluation is a phenomenon that compromises the quality of service and safety in its operation. In view of the problem of pendular load control, since it is important for the ongoing control project of Logic and Control, the scales are presented in this dissertation. The purpose of the Fuzzy-Optimal control system design involves as optimality properties and fuziness. The physical data processing and control interfaces are combined for the generation of controllers and infer the behavior of the pendulum oscillations. Optimality is used by means of the joint adjustment function, but there is no sense in minimizing it as a bridge of states with minimum control. A fuziness is marked by the medium of pertinence functions, acting to correct perturbations and parametric effects. Thus, the work addressing the problem of pendulum load displacement in highways, a solution based on a Fuzzy logic and the optimal controls are presented in this dissertation. Since the process under study that involves the inputs and outputs, along with the variable of value and height, does not generate linear ones that can be controlled. As the solution is essential, the co-ordination principle and the base method is not an LQR method and the fuzzy controller that actuating together promote improvements in bridge movement and pendulum load movement, taking into account the cable height characteristics. A multivariate crossover state mathematical model is adapted for optimal control applications, as well as algorithms based on Fuzzy-Optimum models, under this dissertation, are used to evaluate the performance of the proposal and its comparison with the classic PID driver.