Reactive parking control of nonholonomic vehicles via a fuzzy learning automaton

The paper presents an intelligent reactive controller, which is capable of performing automated parallel parking in a confined space slightly larger than the dimensions of the vehicle. This controller combines the features of fuzzy logic control and sliding-mode control and is modelled as a fuzzy learning automaton. Starting with a brief exposition of the principles of reactive learning and learning automata, the concept of the reduced complexity sliding-mode fuzzy logic controller (RC-SMFLC), employed, is introduced. Then the solution of the parking problem via the RC-SMFLC, along with the convergence analysis, is presented. Representative simulation results are provided that demonstrate the parking steps and the effectiveness of the parking controller