IMPROVING AUTOMATIC BRAKE PERFORMANCE IN NONLINEAR VEHICLE USING ARTIFICIAL INTELLIGENCE TECHNIQUE
Publication Details
Abstract
This paper presents improving automatic brake performance in nonlinear vehicles using artificial
intelligence techniques. An empirical study of a fuzzy logic-based brake control system achieved a stability response time of 4.78s as the total time it takes to bring a nonlinear vehicle at 0.4N coefficient friction to stability and speed of 75Km/hr was conducted. A neural network algorithm was adopted and used to develop an automatic brake control system and then implemented with Simulink. The result when tested at the same condition with the characterized system showed a stability response time of 2.25s as against 4.78s in the characterized.
intelligence techniques. An empirical study of a fuzzy logic-based brake control system achieved a stability response time of 4.78s as the total time it takes to bring a nonlinear vehicle at 0.4N coefficient friction to stability and speed of 75Km/hr was conducted. A neural network algorithm was adopted and used to develop an automatic brake control system and then implemented with Simulink. The result when tested at the same condition with the characterized system showed a stability response time of 2.25s as against 4.78s in the characterized.
