초록 ▼

A control system for optimizing the performance of a vehicle suspension system by controlling the damping factor of one or more shock absorbers is described. The control system uses a fitness (performance) function that is based on the physical laws of minimum entropy. The control system uses a fuzz

A control system for optimizing the performance of a vehicle suspension system by controlling the damping factor of one or more shock absorbers is described. The control system uses a fitness (performance) function that is based on the physical laws of minimum entropy. The control system uses a fuzzy neural network that is trained by a genetic analyzer. The genetic analyzer uses a fitness function that maximizes information while minimizing entropy production. The fitness function uses a difference between the time differential of entropy from a control signal produced in a learning control module and the time differential of the entropy calculated by a model of the suspension system that uses the control signal as an input The entropy calculation is based on a dynamic model of an equation of motion for the suspension system such that the suspension system is treated as an open dynamic system.

대표청구항 ▼

1. An optimization control method for a shock absorber comprising the steps of:obtaining a difference between a time differential of entropy inside said shock absorber and a time differential of entropy given to said shock absorber from a control unit that controls said shock absorber; and optimizin

1. An optimization control method for a shock absorber comprising the steps of:obtaining a difference between a time differential of entropy inside said shock absorber and a time differential of entropy given to said shock absorber from a control unit that controls said shock absorber; and optimizing at least one control parameter of said control unit by using a genetic algorithm, said genetic algorithm using said difference as a performance function.