INTELLIGENT MECHATRONIC CONTROL SUSPENSION SYSTEM BASED ON QUANTUM SOFT COMPUTING

摘要

A control system for optimizing a shock absorber having a non-linear kinetic characteristic is described. The control system uses a fitness (performance) function that is based on the physical laws of minimum entropy and biologically inspired constraints relating to mechanical constraints and/or rider comfort, driveability, etc. In one embodiment, a genetic analyzer is used in an off-line mode to develop a teaching signal. The teaching signal can be approximated online by a fuzzy controller that operates using knowledge from a knowledge base. A learning system is used to create the knowledge base for use by the online fuzzy controller. In one embodiment, the learning system uses a quantum search algorithm to search a number of solution spaces to obtain information for the knowledge base. The online fuzzy controller is used to program a linear controller.