Using Ga-Based Intelligent Control Means to Enhance Human-Machine Interfaces
Daniel W. Repperger, Ling Rothrock · Intelligent Automation & Soft Computing · 2005
Abstract A GA (genetic algorithm) search procedure was employed to explore a best set of sensory feedback parameters in designing ahuman-machine interface for improved performance. The optimization concerned two objective functions of interest, which incorporated tradeoffs between speed and accuracy in tracking. APareto-optimal front was calculated involving the two cost functions selected. This approach differs from the traditional minimum of anon-convex cost function (scalaz) describing the desired closed loop performance. Also, this methodology used a parsimonious experimental design method. By making a few runs with a limited number of subjects, a response model was first developed. This model was then simulated and a complex vector response surface was generated by the performance variables of interest. The GA seazch procedure was then used to locate the minimum of this response surface. Finally, in a post hoc experimental study to confirm that the selected design parameters were the best from the cl...