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This thesis addresses the collision avoidance control problem of
a 4WSground vehicle. A linear quadratic regulator (LQR) which is
a usefulcontrol method for linear systems is used to find the
state feedbackgain matrix (K) of linear vehicle systems. Then
the values of K computedby LQR set up the search space of
genetic algorithm (GA) in which theoptimal state feedback gain
of nonlinear vehicle system can be achieved.Because the GA-based
control law needs much time to search for the optimalsolution of
the optimization problem, it can't be a real time controllerfor
the vehicle systems. The feedback gain matrix for some vehicle'
svelocities searched by GA generates the continuous feedback
gain for adymanic range of the speed between 10 m/s and 50 m/s
by the interpolationmethod. At the end of this thesis, a Driver-
Preview-Model-based GA controlleris derived for nonlinear
vehicle systems to reduce the effects of the lateralacceleration
response's delay, and make the controlled vehicle system hasa
faster response and more stable performances.
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