Adaptive control algorithm based on clone selection optimization

A clonal selection based adaptive control algorithm is developed by applying clonal selection algorithm to the adaptive control problem. For the dynamical uncertainty of both the plant and the environmental disturbance, the adaptive machine of clonal selection dopes out the plant output by a plant model according to the plant inputs, and then evaluates the candidate controllers before selecting the fittest controller to the current plant operating conditions. Thus the actual controller is tuned on-line to adapt the plant and environment. In simulations, a third order nonlinear model was adopted as a cargo ship, a second order linear model as its model, and the PID control law was applied to them. The results show that the proposed controller can adapt well the dynamical plant and the environmental disturbance.