Robust adaptive control
Adaptive Clonal Selection with Elitism-Guided Crossover for Function Optimization
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1
Multiobjective optimization using ideas from the clonal selection principle
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
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Using clonal selection model identification, an adaptive PD control algorithm with disturbance compensation is proposed for uncertain and nonlinear system in ship steering. Actual ship with disturbance and model uncertainty, regarded as a black box, is dynamically identified as second-order linear model with disturbance terms; then, certainty equivalence principle is applied to tune the PD control parameters while the disturbance is compensated. The combination of previous elitist reservation and stochastic initialization for the initial population in clonal selection algorithm improves the optimization efficiency for dynamic problem. Simulations on the third-order nonlinear cargo vessel verify that the proposed adaptive control algorithm possesses strong robustness and improves the capability of PD controller in inhibiting stable error.