Random anonymization via multi-objective immune cloning evolution
基于多目标免疫克隆进化的随机匿名化算法*

For the conventional integral control for nonlinear systems, designed an improved adaptive integral control method to reduce the steady-state tracking error and prevent integral saturation. The method used feedback linearization to eliminate nonlinearity, and adjusted the proportional factor and integral factor corresponding to the error by introducing penalty functions, then could avoid the large overshoots due to the large initial errors. By using the Lyapunov synthesis approach, it is proved that the closed-loop system is uniformly ultimately bounded in the presence of bounded disturbance force. Theoretical analysis on the stability of the closed-loop system and simulation results show the feasibility of the proposed scheme.