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With the system complexity and objects uncertainties increasing, for overcoming the defect of linear PID controller, a nonlinear PID controller was constructed by analyzing the ideal varying process of the individual tuning nonlinear PID controller concerning error. The traditional optimization was inapplicable due to the quantity of gain parameters increasing. On the basis of analyzing the control parameter optimization by ant colony optimization (ACO), the self-adaptive ant colony optimization based on sensation was used and the fuzzy self-adaptive update mechanism of pheromone was added. The controller was compared with nonlinear PID controller based on ACO, linear controller based on ACO and Z-N in simulation, their control performance and convergence performance were analyzed. The results show that the algorithm overcomes the defect of traditional ACO effectively which is slow in converging, possible to sink into local optimum and effected by initial value, and the controller has better dynamic performance and steady performance.