Tracking control of time-varying signal is a very challenging problem for the network environment applications. An adaptive control strategy based on the inverse of fuzzy singleton model is proposed in the paper. The fuzzy singleton model is a designed equivalent system instead of the fuzzy clustering model of the controlled process. Following an invertibility condition, a collection of predicted control actions are derived from the iterated inverse fuzzy singleton model. Thus, the data dropout and time delays in the network are compensated by means of these predicted values. To enhance control performance, the adaptive control strategy is adopted. Since the method is started from the inputs and outputs of the process, it is actually a data-based solution which is very suitable to the processes with blurred mechanism. Compared with other two control algorithms, the proposed control algorithm exhibits good accuracy, high efficiency, and fast tracking features. Simulations in the data dropout and time-delay cases have verified the effectiveness of the method.

时变信号的跟踪控制对于网络环境应用来说是一个非常具有挑战性的问题。提出了一种基于模糊单例模型逆的自适应控制策略。模糊单例模型是设计的等效系统，而不是受控过程的模糊聚类模型。遵循可逆条件，从迭代逆模糊单例模型中导出一组预测控制动作。因此，网络中的数据丢失和时间延迟通过这些预测值得到补偿。为了提高控制性能，采用自适应控制策略。由于该方法是从流程的输入和输出开始的，它实际上是一种基于数据的解决方案，非常适合具有模糊机制的流程。与其他两种控制算法相比，所提出的控制算法具有精度好、效率高、跟踪速度快等特点。在数据丢失和时滞情况下的仿真验证了该方法的有效性。