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针对一类含有不确定项的非线性系统,提出了一种鲁棒直接自适应模糊控制算法,可在系统的控制增益已知、部分已知和未知三种情况下,实现系统跟踪有界参考信号的控制目标。该算法采用广义模糊双曲正切模型逼近系统的等价控制项,广义模糊双曲正切模型具有模糊规则个数少,更易于用语言描述获取的特点,在实际应用中更易实现。同时,引入鲁棒补偿项消除系统的不确定项和逼近误差,放宽系统稳定条件为最小近似误差有界。利用Lyapunov函数证明了采用上述控制策略保证了控制系统跟踪误差收敛到原点的一个小的邻域内,且所有的变量一致有界。仿真例子说明了该算法的有效性。
Aiming at a class of nonlinear systems with uncertainties, a robust direct adaptive fuzzy control algorithm is proposed, which can realize the system tracking bounded reference under the known, unknown and partially known control gains Signal control objectives. In this algorithm, the generalized fuzzy hyperbolic model is used to approximate the equivalent control of the system. The generalized fuzzy hyperbolic model has the characteristics of less number of fuzzy rules and easier to describe by language description, which is easier to implement in practical application. At the same time, the robust compensation term is introduced to eliminate the uncertainties and the approximation errors of the system. The relaxation of the system stability condition is that the minimum approximation error is bounded. The Lyapunov function is used to prove that the above control strategy ensures that the tracking error of the control system converges to a small neighborhood of the origin, and all the variables are uniformly bounded. The simulation example shows the effectiveness of the algorithm.