针对一类具有未知时变时滞的一阶非线性参数化系统，提出一种自适应迭代学习控制方案。通过利用边界层函数构造广义跟踪误差，消除了迭代学习控制初始精确定位的限制。为避免因引入边界层函数而产生的奇异性问题，引入双曲正切函数，并根据双曲正切函数的性质，通过构造Lyapunov-krasovskii型复合能量函数证明了所有信号的有界性和跟踪误差的收敛性。仿真算例验证了所提出方案的有效性。

An adaptive iterative learning control ( AILC) scheme was proposed for a class of first-order nonlinear param-eterized systems with unknown time-varying delays.By utilizing boundary layer function to construct generalized track-ing error, the assumption of initial condition for iterative learning control ( ILC) was removed.The possible singularity problem arising from boundary layer function was avoided by introducing the hyperbolic tangent function.According to the characteristic of hyperbolic tangent function, the boundedness of all signals and the convergence of tracking errors were proved in two cases by constructing Lyapuonv-Krasovskii-Like composite energy function ( CEF) .Finally a simu-lation example demonstrates the effectiveness of the control scheme.

针对一类控制增益函数未知的、含有不确定项的非线性系统,为实现其跟踪控制目标,提出了一种鲁棒直接自适应模糊控制方法.该方法仅要求控制增益函数为有界函数,用广义模糊双曲正切模型逼近一个与控制增益函数无关的新颖的等价控制器,并为消除系统中的不确定项和逼近误差设计了一个双曲形式的鲁棒补偿控制项,从而保证了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,控制输入平滑没有抖振.利用Lyapunov函数证明了该算法的有效性,并用倒立摆仿真实例进行了验证.

A robust direct self-adaptive fuzzy control scheme for a class of nonlinear system with uncertainty and unknown control gain function is proposed to achieve tracking control. In this scheme,only based on existence of control gain function bound,a novel certainty equivalent controller which is unconcerned of control gain function is approximated by a generalized fuzzy hyperbolic model (GFHM).Furthermore,a robust compensation control term is constructed in the form of hyperbolic function to eliminate uncertainty of nonlinear system and the approximation error.Then,the overall control system guarantees that the tracking error converges in the small neighborhood of zero and that all signals involved are uniformly bounded,also a smooth control input with no chattering phenomena is developed.The effectiveness of the proposed control algorithm is proved by Lyapunov function and the simulation example of the inverted pendulum tracking control system.

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。

For a class of nonlinear systems with uncertainty, a robust direct adaptive fuzzy control scheme is proposed to achieve tracking reference signal on conditions that the control gain of the system is known/known partly/unknown. In this scheme, the certainty equivalent control term is approximated by a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Because it is easier to describe and access, with a lower number of fuzzy rules, GFHM is achieved easily in engineering practice. Further, a robust compensation term is introduced to compensate the approximation error and uncertainty. The system stability condition is relaxed to the existence of bounds of minimum approximation error. Through Lyapunov function it is proven that the overall control system guarantees that the tracking error converges in the small neighborhood of zero and that all signals involved are uniformly bound. An example of the simulation is provided to demonstrate the effect of the p

提出将ip-iq谐波检测方法中的低通滤波器用一种新型变步长LMS自适应滤波算法来实现,该算法用双曲正切函数进行步长更新,使之具有较快的收敛速度和跟踪速度。仿真结果表明,相比传统ip-iq谐波检测算法,所提算法不仅拥有较高的检测精度,而且拥有更快的动态响应性能,提高了谐波电流的检测性能。

LMS adaptive filtering algorithm with a new type of variable step size was proposed to realize the low-pass filter in theip-iqharmonic detection method. The proposed algorithm is implemented by a hyperbolic tangent function for updating step length, so that it has a faster convergence speed and tracking speed. Simulation results show that compared with the traditionalip-iq harmonic detection algorithm, the proposed algorithm not only has a high detection accuracy, but also has a faster dynamic response performance, which adds up to improve harmonic current detection performance.

为了提高图像处理效果，提出一种改进MSR图像增强算法。首先将MSR算法中的对数函数改为双曲正切函数，然后采用MSR算法对图像进行增强处理，以提高图像的增强质量。采用仿真实验对改进MSR算法与其它图像增强算法进行对比。采用具体仿真实验对改进MSR算法的性能进行验证。仿真结果表明，相对于其它图像增强算法，改进MSR算法明显提高了图像增强后的质量，具有良好的视觉欣赏效果。

In order to improve the effect of image processing, this paper proposes an improved MSR image enhancement algorithm. the logarithm function in the MSR algorithm is replace by hyperbolic tangent function, and then the MSR algorithm is used to enhance image processing to improve the quality of image enhancement. The simulation experiments is carried out to test the performance of the improved MSR a. The simulation results show that the proposed algorithm significantly improves the quality of image enhancement compared with other image enhancement algorithm, it has good visual effect of the appreciation.