具有饱和执行器多重滞后系统的鲁棒控制

利用LMIs方法,对一类具有非线性饱和执行器的不确定线性多重滞后系统的鲁棒镇定问题进行了研究,提出了新的鲁棒可镇定判据和相应的鲁棒无记忆状态反馈控制器设计方法.简洁的例子说明了结果的有效性.     

一类非线性不确定结构系统的鲁棒饱和主动控制

对一类非线性不确定结构系统研究了在外部干扰下的鲁棒饱和主动控制策略.将质量、阻尼、刚度矩阵都存在不确定的结构系统描述为一种不确定中立系统,采用鲁棒饱和主动控制策略,提出基于线性矩阵不等式的代数解.通过提出的控制方法同时保证了结构系统在模型和参数摄动下以及在控制变量和扰动存在非线性不确定性时的鲁棒稳定.最后通过对一个4层建筑大楼在地震波作用下的主动振动控制仿真证明了该方法的有效性.     

鲁棒优化设计方法在结构动力学中的应用

在传统的静力学鲁棒优化设计基础上,考虑时间t参数,通过优化系统目标函数和约束条件的鲁棒性,将鲁棒优化设计方法运用在动力学问题中。通过一个主系统的质量和刚度均有微小波动的二自由度模型减振器设计算例,与传统的优化设计方法相比,显示了鲁棒优化设计的优越性,能使结构具有更稳定的性能。     

空调温控的鲁棒自适应Fuzzy-PID控制器

针对空调系统多变量、非线性、时滞和时变的特点,提出了一种用于空调系统温度控制的鲁棒自适应两级模糊比例-积分-微分(PID)控制器并进行了仿真.该控制器通过一个模糊切换开关把模糊比例-微分控制器和模糊积分控制器结合起来,模糊比例-微分控制器用来在系统动态响应期间减小上升时间和超调,模糊积分控制器用来抗干扰和消除稳态误差.仿真结果表明,所提出的控制器与传统控制器相比不仅鲁棒性好,同时具有优良的动静态性能.     

一类具有不匹配不确定性非线性系统鲁棒输出跟踪

应用输入／输出反馈线性化法和李亚谱诺夫直接法,提出了一种基于不确定项上界的连续型鲁棒输出跟踪控制器设计方案。利用该方案设计的鲁棒跟踪控制器可确保相应闭环系统的输出跟踪误差及状态一致最终有界。所提出的鲁棒跟踪控制器计算简单,更易实现。最后给出了一个例子,仿真结果证明了所提方法的可行性与有效性。     

不确定多重时滞中立系统的时滞相关鲁棒H∞控制

本文利用一个新的积分不等式方法讨论了一类不确定多重时滞中立系统的时滞相关鲁棒H∞控制器设计问题.该中立系统的状态项、控制项、微分项、外部干扰输入项均含有时滞.首先,利用Lyapunov稳定性理论,推导出系统鲁棒可镇定的充分条件.在此基础上,进一步给出了鲁棒H∞控制器存在的充分条件.不需要对原系统进行模型变换,仿真算例说明了定理的可行性.     

一类不确定性机器人的鲁棒跟踪控制

本文提出一种新的用以控制具有参数不确定性机器人的轨迹跟踪鲁棒控制方案。控制器由基于标称模型设计的非线性补偿控制器和基于Lyapunov理论设计的鲁棒补偿控制器构成，鲁棒补偿控制器用十消除参数误差带来的不确定性影响，其结构简单，只需知道系统的一个参数不确定性上界，最后保证系统达到三种不同的稳定性。另外，在机器人参数不确定性上界未知时，我们还设计了一个简单的在线辨识器，以保证系统全局收敛。并通过仿真实验证明其可靠性和有效性。     

不确定Takagi-Sugeno模糊广义交联大系统的鲁棒分散H∞控制

本文研究参数不确定Takagi-Sugeno(简称T-S)模糊广义交联大系统的鲁棒分散H∞控制问题。得到了使闭环系统渐近稳定并满足一定H∞性能指标的充分条件,用线性矩阵不等式(LMI)方法表示了这些充分条件,状态反馈鲁棒H∞控制器可以通过解这些LMIs而得到。算例说明所得结果的可行、有效。     

复合材料机翼鲁棒气动弹性优化设计

针对气动弹性结构, 利用遗传-敏度混合算法开展鲁棒优化设计。以大展弦比复合材料机翼的鲁棒气动弹性结构优化设计为例验证了鲁棒设计方法的适用性和有效性, 比较了鲁棒结构优化设计与传统优化设计的区别。研究结果表明: 在设计变量存在不确定性的情况下, 考虑鲁棒性约束优化得到的结构较传统优化结构具有更好的抗干扰性; 但鲁棒性的满足是以增加结构质量为代价的, 鲁棒性要求越高, 结构增重越明显。      

一种用于H.264数据分类的自适应的不平等错误保护策略

主要从较新的H．264视频压缩标准出发,提出了一种适用于视频流在包丢失的Internet上传输的基于数据分类的自适应不平等保护策略。实验证明,与传统方法相比,该方法实现了在一定包丢失概率下质量与码率的较好权衡,并且获得了较好的错误鲁棒性能。     

Fuzzy Design Method of Product Quality Robustness

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Robust Design Rule with Definite Purpose Character Based on Fuzzy Probability and Study of its Characteristics

The design target with definite purpose character of product quality was described in a real fuzzy number(named fuzzy target for short in this paper),and its membership functions in common use were given.According to the fuzzy probability theory and the robust design principle,the robust design rule based on fuzzy probability(named fuzzy robust design rule for short)was put forward and its va-lidity and practicability were analyzed and tested with a design example.The theoretical analysis and the design examples make clear that,while the fuzzy robust design rule was used,the fine design effect can be obtained and the fuzzy robust design rule can be very suitable for the choice of the membership function of the fuzzy target;so it has a particular advantage.     

Tolerance synthesis using second-order fuzzy comprehensive evaluation and genetic algorithm

In modern manufacturing engineering, tolerance synthesis is important because it directly effects product quality and manufacturing cost. This paper introduces a new method for tolerance synthesis of machining parts. The new method consists of three steps. First, machining parts are evaluated using the second-order fuzzy comprehensive evaluation (FCE). Then, a mathematical model for tolerance allocation is formed based on the machinability of the parts. Finally, the model is solved using the genetic algorithm (GA). The feasibility of the method is validated using a practical gearbox design example.     

基于模糊滑模切换控制的PMSMS弱磁调速控制策略

针对表贴式永磁同步电主轴(PMSMS)弱磁控制方案中,主轴系统调速性能欠佳的问题,提出一种基于模糊滑模切换控制(FSMSC)的超前角弱磁调速策略。在转速误差大于设定阈值时,使用模糊控制器实现主轴转速快速趋近给定值,利用模糊控制的特点对控制器进行实时的参数调整,使系统具有更强的鲁棒性;在转速误差小于设定阈值时,使用趋近律滑模控制器提高系统抗干扰能力,减小加工过程中因负载突变造成的加工误差,进一步增强系统鲁棒性。实验结果表明,基于FSMSC的超前角弱磁调速策略能有效抑制定子电流震荡以及电磁转矩脉动,并且控制器对抖动因子参数敏感性低,参数调节便捷,在实际加工中具有重要意义。     

基于混合智能的刀具状态在线识别

提出了一个将小波包分析方法,模糊理论及人工神经网络技术相结合的智能刀具状态在线监测系统,系统利用小波包方法将声发射信号分解为不同频带的时间序列,从中抽取出与刀具切削状态紧密相关的序列信号的构方根值（RMS）作为信号特征值,为了表示刀具状态与特征值之间的关系提出了一个模糊神经网络模型,采用了自组织竞争学习与BP算法相结合的混合学习算法,可迅速,可靠地对刀具状态进行识别。     

Fuzzy adaptive networks in machining process modelling: dimensional error prediction for turning operations

Due to the complexity of machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true for high-speed machining processes. To model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural-fuzzy approach appears ideally suited for this purpose. To illustrate the approach, the recently developed fuzzy adaptive networks are used to model dimensional error in turning operations. The fuzzy adaptive network has both the learning ability of a neural network and the linguistic representation of a complex, not well understood or vague phenomenon. An approximate model representing the influences of machining parameters on dimensional error is first established. This model is then improved by learning with the given training data. The improved models are verified by the use of test data, which are obtained by the use of actual experiments.     

基于主动空气轴承作动器的模糊主动振动控制研究

提出基于主动空气轴承作动器的溜板模糊主动振动控制。在溜板的空气静压支承基础上,以主动空气轴承为作动器,采用模糊控制方法,实现运动中的溜板振动主动控制。在自制的空气静压导轨上用电磁激振器模拟干扰力进行控制实验,取得良好效果。     

Fuzzy geometric programming approach to a fuzzy machining economics model

Machining economics is an important function of the process planning activity for manufacturing products with high quality and low cost. The machining economics model usually contains a highly non-linear objective function and equations that could be formulated as a geometric programming problem. The paper develops a solution method for deriving the fuzzy objective value of the fuzzy machining economics problem when some of the parameters in the problem are fuzzy numbers. A pair of geometric programs is formulated to calculate the lower and upper bounds of the unit production cost at possibility level α. With the ability to calculate the fuzzy objective value developed, it might help lead to a more realistic modelling effort. The developed methodology can also be applied to other engineering design problems with fuzzy numbers.     

Optimization of a machining economics model with fuzzy exponents and coefficients

The primary objective of a machining economics model is to determine the optimal cutting parameters that minimize production costs while satisfying some design constraints. This paper develops a solution method that can derive the fuzzy unit production cost of a fuzzy machining economic model when the exponents of decision variables in the objective function, the cost and the constraint coefficients are fuzzy numbers. A pair of two-level machining economics problems is formulated to calculate the upper and lower bounds of the fuzzy unit production cost at possibility level α. Based on the duality theorem and by using a variable substitution technique, the two-level machining economics problem is transformed into the one-level conventional geometric program. Solving the corresponding pair of geometric programs produces the interval of the unit production cost. The examples show that the interval of unit production cost contain more information when the parameters in machining economics problems are fuzzy numbers.     

Study on Electro Discharge Diamond Wheel Grinding (EDGM) of Ceramic Materials

This paper focuses on studying the principal of machining of ceramic materials using diamond wheel grinding and electro-discharge machining (EDM) and hence a new machining method, diamond wheel grinding with electro-discharge machining (EDGM) was proposed. This combined machining technology merges the respective advantages from diamond wheel grinding and electro-discharge machining. It can, therefore, increase the efficiency and the quality of ceramics machining. Experimental results showed that the machining efficiency of the combined machining technique is two to three times of diamond wheel grinding with the same quality surface finish.