含有不灵敏区非线性系统的增益调度自适应变结构控制

针对具有控制输入不灵敏区及有界不确定性的非线性系统,采用增益调度变结构控制策略,研究其镇定问题.利用增益调度策略和自适应参数估计方法,在同时存在参数、结构及干扰的不确定性和未知控制输入不灵敏区的情形下,提出了新的增益调度自适应变结构镇定控制律设计方法,既节省了控制能量,又消除了控制信号的颤振.所提出的控制律可以保证闭环输出为一致终结有界,并且算法比较简单,便于实现.用数字仿真方法验证了所得控制律设计方法的有效性.     

多型号变加载磨合试验装置测控系统研究

针对多型号某传动机构的变加载磨合试验需求,研究了变加载磨合试验的相关技术,给出了一种双路传动链的磨合试验装置的构建及其实现方法。测控系统采用主从式控制模式,主机为工控机辅以多功能数据采集卡,用于磨合作业的调度、数据处理及人机交互等;从机为西门子Simotion D410运动控制系统,通过TCP/IP通信方式接收主机的数据指令,完成对磨合作业运动任务的控制。     

基于精英进化导向的多目标PID参数优化

在多目标优化问题中,决策者必须对Pareto前沿的众多非劣解做出选择.本文将决策偏好融入Pareto优化过程,提出一种基于精英导向机制的多目标遗传算法,根据决策偏好选择Pareto最优解为精英,利用无损有限精度法和归一增量距离保持种群多样性,通过多种群进化机制将决策偏好的影响传播到整个种群.该方法成功应用于自动导引车(AGV)伺服系统的PID参数优化,可根据决策偏好快速有效地定向搜索Pareto最优解,保证伺服控制达到路径跟踪要求的速度响应性能.     

水下定位系统传感器安装误差标定技术研究

提出了一种基于非线性参数估计的水下定位系统传感器安装误差标定技术.水下定位系统由声学传感器,GPS和船体姿态传感器组成,各传感器的坐标系并不能完全重合,需要对传感器之间的误差标定后进行修正才能够获得高精度的定位效果.已有的标定方法多基于高斯-牛顿迭代法,而当非线性系统模型线性化带来较大误差时,常规的基于高斯-牛顿迭代法的标定方法已无法达到高精度的要求,而非线性模型参数估的直接解法则掺人了三阶量,有效减小线性化的模型误差,提高了各传感器安装误差的标定精度.海试数据处理表明:定位精度可由1 m提高到0.7 m.     

基于遗传算法的锅炉水温PID控制寻优

遗传算法相比传统调节方法具有更好的鲁棒性和最优性。结合锅炉动态水温单回路控制系统的PID参数整定与优化问题,采用遗传算法对其参数进行优化。仿真结果表明,这种优化算法加快了收敛速度,有效提高了系统的全局稳定性,增强了PID控制器的鲁棒性。     

Bayesian projection approaches to variable selection in generalized linear models

A Bayesian approach to variable selection which is based on the expected Kullback-Leibler divergence between the full model and its projection onto a submodel has recently been suggested in the literature. For generalized linear models an extension of this idea is proposed by considering projections onto subspaces defined via some form of L₁ constraint on the parameter in the full model. This leads to Bayesian model selection approaches related to the lasso. In the posterior distribution of the projection there is positive probability that some components are exactly zero and the posterior distribution on the model space induced by the projection allows exploration of model uncertainty. Use of the approach in structured variable selection problems such as ANOVA models is also considered, where it is desired to incorporate main effects in the presence of interactions. Projections related to the non-negative garotte are able to respect the hierarchical constraints. A consistency result is given concerning the posterior distribution on the model induced by the projection, showing that for some projections related to the adaptive lasso and non-negative garotte the posterior distribution concentrates on the true model asymptotically.     

Modeling data envelopment analysis by chance method in hybrid uncertain environments

This article first presents several formulas of chance distributions for trapezoidal fuzzy random variables and their functions, then develops a new class of chance model (C-model for short) about data envelopment analysis (DEA) in fuzzy random environments, in which the inputs and outputs are assumed to be characterized by fuzzy random variables with known possibility and probability distributions. Since the objective and constraint functions contain the chance of fuzzy random events, for general fuzzy random inputs and outputs, we suggest an approximation method to compute the chance. When the inputs and outputs are mutually independent trapezoidal fuzzy random variables, we can turn the chance constraints and the chance objective into their equivalent stochastic ones by applying the established formulas for the chance distributions. In the case when the inputs and the outputs are mutually independent trapezoidal fuzzy random vectors, the proposed C-model can be transformed to its equivalent stochastic programming one, in which the objective and the constraint functions include a number of standard normal distribution functions. To solve such an equivalent stochastic programming, we design a hybrid algorithm by integrating Monte Carlo (MC) simulation and genetic algorithm (GA), in which MC simulation is used to calculate standard normal distribution functions, and GA is used to solve the optimization problems. Finally, one numerical example is presented to demonstrate the proposed modeling idea and the efficiency in the proposed model.     

A new design of delay‐dependent robust ℋ︁∞ filtering for continuous‐time polytopic systems with time‐varying delay

This paper revisits the problem of delay‐dependent robust ?_∞ filtering design for a class of continuous‐time polytopic linear systems with a time‐varying state delay. Based on a newly developed parameter‐dependent Lyapunov–Krasovskii functional combined with Projection Lemma and an improved free‐weighting matrix technique for delay‐dependent criteria, a new sufficient condition for robust ?_∞ performance analysis is first derived and then the filter synthesis is developed by using a simple matrix inequality linearization technique. It is shown that the desired filters can be constructed by solving a set of linear matrix inequalities. Finally, two simulation examples are given to show the effectiveness and less conservatism of the proposed method in comparison with the existing approaches. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust MIMO disturbance observer analysis and design with application to active car steering

A multi‐input–multi‐output extension of the well‐known two control degrees‐of‐freedom disturbance observer architecture that decouples the problem into single‐input–single‐output disturbance observer loops is presented in this paper. Robust design based on mapping D‐stability and the frequency domain specifications of weighted sensitivity minimization and phase margin bound to a chosen controller parameter space is presented as a part of the proposed design approach. The effect of the choice of disturbance observer Q filter on performance is explained with a numerical example. This is followed by the use of structured singular values in the robustness analysis of disturbance observer controlled systems subject to structured, real parametric and mixed uncertainty in the plant. A design and simulation study based on a four wheel active car steering control example is used to illustrate the methods presented in the paper. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust delay‐dependent guaranteed cost controller design for uncertain nonlinear neutral systems with time‐varying state delays

In this paper, the problem of robust delay‐dependent guaranteed cost control for uncertain nonlinear neutral systems with time‐varying state delay is investigated. The control law is chosen to be a memoryless type one. Neither any model transformation nor bounding of any cross terms are utilized. The system under consideration may be subjected to both norm‐bounded uncertainties and nonlinear parameter perturbations. A delay‐dependent sufficient condition is obtained in terms of a matrix inequality for which a cone complementarity problem is introduced to provide a feasible solution set. Two numerical examples have been demonstrated to show the effective application of the proposed method. Copyright © 2009 John Wiley & Sons, Ltd.