UNCERTAIN BANG-BANG CONTROL FOR CONTINUOUS TIME MODEL

By using the equation of optimality in uncertain optimal control, an uncertain bang-bang control problem for a continuous time model is investigated. An example is given to illustrate the result obtained.     

一类不确定非完整动力学系统的鲁棒镇定及其在移动机器人中的应用

本文讨论了一类带有未知惯性参数、动静态摩擦及外界干扰的非完整动力学系统的控制问题．基于变结构控制的思想，给出了该系统的镇定方法，使得Ｐｏｍｅｔ［３］关于非完整运动学系统的时变光滑镇定律可推广到相应的带有参数不确定和干扰的动力学系统上．最后，将所得结果应用于一类移动机器人的镇定控制，仿真结果验证了该方法的有效性．     

一类含参数不确定性混沌系统的控制

给出一类含参数不确定性混沌系统的控制器设计方法 .用该方法设计的控制器 ,能够使系统消除混沌并鲁棒渐近稳定到任何期望的光滑轨道 .设计过程无需预先知道未知参数的估计值和精确值 .直接构造混沌控制器 ,方法简单 .仿真验证了其有效性     

多专家AHP的算法改进及其在供应商选择模型中的应用

本文以集成供应链管理(ISCM)软件开发项目为背景,重点研究多专家层次分析法在供应商选择模型中的应用问题。首先提出一种改进的多专家层次分析法,其软件实现更为安全稳健;进而建立供应商选择软件的UML功能模型,给出该方法在供应商选择中的具体应用;最后通过一个应用实例来验证软件运行的有效性。     

不确定多变量系统控制的多模型设计方法及其在造纸机控制中的应用

本文用有限个时不变模型描述不确定多变量系统,给出了一种鲁棒控制器频域设计方法,使得由控制器和任一模型构成的单位反馈系统都达到闭环的稳定性、渐近调节和跟踪、弱相互耦合以及期望的瞬态特性.该方法应用于造纸机的多种纸张的定量和水份控制,获得了令人满意的效果.     

参数不确定性柔性机械手控制的一种简单方法

本文讨论了具有模型不确定性的柔性机械手运动控制问题,给出了一种基于差分方程 和最小二乘法的控制器设计方法．在快速采样的条件下,难于建模的不确定项可以直接忽略 而不影响控制效果．通过一个柔性机械手的仿真表明,本文提出的控制方法可实现柔性机械 手轨迹的准确跟踪,同时能消除柔性机械手的弹性振动．     

视频编码中考虑模式选择的位率优化控制

本文在传统位率控制方法的基础上提出一种新算法,即基于宏块的最佳位率控制算法．主要思想是在考虑还宽,比特率和缓冲区大小的同时,考虑不同宏块模式的选择对位率的影响,文中给出了一些相关结果并将其与传统方法所得数据相比较,结果表明在多数位率条件下用本算法得到的ＰＳＮＲ比传统方法要好．     

具有状态和控制滞后不确定系统的保性能控制器设计

1　引言本文的目的在于将文献 [1 ]的结论推广到同时具有状态和控制滞后的不确定系统 ,并进而研究其最优保性能控制问题 .考虑具有状态和控制滞后的不确定系统x( t) =[A DF( t) E1 ] x( t) [Ad DF( t) Ed] x( t-d) [B DF( t) E2 ] u( t) [Bh DF( t) Eh]《u》( t-     

一种新的位置数据融合方法的研究

给出了一新的基于团队一致法的多传感器位置数据融合方法，该方法按传感器队中的每个成员的测量不确定性，构造团队期望效用函数（或密度），并基于该期望效用函数求得位置参数估计，其优点是可消除失效传感器和测量值为野值的传感器的影响，本文给出了仿真结果。     

A STABLE SELF-LEARNING OPTIMAL FUZZY CONTROL SYSTEM

The issue of developing a stable self-learning optimal fuzzy control system is discussed in this paper. Three chief objectives are accomplished: 1) To develop a self-learning fuzzy controller based on genetic algorithms. In the proposed methodology, the concept of a fuzzy sliding mode is introduced to specify the system response, to simplify the fuzzy rules and to shorten the chromosome length. The speed of fuzzy inference and genetic evolution of the proposed strategy, consequently, is higher than that of the conventional fuzzy logic control. 2) To guarantee the stability of the learning control system. A hitting controller is designed to achieve this requirement. It works as an auxiliary controller and supports the self-learning fuzzy controller in the following manner. When the learning controller works well enough to allow the system state to lie inside a pre-defined boundary layer, the hitting controller is disabled. On the other hand, if the system tends to diverge, the hitting controller is turned on to pull the state back. The system is therefore stable in the sense that the state is bounded by the boundary layer. 3) To explore a fuzzy rule-base that can minimize a standard quadratic cost function. Based on the fuzzy sliding regime, the problem of minimizing the quadratic cost function can be transformed into that of deriving an optimal sliding surface. Consequently, the proposed learning scheme is directly applied to extract the optimal fuzzy rulebase. That is, the faster the hitting time a controller has and the shorter the distance from the sliding surface the higher fitness it possesses. The superiority of the proposed approach is verified through simulations.     

冗余度机器人全局优化的一种新方法

提出一种冗余度机器人全局优化的新方法．通过引入自运动变量,为冗余度机器人全局优化问题建立了一个简单泛函极值模型,并由此导出了响应的全局优化算法．这种方法建模简单,计算量小,能实现冗余度机器人全局优化的实时控制．     

MULTIVARIABLE FUZZY GENERALIZED PREDICTIVE CONTROL

A Takagi-Sugeno (T-S) fuzzy model is used to express non-linear dynamic systems with time-delay in this paper, and an on-line identification algorithm is presented regarding its parameters and structures. A multivariable fuzzy generalized predictive control approach is proposed based on the identified fuzzy model by means of the generalized predictive control principle. The closed-loop stability is analyzed in detail. A simulation study for the multivariable load system of a boiler-turbine unit shows that the approach is superior to convention load control systems.     

MODEL SET IDENTIFICATION IN FREQUENCY-DOMAIN AND ITS APPLICATION TO JOINT DESIGN WITH ROBUST CONTROL

In this paper, we propose a new model set identification method for robust control, which determines both nominal models and uncertainty bounds in frequency-domain using periodgrams obtained from experimental data. This method also gives less conservative model sets when we have more experimental data, which is one of the distinguished features compared with the existing model set identification methods. To this end, first, we construct a new noise model set in terms of periodgrams, which consists of hard-bounded (or deterministic) noises but takes account of a low correlation property of noise signals, simultaneously. Then, based on the noise model, we show how to compute the nominal models and the upper bounds of modeling error via convex optimization, which minimize given cost functions. Furthermore, by introducing a weighting function compatible with control performance criterion into the identification cost function, we consider a joint design method of the proposed model set identification and H_∞ control. Numerical examples show the effectiveness of the proposed method.     

一般模型控制(GMC):一种简单实用的非线性过程控制新方法

一般模型控制是１９８８年以来发展起来的一种非线性过程控制方法，此方法具有简单衫，鲁棒性强的特点，而其控制效果却与微分几合方法相类似，因此在过去的和年此方法得到广泛的应用，本文综述了此方法的发展状况，并指出了尚待的若干问题。     

SMOOTH SLIDING CONTROL OF UNCERTAIN SYSTEMS BASED ON A PREDICTION ERROR

This paper addresses the problem of designing sliding control of uncertain systems which are free of chattering and result in smooth control signals. Both state and output feedback are considered. The proposed approach relies on some appropriate prediction error and can be easily applied to modify the usual state feedback VSC for chattering avoidance. It can also be applied for devising new output feedback VSC laws. The robustness improvement, with respect to unmodelled dynamics, even allows one to reconsider the so far rejected utilization of approximate differentiators for VSC output feedback. The theoretical results are illustrated by simulations. An experimental evaluation is briefly discussed. © 1997 by John Wiley & Sons, Ltd.     

可控性差的空间密集模态结构的振幅最优控制

研究可控性差的空间密集模态结构的控制问题,提出了一种最优控制方案,在适当配置系统极点的同时,优化可控性差的模态的振幅.目标函数的寻优采用具有全局搜索能力的遗传算法.为适应不确知的初始状态,也提出一种模型参考自适应机制,用来在线跟踪振幅最优控制,自适应控制系统的稳定性得到证明.仿真结果表明了所提出控制方法的有效性.     

NONLINEAR OPTIMAL CONTROL: A CONTROL LYAPUNOV FUNCTION AND RECEDING HORIZON PERSPECTIVE

Two well known approaches to nonlinear control involve the use of control Lyapunov functions (CLFs) and receding horizon control (RHC), also known as model predictive control (MPC). The on-line Euler-Lagrange computation of receding horizon control is naturally viewed in terms of optimal control, whereas researchers in CLF methods have emphasized such notions as inverse optimality. We focus on a CLF variation of Sontag's formula, which also results from a special choice of parameters in the so-called pointwise minnorm formulation. Viewed this way, CLF methods have direct connections with the Hamilton-Jacobi-Bellman formulation of optimal control. A single example is used to illustrate the various limitations of each approach. Finally, we contrast the CLF and receding horizon points of view, arguing that their strengths are complementary and suggestive of new ideas and opportunities for control design. The presentation is tutorial, emphasizing concepts and connections over details and technicalities.     

PROBLEMS ON FEEDBACK CONTROL OF UNCERTAIN SYSTEMS: A THEORETICAL INTERPRETATION†

Abstract

The main problem in control theory is the definition of the optimal control law that must be applied to a physical system in order to obtain a desired behaviour. A general approach to this problem is developed, in order to explain the consideration of Rapoport that: “.feedback loops suggest that information is somehow fed into the system, or that the system obtains information about itself.” To this extent, the meanings of “system” and approximating “model” are properly clarified. The correct use of an observer, as the device which measures the uncertainty about the internal structure of the system and about the environmental influences on the system itself, is defined. The concept of “equilibrium” of a controlled system is introduced and some necessary and sufficient conditions in order that such an equilibrium may be reached, are stated.     

奇异最优控制和负载观测器在直流随动系统中的应用

本文就电随动系统的奇异最优控制问题作了进一步的研究.考虑了负载力矩对于最优控制律的影响,采用观测器对分段常值型未知负载力矩进行估值,并据此在线修正最优开关曲线,从而使系统具有适应性.