Semi-heterarchical control of FMS: From theory to application

This paper presents both a model and a real implementation of a semi-heterarchical control system for flexible manufacturing systems (FMS). After presenting the concepts of heterarchical and semi-heterarchical control, a product-based control structure, composed of a dynamic allocation process (DAP) and a dynamic routing process (DRP), is proposed. Though the associated control processes (DAP and DRP) are hierarchically dependant, each is managed heterarchically, with no supervisor. The dynamic allocation algorithms are presented, and our highly distributed approach to routing control is then explained in detail. A real distributed application of the active entities and the control architecture was implemented in the AIP-PRIMECA pole at the University of Valenciennes, and this implementation is described in detail. A mixed-integer linear model of the FMS was used to compute lower bounds. The flexibility and robustness of our approach are highlighted through several real experiments.     

Game theory approach to optimal control problem with multi-channel control

In this paper, we mainly study the optimal control problem with multi-channel control. The main contribution is to treat the optimal control problem as a leader-follower problem with multi-hierarchy decision makers in game theory. According to the sequence of the decision makers, the optimal controller is derived by the maximum principle. It is worth mentioning that the optimal solution is in the feedback form related to two symmetric Riccati equations with same dimension as the original state. Furthermore, the obtained solution is sufficient and necessary.     

Multidimensional behaviours: an algebraic approach to control theory for PDE

This paper gives an overview of the algebraic theory of multidimensional behaviours, and it contains some new aspects as well. Some known results are restated with a new proof. After a short introduction to behavioural systems theory, we briefly describe the mathematical background of the algebraic approach. Then we study structural properties such as autonomy and over-determined systems on the one hand, and controllability and flat systems on the other.     

On implicit modelling theory: Basic concepts and application to adaptive control

The paper aims at presenting a unifying theory regarding the so-called “implicit models”. In adaptive control theory, this term commonly indicates system models which do not correspond to the true one, although they convey all the necessary information for the synthesis of the optimal controller, and are simpler to be identified. In the paper, ARX implicit models are considered and their possible use in adaptive control algorithms based on LQ or pole assignment control criteria is discussed.     

LF炉电极控制原理及应用

LF炉是目前最广泛应用的炉外精炼设备之一,LF炉的主要任务包括脱氧、脱硫、去气、去夹杂物、升温并调整出钢温度,合金化并调整钢水化学成分。电极调节是LF炉冶炼的关键技术,本文介绍攀钢方坯连铸LF炉电极控制系统的结构及原理,详细描述了系统的调节模式。     

A learning theory approach to system identification and stochastic adaptive control

In this paper, we present an approach to system identification based on viewing identification as a problem in statistical learning theory. Apparently, this approach was first mooted in [E. Weyer, R.C. Williamson, I. Mareels, Sample complexity of least squares identification of FIR models, in: Proceedings of the 13th World Congress of IFAC, San Francisco, CA, July 1996, pp. 239–244]. The main motivation for initiating such a program is that traditionally system identification theory provide asymptotic results. In contrast, statistical learning theory is devoted to the derivation of finite-time estimates. If system identification is to be combined with robust control theory to develop a sound theory of indirect adaptive control, it is essential to have finite-time estimates of the sort provided by statistical learning theory. As an illustration of the approach, a result is derived showing that in the case of systems with fading memory, it is possible to combine standard results in statistical learning theory (suitably modified to the present situation) with some fading memory arguments to obtain finite-time estimates of the desired kind. It is also shown that the time series generated by a large class of BIBO stable nonlinear systems has a property known as β-mixing. As a result, earlier results of [E. Weyer, Finite sample properties of system identification of ARX models under mixing conditions, Automatica, 36 (9) (2000) 1291–1299] can be applied to many more situations than shown in that paper.     

Walsh transform theory and its application to systems analysis and control: an overview

The purpose of this paper is to provide an overview of the works dealing with the application and utilization of Walsh function series and transforms to a variety of systems and control applications. The works reviewed are classified in the following groups: 1. Walsh signal definition and generation, 2. Walsh transform Computation, 3. System analysis using Walsh functions, 4. System identification via Walsh functions, 5. Optimal control via Walsh functions, 6. Block-pulse functions, 7. Miscellaneous properties of Walsh functions, 8. Walsh-to-Fourier transform conversion, and 9. Walsh transform applications.     

An optimal graph theoretic approach to data clustering: theory andits application to image segmentation

A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph 𝒢 with arc capacities assigned to reflect the similarity between the linked vertices. Clustering is achieved by removing arcs of 𝒢 to form mutually exclusive subgraphs such that the largest inter-subgraph maximum flow is minimized. For graphs of moderate size (~ 2000 vertices), the optimal solution is obtained through partitioning a flow and cut equivalent tree of 𝒢, which can be efficiently constructed using the Gomory-Hu algorithm (1961). However for larger graphs this approach is impractical. New theorems for subgraph condensation are derived and are then used to develop a fast algorithm which hierarchically constructs and partitions a partially equivalent tree of much reduced size. This algorithm results in an optimal solution equivalent to that obtained by partitioning the complete equivalent tree and is able to handle very large graphs with several hundred thousand vertices. The new clustering algorithm is applied to the image segmentation problem. The segmentation is achieved by effectively searching for closed contours of edge elements (equivalent to minimum cuts in 𝒢), which consist mostly of strong edges, while rejecting contours containing isolated strong edges. This method is able to accurately locate region boundaries and at the same time guarantees the formation of closed edge contours     

A population approach to cortical dynamics with an application to orientation tuning

A typical functional region in cortex contains thousands of neurons, therefore direct neuronal simulation of the dynamics of such a region necessarily involves massive computation. A recent efficient alternative formulation is in terms of kinetic equations that describe the collective activity of the whole population of similar neurons. A previous paper has shown that these equations produce results that agree well with detailed direct simulations. Here we illustrate the power of this new technique by applying it to the investigation of the effect of recurrent connections upon the dynamics of orientation tuning in the visual cortex. Our equations express the kinetic counterpart of the hypercolumn model from which Somers et al (Somers D, Nelson S and Sur M 1995 J. Neurosci. 15 5448-65) computed steady-state cortical responses to static stimuli by direct simulation. We confirm their static results. Our method presents the opportunity to simulate the data-intensive dynamical experiments of Ringach et al (Ringach D, Hawken M and Shapley R 1997 Nature 387 281-4), in which 60 randomly oriented stimuli were presented each second for 15 min, to gather adequate statistics of responses to multiple presentations. Without readjustment of the previously defined parameters. our simulations yield substantial agreement with the experimental results. Our calculations suggest that differences in the experimental dynamical responses of cells in different cortical layers originate from differences in their recurrent connections with other cells. Thus our method of efficient simulation furnishes a variety of information that is not available from experiment alone.     

Modal control theory and industrial dynamics — a dual approach to the design of policy decisions in a multistage production-inventory system

This paper deals with the problem of designing realistic policy decisions in a Multistage Production-Inventory System (MPIS). First Modal Control Theory has been utilised for the synthesis of control policies in a two-stage production-inventory system. The structure of the resultant control policies, though somewhat idealised, has an underlying implication of central control. Two types of realistic policy decisions are made and tested in Forresters's ID simulation study of the MPIS. It is shown that both the policies result in more attenuated system behaviour than that obtained by Forrester.     

An iterative learning approach to formation control of multi-agent systems

In this paper, an efficient framework is proposed to the formation control problem of multiple agents with unknown nonlinear dynamics, by means of the iterative learning approach. In particular, a distributed D-type iterative learning scheme is developed for the multi-agent system with switching topology, whose switching time and sequence are allowed to be varied at different iterations according to the actual trajectories of agents, and a sufficient condition is derived to ensure that the desired formation can be always preserved from the initial starting location to the final one after some iterations. Simulation results are provided to verify the effectiveness of the proposed approach.     

Resource management in network dynamics: An optimal approach to the admission control problem

This paper presents an innovative procedure to solve the Connection Admission Control Problem for a telecommunication network. Here, this important problem in the context of Communication Theory and Network Dynamics is dealt with by imbedding it in the framework of System and Control Theory. Highlights of the procedure are technology independence, coordinated and coherent decoupling, optimality and feedback properties, stochastic dynamic control.     

采用TD3100变频器实现的高精度定位控制的几种方法

本文提出采用TD3100电梯专用矢量控制变频器实现的高精度定位控制的几种方法,重点论述了该系统的原理及应用实例。     

An application of fuzzy set theory to inventory control models

A method for solving an inventory control problem, of which input data are described by triangular fuzzy numbers will be presented here. The continuous review model of the inventory control problem with fuzzy input data will be focused in, and a new solution method will be presented. For the reason that the result should be a fuzzy number because of fuzzy input data, and the certain number about order quantity is prefered in the real-world, it is necessary to transform the fuzzy result to crisp one. The interval mean value concept is used here to help to solve this problem. Under the condition of total cost minimum, the interval order quantity maximum can be obtained.     

A switched-system approach to formation control and heading consensus for multi-robot systems

This paper proposes a novel, hybrid and decentralized, switched-system approach for formation and heading consensus control of mobile robots under switching communication topology, including collision avoidance capability. The set of robots consists of nonholonomic wheeled mobile robots and can include a teleoperated UAV. The key feature of this approach is a virtual graph, which is derived by adding a set of relative translation vectors to the real graph of the multiple robots. Our approach results in the robots in the real graph moving to the desired formation and achieving heading consensus while the virtual robots on the virtual graph reach pose consensus. If any robot detects a nearby obstacle or other robot, the robot will temporarily move along an avoidance vector, which is perpendicular and positively projected onto the attractive vector, such that collision is avoided while minimally deviating from its formation control path. Experimental results are provided by two different research groups to demonstrate the effectiveness of our approach. These experiments extend the theoretical development by introducing a teleoperated quadrotor as a leader robot of the multi-robot systems. The same control law works for the extended system, with no modifications.     

基于混沌理论的控制系统及应用

介绍了混沌的概念及发展概况,在分析混沌现象的特点的基础上介绍了混沌控制的方法,论述了混沌理论的应用现状,展望了混沌控制的发展应用前景。     

量子分子动力学中的操纵技术及其系统控制理论

回顾了量子操纵技术在分子化学动力学控制中的发展历程及其技术的分类与效果,并就不同操纵技术的原理以及实现上的特点进行了分析和对比,其中包括:频域中的π脉冲动力学法和干涉路径控制方案,时域中的激光脉冲成型操纵技术,继而对宏观控制理论在分子化学动力学控制中的发展状况给予逐一的阐述及评价,包括系统建模、分析与综合、几何控制、幺正演化矩阵控制、最优控制、基于李雅普诺夫方法的控制等.对全面了解量子化学中动力学操纵技术及其控制理论的应用提供一个全方位的综述.     

Virtual target tracking of mobile robot and its application to formation control

A virtual target tracking approach is proposed for kinematic control of mobile robot. In the controller, linear and angular velocity inputs are generated by using the local data of robot position and orientation along with the estimated velocity of target object. Applying the proposed approach to a cooperative robot group with arbitrary number of multiple mobile robots, it is possible to create various robot formations for cooperative navigation and tracking of moving object. The developed controller is shown to be stable and convergent through theoretical proof and a series of experiments.