Modeling and analysis of networked control systems using stochastic hybrid systems

This paper aims at familiarizing the reader with Stochastic Hybrid Systems (SHSs) and enabling her to use these systems to model and analyze Networked Control Systems (NCSs). Towards this goal, we introduce two different models of SHSs and a set of theoretical tools for their analysis. In parallel with the presentation of the mathematical models and results, we provide a few simple examples that illustrate the use of SHSs to models NCSs.     

Forward analysis of some special Stewart platforms

A closed forward displacement analysis is performed for a parallel mechanism where a triangular platform is joined to a hexagonal base, with two legs from each triangle vertex connected to an adjacent pair of base vertices. A new approach, based on symbolic manipulation computer techniques, is used to show there are 16 solutions for any given set of leg lengths. If the platform is an equilateral triangle, the base a hexagon with a rotational symmetry, and the legs put in two natural groups, this approach can show that one of these sets may be replaced by cables (so the leg can only “pull”), and the other set can be rods that are only under compression (we refer to this subsequently as only “push”). If the base is further constrained to be planar the rod/cable values are related by a simple equation such that once the base and platform dimensions are known a wide range of rod/cable values may be picked. In these cases it can also be proved that the chosen solutions are the only physically realizable solutions (in the non‐planar case this can only be demonstrated computationally). Examples are provided for several cases. © 2000 John Wiley & Sons, Inc.     

Modeling access control for cyber-physical systems using reputation

The emergence of Cyber-Physical Systems (CPSs) heralds the ubiquitous and autonomous globally interconnected networks of embedded devices with their own means of interaction with the physical environment. The complex interactions with the physical environment significantly increase security risks. Especially, for mission-critical CPSs, sensitive data are closely related to security issues and are accessed only by authorized users. Role based access control is an essential component for protecting CPSs from unauthorized access. However, existing mechanisms are inadequate. We argue that role assignment should not depend on the remaining energy of a node but its reputation. This paper proposes a role-based access control model, R2BAC, for CPSs using reputation. The definitions and evaluation metrics of trust and reputation are given in order to evaluate the behavior of the nodes. Then reputation evaluation scheme and role assignment scheme are presented, respectively. In addition, we give the proofs of correctness and complexity analysis for R2BAC. Eventually, a wide set of simulations are provided to evaluate its performance.     

Modeling and control of non-linear systems using soft computing techniques

This work is an attempt to illustrate the utility and effectiveness of soft computing approaches in handling the modeling and control of complex systems. Soft computing research is concerned with the integration of artificial intelligent tools (neural networks, fuzzy technology, evolutionary algorithms, …) in a complementary hybrid framework for solving real world problems. There are several approaches to integrate neural networks and fuzzy logic to form a neuro-fuzzy system. The present work will concentrate on the pioneering neuro-fuzzy system, Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is first used to model non-linear knee-joint dynamics from recorded clinical data. The established model is then used to predict the behavior of the underlying system and for the design and evaluation of various intelligent control strategies.     

Modeling and control for a Gough‐Stewart platform CNC machine

In this paper, a complete dynamic model on task space for a 6 degrees of freedom (DOF) Gough‐Stewart platform‐type computer numerical control (CNC) machine is derived. The rotation terms of the legs are included for those inertia effects cannot be negligible in the machine tool applications. The formulation derived by means of the Euler‐Lagrange method is convenient for designing the adaptive control law. Also, the average‐type force model for end milling process is derived and included in the dynamic model and control. A composite adaptive control scheme is developed by use of filtering dynamics technique. An appropriate estimator gain is designed in the parameter adaptation law that is useful for estimating the selected important cutting parameters. Experimental results verify the proposed adaptive control scheme can achieve good tracking performance. © 2004 Wiley Periodicals, Inc.     

Modeling and control of high-throughput screening systems

In previous work it has been shown how a max-plus algebraic model can be derived for cyclically operated high-throughput screening systems and how such a model can be used to design a controller to handle unexpected deviations from the predetermined cyclic operation during run-time. In this paper, this approach is extended by modeling the system in a general dioid algebraic setting. Then a feedback controller can be computed using residuation theory. The resulting control strategy is optimal in the sense of the just-in-time criterion, which is very common in scheduling practice.     

Modeling and control of cooperative teleoperation systems

This paper presents a multilateral control architecture for teleoperation in multimaster/multislave environments. The proposed framework incorporates flow of position and force information between all master and slave robots, rather than merely between corresponding units. Within this architecture, cooperative performance measures are defined to enhance coordination among the operators and the robots for achieving the task objectives. A /spl mu/-synthesis-based methodology for cooperative teleoperation control is also introduced. This approach guarantees robust stability of cooperative teleoperation in the presence of dynamic interaction between slave robots, as well as unknown passive operators and environment dynamics. It also improves task coordination by optimizing relevant performance objectives. Experiments carried out with a two-master/two-slave single-axis system demonstrate the effectiveness of the proposed approach.     

Modeling control in rule-based systems

The Comex modeling tool (control knowledge modeling and execution tool) focuses on modeling a problem-solving strategy and representing control knowledge, the knowledge of how to select among several problem-solving actions. In addition, Comex has facilities that let you execute early versions of the model to simulate the intended system's behavior and continuously execute the evolving model, until it becomes the real system. Comex addresses the rule-based paradigm's biggest shortcoming by adding control structures to executable models. Beginning with the specification phase, you can simulate a system's behavior, then map tasks to a rule base. The result is a structured, rule-based system built according to accepted software-engineering principles     

Design and optimal control of dual-stage Stewart platform using Feedback-Linearized Quadratic Regulator

Design and optimal control of a dual-stage Stewart robot is performed in this paper using sequential optimal feedback linearization method considering the dynamics of the jacks. Considering the limited length of the jacks, the possible dynamic workspace of this robot is extremely limited. Dual-stage platform version of this robot is designed and proposed in this paper to improve this limitation. As a result, the dynamic workspace of the robot is increased by increasing the degrees of freedom (DOFs) of the system. Modeling and dynamics of the new proposed system are developed considering the dynamics of the jacks. Besides, the robot is controlled with the highest accuracy and the lowest energy using an optimal control strategy based on Feedback-Linearized Quadratic Regulator (FLQR). Two sequential controlling loops are employed for simultaneous control of the joint space and work space of the robot. The efficiency of the proposed manipulator toward increasing the workspace of the robot and also the accuracy of the proposed controller are investigated using MATLAB for a dual-stage Stewart robot. The kinematics and kinetics of the robot are extracted, the proposed controller is implemented and the results are analyzed which show the efficiency of the proposed structure and controlling method.     

On the dynamic model and kinematic analysis of a class of Stewart platforms

In this paper, a dynamic model for a class of Stewart platform (six degrees of freedom parallel link robotic manipulators) is derived by using tensor representation. A set of six Lagrange's equations are obtained. The kinematics analysis for a class of Stewart platform is conducted and a sixteenth order polynomial equation corresponding to the forward kinematic solution of the Stewart platform is obtained, which gives all possible global solutions of a manipulator configuration for a given set of six leg lengths.     

Co-simulation platforms for co-design of networked control systems: An overview

This paper gives an overview of the existing co-simulation platforms for co-design of networked control systems (NCSs). NCSs contain coupled control and communication perspectives. However, the existing simulators focus either on control systems or communication networks. In order to analyse the coupling effect from both sides, co-simulation method is under consideration as one of the most promising solutions. This paper briefly introduces the commonly used individual control and communication simulators. Then the existing co-simulation platforms have been reviewed and discussed. Synchronization technique is the key point toward co-simulation, thus different synchronization methods have also been summarized. Two sample case studies with results are provided to show the beneficial of co-simulations.     

Optimal layout and reconfiguration of a fixturing system constructed from passive Stewart platforms

The distinguishing property of Reconfigurable Manufacturing Systems (RMS) is that they can rapidly and efficiently adapt to new production requirements, both in terms of their capacity and functionalities. For this type of systems to achieve the desired efficiency, it should be possible to easily and quickly setup and reconfigure all of their components. This includes fixturing jigs that are used to hold workpieces firmly in place to enable a robot to carry out the desired production processes.In this paper, we formulate a constrained nonlinear optimization problem that must be solved to determine an optimal layout of reconfigurable fixtures for a given set of workpieces. The optimization problem takes into account the kinematic limitations of the fixtures, which are built in shape of Sterwart platforms, and the characteristics of the workpieces that need to be fastened into the fixturing system. Experimental results are presented that demonstrate that the automatically computed fixturing system layouts satisfy different constraints typically imposed in production environments.     

活套关联系统建模及滚动时域控制

本文分析了热连轧活套系统下游机架轧制速度对活套张力系统的影响和热连轧多机架协同工作的特性,建立了活套关联系统模型;基于分散控制思想,为每个活套系统单独设计控制器.对于每一个活套子系统,活套高度和张力是强耦合系统,本文采用一类基于滚动时域优化原理的多路控制策略,在每个周期内顺序求解活套高度和张力子系统的控制律后及时更新系统,从H∞观点出发,将解耦问题转化为干扰抑制和多目标优化问题.仿真结果证实了该方法具有良好的解耦效果和控制特性.     

Modeling and control of drug assignment for pharmaceutical cabinets using discrete event systems approaches

The public health sector, considered to be vital, especially in this pandemic crisis of COVID-19, requires automation and control of drug distribution in pharmacies commonly called: “Dispensing.” In this paper, we address the medication assignment problem for automated dispensing cabinets (ADCs). First, we use a network of conflicting timed event graphs (CTEGs), a class of timed Petri nets with shared resources, to model pharmaceutical cabinets. Second, we develop a new method for controlling CTEGs under mutual exclusion constraints (MECs) to solve the problem of drug assignment, using a control approach based on Min-Plus algebra. Finally, a case study of assigning drugs is given to illustrate the proposed methodology and show the efficiency of the developed control laws.     

Modeling and control of fuzzy discrete event systems

In order to make it possible to effectively represent deterministic uncertainties and vagueness as well as the human subjective observation and judgement inherent to many real-world problems, especially those in biomedicine, we introduce, in this paper, fuzzy states and fuzzy events and generalize (crisp) discrete event systems (DES) to fuzzy DES. The largely graph-based current framework of the crisp DES is unsuitable for the expansion, and we have thus reformulated it using state vectors and event transition matrices which can be extended to fuzzy vectors and matrices by allowing their elements to take values between 0 and 1. To measure information related to fuzzy DES, we generalize the crisp DES observability. The new observability allows one to determine whether or not the system output observed is sufficient for decision making. Finally, we extend the optimal control of DES to fuzzy DES. The new fuzzy DES theory is consistent with the existing theory, both at the conceptual and the computation levels, in that the former contains the latter as a special case when the memberships must be either 0 or 1. Numerical examples are provided to illustrate the theoretical development.     

变采样网络控制系统的建模与分析

在变采样网络控制系统中采用事件—时间驱动方式,同时在使用预测控制值和预测反馈值的情况下,给出了各种网络时延所对应的网络控制系统的状态转移矩阵,最后分析了变采样网络控制系统稳定需要的条件。     

MIMO网络控制系统的建模与分析

针对网络只存在于传感器节点与控制器节点之间的多输入多输出(MIMO)网络控制系统,研究了系统建模和稳定性问题.设传感器节点和控制器节点均为时间驱动,且它们的采样存在着固定的时间差,网络诱导时延的上界大于一个采样周期,建立了此类网络控制系统的模型.基于Lyapunov函数和线性矩阵不等式(LMIs)方法,给出了闭环系统渐近稳定的充分条件.仿真表明本文的方法是有效的.