Volume 2, Number 2, 2005

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Regular Papers
H State Feedback Delay-dependent Control for Discrete Systems with Multi-time-delay
2005, vol. 2, no. 2, pp. 107-113, doi: 10.1007/s11633-005-0107-0
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Abstract:
In this paper, H state feedback control with delay information for discrete systems with multi-time-delay is discussed. Making use of linear matrix inequality (LMI) approach, a time-delay-dependent criterion for a discrete system with multi-time-delay to satisfy H performance indices is induced, and then a strategy for H state feedback control with delay values for plant with multi-time-delay is obtained. By solving corresponding LMI, a delay-dependent state feedback controller satisfying H performance indices is designed. Finally, a simulation example demonstrates the validity of the proposed approach.
An Analysis of the Inverse Kinematics for a 5-DOF Manipulator
De Xu, Carlos A. Acosta Calderon, John Q. Gan, Huosheng Hu, Min Tan
2005, vol. 2, no. 2, pp. 114-124, doi: 10.1007/s11633-005-0114-1
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Abstract:
In this paper, H state feedback control with delay information for discrete systems with multi-time-delay is discussed. Making use of linear matrix inequality (LMI) approach, a time-delay-dependent criterion for a discrete system with multi-time-delay to satisfy H performance indices is induced, and then a strategy for H state feedback control with delay values for plant with multi-time-delay is obtained. By solving corresponding LMI, a delay-dependent state feedback controller satisfying H performance indices is designed. Finally, a simulation example demonstrates the validity of the proposed approach.
Adaptive Air-Fuel Ratio Control with MLP Network
Shi-Wei Wang, Ding-Li Yu
2005, vol. 2, no. 2, pp. 125-133, doi: 10.1007/s11633-005-0125-y
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Abstract:
This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC.
Multi-Modal Reasoning Medical Diagnosis System Integrated With Probabilistic Reasoning
Jia Tian, Xun Chen, Sheng-Ping Dong
2005, vol. 2, no. 2, pp. 134-143, doi: 10.1007/s11633-005-0134-x
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Abstract:
In this paper, a Multi Modal Reasoning (MMR) method integrated with probabilistic reasoning is proposed for the diagnosis support module of the open eHealth platform. MMR is based on both Rule Based Reasoning (RBR) and Case Based Reasoning (CBR). It is not only applied to the identification of diseases and syndromes based on medical guidelines, but also deals with exceptional cases and individual therapies in order to improve diagnostic accuracy. Moreover, a new rule expression frame is introduced to deal with uncertainty, which can represent and process vague, imprecise, and incomplete information. Furthermore, this system is capable of updating the attributes of rules and inducing rules with a small data sample.
A Hierarchical Framework for Visualising and Simulating Supply Chains in Virtual Environments
Hai-Yan Zhang, Zheng-Xu Zhao
2005, vol. 2, no. 2, pp. 144-154, doi: 10.1007/s11633-005-0144-8
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Abstract:
This paper presents research into applying virtual environment (VE) technology to supply chain management (SCM). Our research work has employed virtual manufacturing environments to represent supply chain nodes to simulate processes and activities in supply chain management. This will enable those who are involved in these processes and activities to gain an intuitive understanding of them, so as to design robust supply chains and make correct decisions at the right time. A framework system and its hierarchical structure for visualising and simulating supply chains in virtual environments are reported and detailed in this paper.
Formal Verification of the Merchant Registration Phase of the SET Protocol
Xiao-Qi Ma, Xiao-Chun Cheng
2005, vol. 2, no. 2, pp. 155-162, doi: 10.1007/s11633-005-0155-5
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Abstract:
This paper describes the formal verification of the Merchant Registration phase of the Secure Electronic Transactions (SET) protocol, a realistic electronic transaction security protocol which is used to protect the secrecy of online purchases. A number of concepts, notations, functions, predicates, assumptions and rules are introduced. We describe the knowledge of all legal participants, and a malicious spy, to assess the security of the sub-protocol. Avoiding search in a large state space, the method converges very quickly. We implemented our method in the Isabelle/Isar automated reasoning environment, therefore the whole verification process can be executed mechanically and efficiently.
An Orthogonal Least Squares Based Approach to FIR Designs
Xiao-Feng Wu, Zi-Qiang Lang, Stephen A Billings
2005, vol. 2, no. 2, pp. 163-170, doi: 10.1007/s11633-005-0163-5
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Abstract:
This paper is concerned with the application of forward Orthogonal Least Squares (OLS) algorithm to the design of Finite Impulse Response (FIR) filters. The focus of this study is a new FIR filter design procedure and to compare this with traditional methods known as the fir2() routine provided by MATLAB.
Power System Aggregate Load Area Modelling by Particle Swarm Optimization
Jian-Lin Wei, Ji-Hong Wang, Q. H. Wu, Nan Lu
2005, vol. 2, no. 2, pp. 171-178, doi: 10.1007/s11633-005-0171-5
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Abstract:
This paper presents a new approach for deriving a power system aggregate load area model (ALAM). In this approach, an equivalent area load model is derived to represent the load characters for a particular area load of a power system network. The Particle Swarm Optimization (PSO) method is employed to identify the unknown parameters of the generalised system, ALAM, based on the system measurement directly using a one-step scheme. Simulation studies are carried out for an IEEE 14-Bus power system and an IEEE 57-Bus power system. Simulation results show that the ALAM can represent the area load characters accurately under different operational conditions and at different power system states.
Application of Full-Order and Simplified EKFs to Sensorless PM Brushless AC Machines
Xi Zhu, Zi-Qiang Zhu, David Howe
2005, vol. 2, no. 2, pp. 179-186, doi: 10.1007/s11633-005-0179-x
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Abstract:
This paper employs an extended Kalman filter (EKF) to estimate the rotor position and speed of a vector controlled surface-mounted permanent magnet (PM) brushless AC (BLAC) motor from measured terminal voltages and currents only. Both full-order and simplified EKFs are employed and their simulated performance capabilities are compared. Excellent agreement is achieved between estimated and commanded results. The EKF is also employed to identify the stator flux-linkage due to the PMs, which is influenced by temperature variation and magnetic saturation.
Modeling Delay and Packet Drop in Networked Control Systems Using Network Simulator NS2
Mohammad Shahidul Hasan, Christopher Harding, Hongnian Yu, Alison Griffiths
2005, vol. 2, no. 2, pp. 187-194, doi: 10.1007/s11633-005-0187-x
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Abstract:
Wireless Networked Control Systems (WNCS) are used to implement a control mechanism over a wireless network that is capable of carrying real-time traffic. This field has drawn enormous attention from current researchers because of its flexibility and robustness. However, designing efficient WNCS over Mobile Ad Hoc Networks (MANET) is still a challenging topic because of its less-predictable aspects, such as inconsistent delay, packet drop probability, and dynamic topology. This paper presents design guidelines for WNCS over MANET using the Network Simulator version 2, NS2 software. It investigates the impact of packet delay and packet drop under the AODV and DSR routing protocols. The simulation results have been compared to MATLAB results for validation.
CA-PLAN, a Service-Oriented Workflow
Shung-Bin Yan, Feng-Jian Wang
2005, vol. 2, no. 2, pp. 195-207, doi: 10.1007/s11633-005-0195-x
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Abstract:
Workflow management systems (WfMSs) are accepted worldwide due to their ability to model and control business processes. Previously, we defined an intra-organizational workflow specification model, Process LANguage (PLAN). PLAN, with associated tools, allowed a user to describe a graph specification for processes, artifacts, and participants in an organization. PLAN has been successfully implemented in Agentflow to support workflow (Agentflow) applications. PLAN, and most current WfMSs are designed to adopt a centralized architecture so that they can be applied to a single organization. However, in such a structure, participants in Agentflow applications in different organizations cannot serve each other with workflows. In this paper, a service-oriented cooperative workflow model, Cooperative Agentflow Process LANguage (CA-PLAN) is presented. CA-PLAN proposes a workflow component model to model inter-organizational processes. In CA-PLAN, an inter-organizational process is partitioned into several intra-organizational processes. Each workflow system inside an organization is modeled as an Integrated Workflow Component (IWC). Each IWC contains a process service interface, specifying process services provided by an organization, in conjunction with a remote process interface specifying what remote processes are used to refer to remote process services provided by other organizations, and intra-organizational processes. An IWC is a workflow node and participant. An inter-organizational process is made up of connections among these process services and remote processes with respect to different IWCs. In this paper, the related service techniques and supporting tools provided in Agentflow systems are presented.
High-Order Volterra Model Predictive Control and Its Application to a Nonlinear Polymerisation Process
Yun Li, Hiroshi Kashiwagi
2005, vol. 2, no. 2, pp. 208-214, doi: 10.1007/s11633-005-0208-9
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Abstract:
Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but existing design and implementation methods are restricted to linear process models. A chemical process, however, involves severe nonlinearity which cannot be ignored in practice. This paper aims to solve this nonlinear control problem by extending MPC to accommodate nonlinear models. It develops an analytical framework for nonlinear model predictive control (NMPC). It also offers a third-order Volterra series based nonparametric nonlinear modelling technique for NMPC design, which relieves practising engineers from the need for deriving a physical-principles based model first. An on-line realisation technique for implementing NMPC is then developed and applied to a Mitsubishi Chemicals polymerisation reaction process. Results show that this nonlinear MPC technique is feasible and very effective. It considerably outperforms linear and low-order Volterra model based methods. The advantages of the developed approach lie not only in control performance superior to existing NMPC methods, but also in eliminating the need for converting an analytical model and then convert it to a Volterra model obtainable only up to the second order.
Current Issue

2019 Vol.16 No.1

Table of Contents

ISSN 1476-8186

E-ISSN 1751-8520

CN 11-5350/TP

Editors-in-chief
Tieniu TAN, Chinese Academy of Sciences Guoping LIU, University of South Wales Huosheng HU, University of Essex
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