A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation

Vol. 2,  No. 4, 2015

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2015, 2(4): .
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A Reduced Reachability Tree for a Class of Unbounded Petri Nets
Shouguang Wang, Mengdi Gan, Mengchu Zhou, Dan You
2015, 2(4): 345-352.
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As a powerful analysis tool of Petri nets, reachability trees are fundamental for systematically investigating many characteristics such as boundedness, liveness and reversibility. This work proposes a method to generate a reachability tree, called ωRT for short, for a class of unbounded generalized nets called ω-independent nets based on new modified reachability trees (NMRTs). ωRT can effectively decrease the number of nodes by removing duplicate and ω-duplicate nodes in the tree, and verify properties such as reachability, liveness and deadlocks. Two examples are provided to show its superiority over NMRTs in terms of tree size.
Cyber-physical Systems as General Distributed Parameter Systems: Three Types of Fractional Order Models and Emerging Research Opportunities
Fudong Ge, YangQuan Chen, Chunhai Kou
2015, 2(4): 353-357.
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Cyber-physical systems (CPSs) are man-made complex systems coupled with natural processes that, as a whole, should be described by distributed parameter systems (DPSs) in general forms. This paper presents three such general models for generalized DPSs that can be used to characterize complex CPSs. These three different types of fractional operators based DPS models are: fractional Laplacian operator, fractional power of operator or fractional derivative. This research investigation is motivated by many fractional order models describing natural, physical, and anomalous phenomena, such as sub-diffusion process or super-diffusion process. The relationships among these three different operators are explored and explained. Several potential future research opportunities are then articulated followed by some conclusions and remarks.
Anti-windup-based Dynamic Controller Synthesis for Lipschitz Systems under Actuator Saturation
Naizhou Wang, Hailong Pei, Yong Tang
2015, 2(4): 358-365.
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This paper presents a new method for simultaneous synthesis of dynamic controller and static anti-windup compensator for saturated Lipschitz systems. Thanks to the reformulated Lipschitz property, the Lipschitz systems can be transformed into LPV (linear parameter-varying) systems whose system matrices are affine in a parameter matrix. Based on the modified sector condition dealing with saturation nonlinearity, the design of a nonlinear anti-windup-based controller leads to the solvability of a set of bilinear matrix inequalities (BMI) on the vertices of a bounded convex set which can be solved by the so-called iterative linear matrix inequality (ILMI) algorithm. A numerical example is presented to illustrate the effectiveness of the proposed method.
Linguistic Dynamic Modeling and Analysis of Psychological Health State Using Interval Type-2 Fuzzy Sets
Hong Mo, Jie Wang, Xuan Li, Zhanlin Wu
2015, 2(4): 366-373.
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The study of psychological health state is helpful to build appropriate models and take effective intervention strategies, and the results benefit the intervened released from psychological distress within the shortest possible time. In this paper, interval type-2 fuzzy sets and fuzzy comprehension evaluation are applied in the analysis of mental health status and crisis intervention. A closed-loop linguistic dynamic intervention model for psychological health state is built. Linguistic dynamic systems based on interval type-2 fuzzy sets are used to describe and analyze the evolutionary process of psychological health status.
Distributed Model Predictive Control with Actuator Saturation for Markovian Jump Linear System
Yan Song, Haifeng Lou, Shuai Liu
2015, 2(4): 374-381.
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This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system matrices. The global system is decomposed into several subsystems which coordinate with each other. A set of distributed controllers is designed by solving a min-max optimization problem in terms of the solutions of linear matrix inequalities (LMIs). An iterative algorithm is developed to achieve the online computation. Finally, a simulation example is employed to show the effectiveness of the proposed algorithm.
A Systematic Approach for Designing Analytical Dynamics and Servo Control of Constrained Mechanical Systems
Xiaoli Liu, Shengchao Zhen, Kang Huang, Han Zhao, Ye-Hwa Chen, Ke Shao
2015, 2(4): 382-393.
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A systematic approach for designing analytical dynamics and servo control of constrained mechanical systems is proposed. Fundamental equation of constrained mechanical systems is first obtained according to Udwadia-Kalaba approach which is applicable to holonomic and nonholonomic constrained systems no matter whether they satisfy the D'Alember's principle. The performance specifications are modeled as servo constraints. Constraint-following servo control is used to realize the servo constraints. For this inverse dynamics control problem, the determination of control inputs is based on the Moore-Penrose generalized inverse to complete the specified motion. Secondorder constraints are used in the dynamics and servo control. Constraint violation suppression methods can be adopted to eliminate constraint drift in the numerical simulation. Furthermore, this proposed approach is applicable to not only fully actuated but also underactuated and redundantly actuated mechanical systems. Two-mass spring system and coordinated robot system are presented as examples for illustration.
Function Observer Based Event-triggered Control for Linear Systems with Guaranteed L-Gain
Pei Jia, Fei Hao, Hao Yu
2015, 2(4): 394-402.
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This paper is devoted to event-triggered control design for linear systems based on function observer. More specifically, the main purpose is to design event-triggered mechanisms that trigger transmissions when the difference between the current value of the system and its previously transmitted value which includes the plant output or the function observer output exceeds an additional threshold. For such an eventtriggered mechanism, we derive conditions in terms of matrix inequality to guarantee the stability as well as longer inter-event time. We propose two approaches to investigate the closed-loop model, namely, reformulating the event-triggered control system as a hybrid system and interpreting the event-induced error as exogenous disturbance. Furthermore, the minimum inter-event time is guaranteed to be strictly positive. An example is presented to illustrate the feasibility and efficiency of the theoretic results.
Review Expert Collaborative Recommendation Algorithm Based on Topic Relationship
Shengxiang Gao, Zhengtao Yu, Linbin Shi, Xin Yan, Haixia Song
2015, 2(4): 403-411.
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The project review information plays an important role in the recommendation of review experts. In this paper, we aim to determine review expert's rating by using the historical rating records and the final decision results on the previous projects, and by means of some rules, we construct a rating matrix for projects and experts. For the data sparseness problem of the rating matrix and the “cold start” problem of new expert recommendation, we assume that those projects/experts with similar topics have similar feature vectors and propose a review expert collaborative recommendation algorithm based on topic relationship. Firstly, we obtain topics of projects/experts based on latent Dirichlet allocation (LDA) model, and build the topic relationship network of projects/experts. Then, through the topic relationship between projects/experts, we find a neighbor collection which shares the largest similarity with target project/expert, and integrate the collection into the collaborative filtering recommendation algorithm based on matrix factorization. Finally, by learning the rating matrix to get feature vectors of the projects and experts, we can predict the ratings that a target project will give candidate review experts, and thus achieve the review expert recommendation. Experiments on real data set show that the proposed method could predict the review expert rating more effectively, and improve the recommendation effect of review experts.
A Priority-aware Frequency Domain Polling MAC Protocol for OFDMA-based Networks in Cyber-physical Systems
Meng Zheng, Junru Lin, Wei Liang, Haibin Yu
2015, 2(4): 412-421.
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Wireless networking in cyber-physical systems (CPSs) is characteristically different from traditional wireless systems due to the harsh radio frequency environment and applications that impose high real-time and reliability constraints. One of the fundamental considerations for enabling CPS networks is the medium access control protocol. To this end, this paper proposes a novel priority-aware frequency domain polling medium access control (MAC) protocol, which takes advantage of an orthogonal frequency-division multiple access (OFDMA) physical layer to achieve instantaneous priority-aware polling. Based on the polling result, the proposed work then optimizes the resource allocation of the OFDMA network to further improve the data reliability. Due to the Non-polynomial-complete nature of the OFDMA resource allocation, we propose two heuristic rules, based on which an efficient solution algorithm to the OFDMA resource allocation problem is designed. Simulation results show that the reliability performance of CPS networks is significantly improved because of this work.
Security-aware Signal Packing Algorithm for CAN-based Automotive Cyber-physical Systems
Yong Xie, Liangjiao Liu, Renfa Li, Jianqiang Hu, Yong Han, Xin Peng
2015, 2(4): 422-430.
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Network and software integration pose severe challenges in cyber-security for controller area network (CAN)-based automotive cyber-physical system (ACPS), therefore we employ message authentication code (MAC) to defend CAN against masquerade attack, but the consequent bandwidth overhead makes it a necessity to find the tradeoff among security, real-time and bandwidth utilization for signal packing problem (SPP) of CAN. A mixed-security signal model is firstly proposed to formally describe the properties and requirements on security and real-time for signals, and then a mixed-integer linear programming (MILP) formulation of SPP security-aware signal packing (SASP) is implemented to solve the tradeoff problem, where the bandwidth utilization is improved and the requirements in both security and real-time are met. Experiments based on both society of automotive engineers (SAE) standard signal set and simulated signal set showed the effectiveness of SASP by comparing with the state-of-the-art algorithm.
Security Risk Assessment of Cyber Physical Power System Based on Rough Set and Gene Expression Programming
Song Deng, Dong Yue, Xiong Fu, Aihua Zhou
2015, 2(4): 431-439.
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Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality.
Logic-based Reset Adaptation Design for Improving Transient Performance of Nonlinear Systems
Xia Wang, Jun Zhao
2015, 2(4): 440-448.
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In this paper, logic-based switching and resetting principles are presented to devise adaptive control laws for a class of uncertain nonlinear systems in order to ensure both the transient bound and the asymptotical convergence of the state. A novel supervisor is constructed to decide when to reset the estimation parameter with the pre-given estimation value. A benchmark example is presented to demonstrate the effectiveness of the approach.