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.3, No.3, 2016

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Control 5.0: From Newton to Merton in Popper's Cyber-Social-Physical Spaces
Fei-Yue Wang
2016, 3(3): 233-234.
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The future of control in cyberspace of parallel worlds is discussed. It argues for the coming age of Control 5.0, the control technology for the new IT capable of dealing with artificial worlds with VR, AR, AI and robotics. The discipline of automation needs a new interpretation of its core knowledge and skill set of modeling, analysis, and control for cyber-socialphysical systems, and a paradigm shift from Newtonian Systems with Newton's Laws or Big Laws with Small Data to Mertonian Systems with Merton's Laws or Small Laws with Big Data.
A Hybrid Estimation of Distribution Algorithm for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times
Ling Wang, Shengyao Wang, Xiaolong Zheng
2016, 3(3): 235-246.
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A hybrid estimation of distribution algorithm (EDA) with iterated greedy (IG) search (EDA-IG) is proposed for solving the unrelated parallel machine scheduling problem with sequence-dependent setup times (UPMSP-SDST). For makespan criterion, some properties about neighborhood search operators to avoid invalid search are derived. A probability model based on neighbor relations of jobs is built in the EDA-based exploration phase to generate new solutions by sampling the promising search region. Two types of deconstruction and reconstruction as well as an IG search are designed in the IG-based exploitation phase. Computational complexity of the algorithm is analyzed, and the effect of parameters is investigated by using the Taguchi method of design-of-experiment. Numerical tests on 1640 benchmark instances are carried out. The results and comparisons demonstrate the effectiveness of the EDA-IG. Especially, the bestknown solutions of 531 instances are updated. In addition, the effectiveness of the properties is also demonstrated by numerical comparisons.
Traffic Signal Timing via Deep Reinforcement Learning
Li Li, Yisheng Lv, Fei-Yue Wang
2016, 3(3): 247-254.
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In this paper, we propose a set of algorithms to design signal timing plans via deep reinforcement learning. The core idea of this approach is to set up a deep neural network (DNN) to learn the Q-function of reinforcement learning from the sampled traffic state/control inputs and the corresponding traffic system performance output. Based on the obtained DNN, we can find the appropriate signal timing policies by implicitly modeling the control actions and the change of system states. We explain the possible benefits and implementation tricks of this new approach. The relationships between this new approach and some existing approaches are also carefully discussed.
Guest Editorial for Special Issue on Fractional Order Systems and Controls
YangQuan Chen, Dingyü Xue, Antonio Visioli
2016, 3(3): 255-256.
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The Fractional Landau Model
Bruce J. West, Malgorzata Turalska
2016, 3(3): 257-260.
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Herein the Landau model of the transition from laminar to turbulent fluid flow is generalized to include the effect of memory. The original Landau model is quadratically nonlinear and memoryless, with turbulent fluctuations decaying exponentially. However, recent experiments show a dependence of the decay of fluctuations on memory, with the exponential being replaced by an inverse power law. This transition is explained herein as being due to critical slowing down. The fractional calculus is used to model this memory and to relate the index of the inverse power law decay to that of the fractional derivative in time.
A Fractional Micro-Macro Model for Crowds of Pedestrians Based on Fractional Mean Field Games
Kecai Cao, YangQuan Chen, Daniel Stuart
2016, 3(3): 261-270.
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Modeling a crowd of pedestrians has been considered in this paper from different aspects. Based on fractional microscopic model that may be much more close to reality, a fractional macroscopic model has been proposed using conservation law of mass. Then in order to characterize the competitive and cooperative interactions among pedestrians, fractional mean field games are utilized in the modeling problem when the number of pedestrians goes to infinity and fractional dynamic model composed of fractional backward and fractional forward equations are constructed in macro scale. Fractional micromacro model for crowds of pedestrians are obtained in the end. Simulation results are also included to illustrate the proposed fractional microscopic model and fractional macroscopic model, respectively.
Fractional Order Modeling of Human Operator Behavior with Second Order Controlled Plant and Experiment Research
Jiacai Huang, YangQuan Chen, Haibin Li, Xinxin Shi
2016, 3(3): 271-280.
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Modeling human operator's dynamics plays a very important role in the manual closed-loop control system, and it is an active research area for several decades. Based on the characteristics of human brain and behavior, a new kind of fractional order mathematical model for human operator in single-input single-output (SISO) systems is proposed. Compared with the traditional models based on the commonly used quasilinear transfer function method or the optimal control theory method, the proposed fractional order model has simpler structure with only few parameters, and each parameter has explicit physical meanings. The actual data and experiment results with the second-order controlled plant illustrate the effectiveness of the proposed method.
Fractional Modeling and SOC Estimation of Lithium-ion Battery
Yan Ma, Xiuwen Zhou, Bingsi Li, Hong Chen
2016, 3(3): 281-287.
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This paper proposes a state of charge (SOC) estimator of Lithium-ion battery based on a fractional order impedance spectra model. Firstly, a battery fractional order impedance model is derived on the grounds of the characteristics of Warburg element and constant phase element (CPE) over a wide range of frequency domain. Secondly, a frequency fitting method and parameter identification algorithm based on output error are presented to identify parameters of the fractional order model of Lithium-ion battery. Finally, the fractional order Kalman filter approach is introduced to estimate the SOC of the lithium-ion battery based on the fractional order model. The simulation results show that the fractional-order model can ensure an acceptable accuracy of the SOC estimation, and the error of estimation reaches maximally up to 0.5% SOC.
Fractional Modeling and Analysis of Coupled MR Damping System
Bingsan Chen, Chunyu Li, Benjamin Wilson, Yijian Huang
2016, 3(3): 288-294.
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The coupled magnetorheological (MR) damping system addressed in this paper contains rubber spring and magnetorheological damper. The device inherits the damping merits of both the rubber spring and the magnetorheological damper. Here a fractional-order constitutive equation is introduced to study the viscoelasticity of the combined damper. An introduction to the definitions of fractional calculus, and the transfer function representation of a fractional-order system are given. The fractional-order system model of a magnetorheological vibration platform is set up using fractional calculus, and the function of displacement is presented. It is indicated that the fractional-order constitutive equation and the transfer function are feasible and effective means for investigating of magnetorheological vibration device.
Parameter Estimation and Topology Identification of Uncertain General Fractional-order Complex Dynamical Networks with Time Delay
Xiaojuan Chen, Jun Zhang, Tiedong Ma
2016, 3(3): 295-303.
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Complex networks have attracted much attention from various fields of sciences and engineering in recent years. However, many complex networks have various uncertain information, such as unknown or uncertain system parameters and topological structure, which greatly affects the system dynamics. Thus, the parameter estimation and structure identification problem has theoretical and practical importance for uncertain complex dynamical networks. This paper investigates identification of unknown system parameters and network topologies in uncertain fractional-order complex network with time delays (including coupling delay and node delay). Based on the stability theorem of fractional-order differential system and the adaptive control technique, a novel and general method is proposed to address this challenge. Finally two representative examples are given to verify the effectiveness of the proposed approach.
H Output Feedback Control of Linear Time-invariant Fractional-order Systems over Finite Frequency Range
Cuihong Wang, Huanhuan Li, YangQuan Chen
2016, 3(3): 304-310.
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This paper focuses on the H output feedback control problem of linear time-invariant fractional-order systems over finite frequency range. Based on the generalized Kalman-Yakubovic-Popov (KYP) Lemma and a key projection lemma, a necessary and sufficient condition is established to ensure the existence of the H output feedback controller over finite frequency range, a desirable property in control engineering practice. By using the matrix congruence transformation, the feedback control gain matrix is decoupled and further parameterized by a scalar matrix. Two iterative linear matrix inequality algorithms are developed to solve this problem. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.
The Ellipsoidal Invariant Set of Fractional Order Systems Subject to Actuator Saturation: The Convex Combination Form
Kai Chen, Junguo Lu, Chuang Li
2016, 3(3): 311-319.
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The domain of attraction of a class of fractional order systems subject to saturating actuators is investigated in this paper. We show the domain of attraction is the convex hull of a set of ellipsoids. In this paper, the Lyapunov direct approach and fractional order inequality are applied to estimating the domain of attraction for fractional order systems subject to actuator saturation. We demonstrate that the convex hull of ellipsoids can be made invariant for saturating actuators if each ellipsoid with a bounded control of the saturating actuators is invariant. The estimation on the contractively invariant ellipsoid and construction of the continuous feedback law are derived in terms of linear matrix inequalities (LMIs). Two numerical examples illustrate the effectiveness of the developed method.
Constrained Swarm Stabilization of Fractional Order Linear Time Invariant Swarm Systems
Mojtaba Naderi Soorki, Mohammad Saleh Tavazoei
2016, 3(3): 320-331.
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This paper deals with asymptotic swarm stabilization of fractional order linear time invariant swarm systems in the presence of two constraints: the input saturation constraint and the restriction on distance of the agents from final destination which should be less than a desired value. A feedback control law is proposed for asymptotic swarm stabilization of fractional order swarm systems which guarantees satisfying the above-mentioned constraints. Numerical simulation results are given to confirm the efficiency of the proposed control method.
Improving the Control Energy in Model Reference Adaptive Controllers Using Fractional Adaptive Laws
Norelys Aguila-Camacho, Manuel A. Duarte-Mermoud
2016, 3(3): 332-337.
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This paper presents the analysis of the control energy consumed in model reference adaptive control (MRAC) schemes using fractional adaptive laws, through simulation studies. The analysis is focused on the energy spent in the control signal represented by means of the integral of the squared control input (ISI). Also, the behavior of the integral of the squared control error (ISE) is included in the analysis.
The orders of the adaptive laws were selected by particle swarm optimization (PSO), using an objective function including the ISI and the ISE, with different weighting factors. The results show that, when ISI index is taken into account in the optimization process to determine the orders of adaptive laws, the resulting values are fractional, indicating that control energy of the scheme might be better managed if fractional adaptive laws are used.
An Approach to Design MIMO FO Controllers for Unstable Nonlinear Plants
Arturo Rojas-Moreno
2016, 3(3): 338-344.
Abstract PDF
This paper develops an approach to control unstable nonlinear multi-inputs multi-output (MIMO) square plants using MIMO fractional order (FO) controllers. The controller design uses the linear time invariant (LTI) state space representation of the nonlinear model of the plant and the diagonal closedloop transfer matrix (TM) function to ensure decoupling between inputs. Each element of the obtained MIMO controller could be either a transfer function (TF) or a gain. A TF is associated in turn with its corresponding FO TF. For example, a D (Derivative) TF is related to a FO TF of the form Dδ, δ = [0, 1]. Two applications were performed to validate the developed approach via experimentation: control of the angular positions of a manipulator, and control of the car and arm positions of a translational manipulator.

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor 2020: 6.171
    Rank:Top 11% (7/93), Category of Automation & Control Systems
    Quantile: The 1st (SCI Q1)
    CiteScore 2020 : 11.2
    Rank: Top 5% (Category of Computer Science: Information System) , Top 6% (Category of Control and Systems Engineering), Top 7% (Category of Artificial Intelligence)
    Quantile: The 1st (Q1)