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

Current Issue

Vol.5, No.6, 2018

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REVIEW
Granular Computing for Data Analytics: A Manifesto of Human-Centric Computing
Witold Pedrycz
2018, 5(6): 1025-1034 doi: 10.1109/JAS.2018.7511213
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In the plethora of conceptual and algorithmic developments supporting data analytics and system modeling, humancentric pursuits assume a particular position owing to ways they emphasize and realize interaction between users and the data. We advocate that the level of abstraction, which can be flexibly adjusted, is conveniently realized through Granular Computing. Granular Computing is concerned with the development and processing information granules-formal entities which facilitate a way of organizing knowledge about the available data and relationships existing there. This study identifies the principles of Granular Computing, shows how information granules are constructed and subsequently used in describing relationships present among the data.
PAPERS
Optimal Decoupling Control Method and Its Application to a Ball Mill Coal-pulverizing System
Yue Fu, Chengwen Hong, Jingyi Li
2018, 5(6): 1035-1043 doi: 10.1109/JAS.2018.7511219
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The conventional optimal tracking control method cannot realize decoupling control of linear systems with a strong coupling property. To solve this problem, in this paper, an optimal decoupling control method is proposed, which can simultaneously provide optimal performance. The optimal decoupling controller is composed of an inner-loop decoupling controller and an outer-loop optimal tracking controller. First, by introducing one virtual control variable, the original differential equation on state is converted to a generalized system on output. Then, by introducing the other virtual control variable, and viewing the coupling terms as the measurable disturbances, the generalized system is open-loop decoupled. Finally, for the decoupled system, the optimal tracking control method is used. It is proved that the decoupling control is optimal for a certain performance index. Simulations on a ball mill coal-pulverizing system are conducted. The results show the effectiveness and superiority of the proposed method as compared with the conventional optimal quadratic tracking (LQT) control method.
Necessary and Sufficient Conditions for Consensus in Third Order Multi-Agent Systems
Chi Huang, Guisheng Zhai, Gesheng Xu
2018, 5(6): 1044-1053 doi: 10.1109/JAS.2018.7511222
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We deal with a consensus control problem for a group of third order agents which are networked by digraphs. Assuming that the control input of each agent is constructed based on weighted difference between its states and those of its neighbor agents, we aim to propose an algorithm on computing the weighting coefficients in the control input. The problem is reduced to designing Hurwitz polynomials with real or complex coefficients. We show that by using Hurwitz polynomials with complex coefficients, a necessary and sufficient condition can be obtained for designing the consensus algorithm. Since the condition is both necessary and sufficient, we provide a kind of parametrization for all the weighting coefficients achieving consensus. Moreover, the condition is a natural extension to second order consensus, and is reasonable and practical due to its comparatively decreased computation burden. The result is also extended to the case where communication delay exists in the control input.
Self-Tuning Asynchronous Filter for Linear Gaussian System and Applications
Wenjun Lv, Yu Kang, Yunbo Zhao
2018, 5(6): 1054-1061 doi: 10.1109/JAS.2018.7511183
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In this paper, optimal filtering problem for a class of linear Gaussian systems is studied. The system states are updated at a fast uniform sampling rate and the measurements are sampled at a slow uniform sampling rate. The updating rate of system states is several times the sampling rate of measurements and the multiple is constant. To solve the problem, we will propose a self-tuning asynchronous filter whose contributions are twofold. First, the optimal filter at the sampling times when the measurements are available is derived in the linear minimum variance sense. Furthermore, considering the variation of noise statistics, a regulator is introduced to adjust the filtering coefficients adaptively. The case studies of wheeled robot navigation system and air quality evaluation system will show the effectiveness and practicability in engineering.
Hazard-evaluation-oriented Moving Horizon Parallel Steering Control for Driver-Automation Collaboration During Automated Driving
Hongyan Guo, Linhuan Song, Jun Liu, Fei-Yue Wang, Dongpu Cao, Hong Chen, Chen Lv, Partick Chi-Kwong Luk
2018, 5(6): 1062-1073 doi: 10.1109/JAS.2018.7511225
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Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization. The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation, the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner. The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.
Using the Fractional Order Method to Generalize Strengthening Buffer Operator and Weakening Buffer Operator
Lifeng Wu, Sifeng Liu, Yingjie Yang
2018, 5(6): 1074-1078 doi: 10.1109/JAS.2016.7510214
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To reveal the relationship between a weakening buffer operator and strengthening buffer operator, the traditional integer order buffer operator is extended to one that is fractional order. Fractional order buffer operator not only can generalize the weakening buffer operator and the strengthening buffer operator, but also results in small adjustments of the buffer effect. The effectiveness of the grey model (GM(1, 1)) with the fractional order buffer operator is validated by six cases.
Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity
Xue Chen, Yanjiang Wang
2018, 5(6): 1079-1088 doi: 10.1109/JAS.2017.7510880
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The complex relationship between structural connectivity (SC) and functional connectivity (FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible (SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field (DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that ⅰ) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ⅱ) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; ⅲ) in comparison with the DMF model, the dynamic model embedded in the shortest paths is found to perform better to predict FC.
Stabilization of Networked Control Systems Using a Mixed-Mode Based Switched Delay System Method
Qing-Kui Li, Xiaoli Li, Jiuhe Wang, Shengli Du
2018, 5(6): 1089-1098 doi: 10.1109/JAS.2018.7511228
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The phenomenon of mixed-mode is one of the most important characteristics of switched delay systems. If a networked control system (NCS) with network induced delays and packet dropouts (NIDs & PDs) is recast as a switched delay system, it is imperative to consider the effects of mixed-modes in the stability analysis for an NCS. In this paper, with the help of the interpolatory quadrature formula and the average dwell time method, stabilization of NCSs using a mixed-mode based switched delay system method is investigated based on a novel constructed Lyapunov-Krasovskii functional. With the Finsler's lemma, new exponential stabilizability conditions with less conservativeness are given for the NCS. Finally, an illustrative example is provided to verify the effectiveness of the developed results.
Expressway Traffic Flow Model Study Based on Different Traffic Rules
Junwei Zeng, Senbin Yu, Yongsheng Qian, Xiao Feng
2018, 5(6): 1099-1103 doi: 10.1109/JAS.2017.7510469
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In this paper, two cellular automata traffic models are proposed to simulate the operation of an expressway. The results show that the flow rate and the average velocity are generally equal in the same density which is different among the lanes. The analysis of lane changing times and the velocity total deviation show some characteristics which are difficult to explain phase transitions under fundamental diagram theory. Therefore, the concept of lane changing probability is introduced, and it is concluded that the speed-limit rule can reduce the motivation of lane changing effectively.
Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments
Yuling Hu, Xiwei Liu
2018, 5(6): 1104-1112 doi: 10.1109/JAS.2018.7511231
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It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.
BRIEF PAPERS
A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System
Fangfang Zhao, Cuiqiao Chen, Wei He, Shuzhi Sam Ge
2018, 5(6): 1113-1120 doi: 10.1109/JAS.2017.7510445
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This paper explores multiple model adaptive estimation (MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter-multiple model adaptive estimation unscented Kalman filter (MMAE-UKF) rather than conventional Kalman filter methods, like the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters, which the improved filtering method can overcome. Meanwhile, this algorithm is used for integrated navigation system of strapdown inertial navigation system (SINS) and celestial navigation system (CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.
Disturbance Observer Based Control for Four Wheel Steering Vehicles With Model Reference
Shuyou Yu, Jing Wang, Yan Wang, Hong Chen
2018, 5(6): 1121-1127 doi: 10.1109/JAS.2016.7510220
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This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model. A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration. The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out, which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.
Speed-assigned Position Tracking Control of SRM With Adaptive Backstepping Control
Jiajun Wang
2018, 5(6): 1128-1135 doi: 10.1109/JAS.2016.7510019
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A novel speed-assigned method is applied to the position tracking control of switched reluctance motor (SRM). A speed control freedom can be drawn into the position control through speed assignment. Adaptive backstepping control is used to design the position controller for the SRM. The accuracy of position tracking of the SRM can be enhanced with speed assignment. A disturbance observer is further designed to enhance the estimation accuracy of the unknown load torque. Simulation results certify that the design scheme is right and effective.
The Cubic Trigonometric Automatic Interpolation Spline
Juncheng Li, Laizhong Song, Chengzhi Liu
2018, 5(6): 1136-1141 doi: 10.1109/JAS.2017.7510442
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A class of cubic trigonometric interpolation spline curves with two parameters is presented in this paper. The spline curves can automatically interpolate the given data points and become C2 interpolation curves without solving equations system even if the interpolation conditions are fixed. Moreover, shape of the interpolation spline curves can be globally adjusted by the two parameters. By selecting proper values of the two parameters, the optimal interpolation spline curves can be obtained.
Mathematical Study of A Memory Induced Biochemical System
Mithun Kumar Ghosh, Tridip Sardar, Xianbing Cao, Priti Kumar Roy
2018, 5(6): 1142-1149 doi: 10.1109/JAS.2018.7511234
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In this work, to study the effect of memory on a bi-substrate enzyme kinetic reaction, we have introduced an approach to fractionalize the system, considering it as a threecompartmental model. Solutions of the fractionalized system are compared with the corresponding integer-order model. The equilibrium points of the fractionalized system are derived analytically. Their stability properties are discussed from numerical aspect. We determine the changes of the substances due to the changes of "memory effect". The effect is discussed critically from the perspective of product formation. We have also analyzed the memory induced system with a control measure in view of optimizing the product. Our numerical result reveals that the solutions of the fractionalized system, when it is free from memory, are in good agreement with the integer-order system. It is noticed that the effect of memory influences the reaction in the forward direction and assists in yielding the product more quickly. However, an extensive use of memory makes the system slower, but introduction of a control input makes the reaction faster. It is possible to overcome the slowness of the reaction due to the undue effect of memory by appropriate use of a control measure.
Predictive Tracking Control of Network-Based Agents With Communication Delays
Tianyong Zhang, Guoping Liu
2018, 5(6): 1150-1156 doi: 10.1109/JAS.2017.7510868
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This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels. A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network. Furthermore, the problem of consecutive data loss in the feedback channel is solved using aforementioned controller, where lateral movement perturbations are introduced. Simulations and experiments are provided for several cases, which verify the realizability and effectiveness of the proposed controller.

IEEE/CAA Journal of Automatica Sinica

  • CiteScore 2017: 3.18
    Rank:Top 18% (Category of Control and Systems Engineering), Top 19% (Categories of Information System and Artificial Intelligence)