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. 1,  No. 2, 2014

2014, 1(2): .
Abstract(1663) PDF(0)
Table of Contents
Modeling and Hybrid Optimization of Batching Planning System for Steelmaking-continuous Casting Process
Tianmu Ma, Xiaochuan Luo, Tianyou Chai
2014, 1(2): 113-126.
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This paper investigates the batching problem for steelmaking and continuous casting production in an iron and steel enterprise. The tasks of this problem are to decide how to select slabs and determine their width, how to group the selected slabs into charges and then group the charges into tundishes, how to determine the sequence of charges in each tundish, and how to group tundishes into casts and determine the sequence of tundishes in each cast. The effective decision on the batching problem can help balance the requirements of the sequential process after steelmaking and continuous casting, reduce production cost, and improve slab quality. We first give the mathematical description of the original problem. Based on the analysis of width, we present a decomposition strategy to divide the model into three sub-models, i.e., charge design model, tundish design model and cast design model, while adding relevant objectives and constraints. According to the characteristics of each sub-model, we present hybrid optimization algorithms separately. Computational experiments show the strategy, models and algorithms can generate satisfactory solutions.
Timesharing-tracking Framework for Decentralized Reinforcement Learning in Fully Cooperative Multi-agent System
Xin Chen, Bo Fu, Yong He, Min Wu
2014, 1(2): 127-133.
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Dimension-reduced and decentralized learning is always viewed as an efficient way to solve multi-agent cooperative learning in high dimension. However, the dynamic environment brought by the concurrent learning makes the decentralized learning hard to converge and bad in performance. To tackle this problem, a timesharing-tracking framework (TTF), stemming from the idea that alternative learning in microscopic view results in concurrent learning in macroscopic view, is proposed in this paper, in which the joint-state best-response Q-learning (BRQ-learning) serves as the primary algorithm to adapt to the companions' policies. With the properly defined switching principle, TTF makes all agents learn the best responses to others at different joint states. Thus from the view of the whole joint-state space, agents learn the optimal cooperative policy simultaneously. The simulation results illustrate that the proposed algorithm can learn the optimal joint behavior with less computation and faster speed compared with other two classical learning algorithms.
Containment Control of General Linear Multi-agent Systems with Multiple Dynamic Leaders: a Fast Sliding Mode Based Approach
Huiyang Liu, Long Cheng, Min Tan, Zengguang Hou
2014, 1(2): 134-140.
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In this paper, distributed containment control problems of general linear multi-agent systems are investigated. The objective is to make the followers in a multi-agent network converge to the convex hull spanned by some leaders whose control inputs are nonzero and not available to any followers. Sliding mode surfaces are defined for the cases of reduced order and non-reduced order, respectively. For each case, fast sliding mode controllers are designed. It is shown that all the error trajectories exponentially reach the sliding mode surfaces in a finite time if for each follower, there exists at least one of the leaders who has a directed path to the follower, and the leaders' control inputs are bounded. The control Lyapunov function for exponential finite time stability, motivated by the fast terminal sliding mode control, is used to prove reachability of the sliding mode surfaces. Simulation examples are given to illustrate the theoretical results.
Bilateral Teleoperation of Multiple Agents with Formation Control
Jing Yan, Xian Yang, Cailian Chen, Xiaoyuan Luo, Xinping Guan
2014, 1(2): 141-148.
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This paper studies the formation problem for multislave teleoperation system over general communication networks, where multiple mobile slave agents are coupled with a single master robot. The forward and backward network transmission time delays are assumed to be asymmetric and time-varying. Due to the quantization in the network, a dynamic quantization strategy is provided to quantize the output signals of the master robot and slave agents before transmitting. Then, a novel masterslave protocol is designed to achieve the formation task under variable time delays and quantization. Additionally, the sufficient conditions for stability are presented to show that the formation protocol can stabilize the master-slave system under variable time delays and quantization. Finally, simulation are performed to show effectiveness of the main results.
Distributed Sparse Signal Estimation in Sensor Networks Using H-Consensus Filtering
Haiyang Yu, Yisha Liu, Wei Wang
2014, 1(2): 149-154.
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This paper is concerned with the sparse signal recovery problem in sensor networks, and the main purpose is to design a filter for each sensor node to estimate a sparse signal sequence using the measurements distributed over the whole network. A so-called l1-regularized H filter is established at first by introducing a pseudo-measurement equation, and the necessary and sufficient condition for existence of this filter is derived by means of Krein space Kalman filtering. By embedding a high-pass consensus filter into l1-regularized H filter in information form, a distributed filtering algorithm is developed, which ensures that all node filters can reach a consensus on the estimates of sparse signals asymptotically and satisfy the prescribed H performance constraint. Finally, a numerical example is provided to demonstrate effectiveness and applicability of the proposed method.
Adaptive Nonsingular Terminal Sliding Mode Control Design for Near Space Hypersonic Vehicles
Ruimin Zhang, Lu Dong, Changyin Sun
2014, 1(2): 155-161.
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This paper presents an adaptive nonsingular terminal sliding mode approach for the attitude control of near space hypersonic vehicles (NSHV) in the presence of parameter uncertainties and external disturbances. Firstly, a novel nonsingular terminal sliding surface is developed and its finitetime convergence is analyzed. Then, an adaptive nonsingular terminal sliding mode control law is proposed, which is chattering free. In the proposed approach, all parameter uncertainties and external disturbances are lumped into one term, which is estimated by an adaptive uncertainty estimation for eliminating the boundary requirement needed in the conventional control design. Subsequently, stability of the closed-loop system is proven based on Lyapunov theory. Finally, the proposed approach is applied to the attitude control design for NSHV. Simulation results show that the proposed approach attains a satisfactory performance in the presence of parameter uncertainties and external disturbances.
Distributed Consensus of Multiple Nonholonomic Mobile Robots
Kecai Cao, Bin Jiang, Dong Yue
2014, 1(2): 162-170.
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Consensus problems of multiple nonholonomic mobile robots are considered in this paper. These problems are simplified into consensus problems of two subsystems based on structure of nonholonomic mobile robots. Linear distributed controllers are constructed respectively for these two subsystems thanks to the theory of nonautonomous cascaded systems. Consensus of multiple nonholonomic mobile robots has been realized using the methodology proposed in this paper no matter whether the group reference signal is persistent excitation or not. Different from previous research on cooperative control of nonholonomic mobile robots where the consensus problem under persistent exciting reference has received a lot of attention, this paper reports the first consensus result for multiple nonholonomic mobile robots whose group reference converges to zero. Simulation results using Matlab illustrate the effectiveness of the proposed controllers in this paper.
Formation Control for Nonlinear Multi-agent Systems with Linear Extended State Observer
Wen Qin, Zhongxin Liu, Zengqiang Chen
2014, 1(2): 171-179.
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This paper investigates the formation control problem for nonlinear multi-agent systems with a virtual leader. A distributed formation control strategy based on linear extended state observer (LESO) is proposed under the hypothesis that velocity of the agent's neighbors could not be measured. Some sufficient conditions are established to ensure that the nonlinear multi-agent systems form a predefined formation with switching topology when the nonlinear function is known. Moreover, the tracking errors are bounded with external disturbance. Lastly, a numerical example with different scenarios is presented to demonstrate the validity of the obtained results.
Distributed Force/Position Consensus Tracking of Networked Robotic Manipulators
Lijiao Wang, Bin Meng
2014, 1(2): 180-186.
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In this paper, we address the tracking problem of distributed force/position for networked robotic manipulators in the presence of dynamic uncertainties. The end-effectors of the manipulators are in contact with flat compliant environment with uncertain stiffness and distance. The control objective is that the robotic followers track the convex hull spanned by the leaders under directed graphs. We propose a distributed adaptive force control scheme with an adaptive force observer to achieve the asymptotic force synchronization in constrained space, which also maintains a cascaded closed-loop structure separating the system into kinematic module and dynamic module. A decentralized stiffness updating law is also proposed to deal with the environment uncertainties. The convergence of tracking errors of force and position is proved using Lyapunov stability theory and input-output stability analysis tool. Finally, simulations are performed to show effectiveness of the theoretical approach.
A Continuous Leader-following Consensus Control Strategy for a Class of Uncertain Multi-agent Systems
Chuanrui Wang, Xinghu Wang, Haibo Ji
2014, 1(2): 187-192.
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In this paper, we study the robust leader-following consensus problem for a class of multi-agent systems with unknown nonlinear dynamics and unknown but bounded disturbances. The control input of the leader agent is nonzero and not available to any follower agent. We first consider a class of high order chain integrator-type multi-agent systems. By employing the robust integral of the sign of the error technique, a continuous distributed control law is constructed using local information obtained from neighboring agents. Using Lyapunov analysis theory, we show that under a connected undirected information communication topology, the proposed protocol achieves semiglobal leader-following consensus. We then extend the approach to a class of more general uncertain multiagent systems. A numerical example is given to verify our proposed protocol.
Distributed Average Consensus in Multi-agent Networks with Limited Bandwidth and Time-delays
Wenhui Liu, Feiqi Deng, Jiarong Liang, Haijun Liu
2014, 1(2): 193-203.
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This paper studies the distributed average consensus problem of multi-agent digital networks with time-delays. For the network, each agent can only exchange symbolic data with its neighbours. We provide a distributed average consensus protocol which uses the quantized and time-delay information. We consider two types of dynamic encoders/decoders in our protocol. One uses inverse proportion function as scaling function, while the other uses exponential function as scaling function. All agents can reach average consensus asymptotically with our protocol. Furthermore, we show that the average consensus protocol is robust to finite symmetric time-delays, but is sensitive to asymmetric time-delays that will destroy the average consensus of the networks. Finally, simulations are presented to illustrate validity of our theoretical results.
Consensus Robust Output Regulation of Discrete-time Linear Multi-agent Systems
Hongjing Liang, Huaguang Zhang, Zhanshan Wang, Junyi Wang
2014, 1(2): 204-209.
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This paper deals with consensus robust output regulation of discrete-time linear multi-agent systems under a directed interaction topology. The digraph is assumed to contain a spanning tree. Every agent or subsystem is identical and uncertain, but subsystems have different external disturbances. Based on the internal model and general discrete-time algebraic Riccati equation, a distributed consensus protocol is proposed to solve the regulator problem. A numerical simulation demonstrates the effectiveness of the proposed theoretical results.
Leader-follower Consensus of Upper-triangular Nonlinear Multi-agent Systems
Chenghui Zhang, Le Chang, Xianfu Zhang
2014, 1(2): 210-217.
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This paper is concerned with the leader-follower consensus problem by using both state and output feedback for a class of nonlinear multi-agent systems. The agents considered here are all identical upper-triangular nonlinear systems which satisfy the Lipschitz growth condition. First, it is shown that the leader-follower consensus problem is equivalent to the control design problem of a high-dimensional multi-variable system. Second, by introducing an appropriate state transformation, the control design problem can be converted into the problem of finding a constant parameter, which can be obtained by solving the Lyapunov equation and estimating the nonlinear terms of the given system. At last, an example is given to verify effectiveness of the proposed consensus algorithms.
A Multi-agent Based Evaluation Framework and Its Applications
Jinlong Wang, Qianchuan Zhao, Haitao Li
2014, 1(2): 218-224.
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The evaluation system is significant for assessment of technologies, experiments, energy cost and effectiveness, especially for the complicated engineering systems, such as energy systems, weapon systems and spacecraft systems. However, as engineering systems become more and more distributed and heterogeneous, evaluation frameworks need to be more universal, distributed and interactive. In this paper, we compare several typical evaluation frameworks and propose a novel evaluation framework based on multi-agent technology. We provide two case studies, indoor comfort system and technology assessment of spacecraft systems, respectively. The results show that the proposed framework can work efficiently.