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. 1, 2016

Display Method:
A Comprehensive Overview of Cyber-Physical Systems: From Perspective of Feedback System
Xinping Guan, Bo Yang, Cailian Chen, Wenbin Dai, Yiyin Wang
2016, 3(1): 1-14.
Abstract(1615) HTML (28) PDF(136)
Cyber-physical systems (CPS) are characterized by integrating cybernetic and physical processes. The theories and applications of CPS face the enormous challenges. The aim of this paper is to provide a latest understanding of this emerging multi-disciplinary methodology. First, the features of CPS are described, and the research progresses are summarized from different components in CPS, such as system modeling, information acquisition, communication, control and security. Each part is also followed by the future directions. Then some typical applications are given to show the prospects of CPS.
Theory and Application of Multi-robot Service-oriented Architecture
Yunfei Cai, Zhenmin Tang, Yuhua Ding, Bin Qian
2016, 3(1): 15-25.
Abstract(1104) HTML (31) PDF(8)
In order to solve the problem of heterogeneity in multi-robot cooperation, a new service-oriented architecture is proposed for multi-robot cooperation. Service provision and energy consumption are the basic cooperative behaviors. A set of basic concepts of robot service are proposed. A layered multi-robot service-oriented architecture is designed. Finally, the experiments illustrate the superiority of the proposed architecture which makes robot's underlying functional components be transparently encapsulated and the services in upper layer be transparently invoked, which will effectively avoid the impact of heterogeneous characteristics in multi-robot cooperation and facilitate the system construction, expansion, restructuring and maintenance.
Adaptive Control of MIMO Mechanical Systems with Unknown Actuator Nonlinearities Based on the Nussbaum Gain Approach
Ci Chen, Zhi Liu, Yun Zhang, C. L. Philip Chen, Shengli Xie
2016, 3(1): 26-34.
Abstract(1231) HTML (22) PDF(33)
This paper investigates MIMO mechanical systems with unknown actuator nonlinearities. A novel Nussbaum analysis tool for MIMO systems is established such that unknown timevarying control coefficients are tackled. In contrast to existing literatures on continuous-times systems, the newly-developed Nussbaum tool focuses on extending the traditional Nussbaum result from one dimensional case to the multiple one. Specifically, not only the multiple unknown input coefficients are extended to the time-varying, but also the limitation of the prior knowledge of coefficients' upper and lower bounds is removed. Furthermore, an adaptive robust controller associated with the proposed tool is presented. The asymptotic tracking of MIMO mechanical systems is guaranteed with the help of the Lyapunov Theorem. Finally, a simulation example is provided to examine the validity of the proposed scheme.
Manipulations Between Eigenstates of 2-Level Quantum System Based on Optimal Measurements
Jingbei Yang, Shuang Cong, Feng Shuang, Herschel Rabitz
2016, 3(1): 35-41.
Abstract(1112) HTML (19) PDF(7)
This paper explores the manipulation between eigenstates in a two-level system by a sequence of instantaneous projective measurements. Three cases of the manipulations are studied: the manipulation of optimal measurement-based control; the optimal measurement-based manipulation with the effect of free evolution of system; and the external control fields being used to compensate for the effect caused by the free evolution. Numerical simulations are conducted to verify the results obtained from the theoretically analytical solutions. The optimal parameters for each manipulation case are obtained. The experimental results indicate that the external control fields can make the optimal measurement-based control more effective.
Characteristic Model-based Discrete-time Sliding Mode Control for Spacecraft with Variable Tilt of Flexible Structures
Lei Chen, Yan Yan, Chaoxu Mu, Changyin Sun
2016, 3(1): 42-50.
Abstract(1301) HTML (29) PDF(22)
In this paper, the finite-time attitude tracking control problem for the spacecrafts with variable tilt of flexible appendages in the conditions of exogenous disturbances and inertia uncertainties is addressed. First the characteristic modeling method is applied to the problem of the spacecraft modeling. Second, a novel adaptive sliding mode surface is designed based on the characteristic model. Furthermore, a discrete-time sliding mode control (DTSMC) law, which makes the tracking error converge into a predefined bound in finite time, is proposed by employing the parameters of characteristic model associated with the sliding mode surface to provide better performances, robustness, faster response, and higher control precision. The designed DTSMC includes the adaptive control architecture and is chattering-free. Finally, digital simulations of a sun synchronous orbit satellite (SSOS) are presented to illustrate effectiveness of the control strategies as well as to verify the practical feasibility of the rapid maneuver mission.
Kalman Filtering for Delayed Singular Systems with Multiplicative Noise
Xiao Lu, Linglong Wang, Haixia Wang, Xianghua Wang
2016, 3(1): 51-58.
Abstract(1123) HTML (21) PDF(22)
Kalman filtering problem for singular systems is dealt with, where the measurements consist of instantaneous measurements and delayed ones, and the plant includes multiplicative noise. By utilizing standard singular value decomposition, the restricted equivalent delayed system is presented, and the Kalman filters for the restricted equivalent system are given by using the well-known re-organization of innovation analysis lemma. The optimal Kalman filter for the original system is given based on the above Kalman filter by recursive Riccati equations, and a numerical example is presented to show the validity and efficiency of the proposed approach, where the comparison between the filter and predictor is also given.
Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information
Dong Shen, Yun Xu
2016, 3(1): 59-67.
Abstract(1396) HTML (19) PDF(23)
An iterative learning control (ILC) algorithm using quantized error information is given in this paper for both linear and nonlinear discrete-time systems with stochastic noises. A logarithmic quantizer is used to guarantee an adaptive improvement in tracking performance. A decreasing learning gain is introduced into the algorithm to suppress the effects of stochastic noises and quantization errors. The input sequence is proved to converge strictly to the optimal input under the given index. Illustrative simulations are given to verify the theoretical analysis.
A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks
Zhen Hong, Rui Wang, Xile Li
2016, 3(1): 68-77.
Abstract(1230) HTML (19) PDF(18)
How to design an energy-efficient algorithm to maximize the network lifetime in complicated scenarios is a critical problem for heterogeneous wireless sensor networks (HWSN). In this paper, a clustering-tree topology control algorithm based on the energy forecast (CTEF) is proposed for saving energy and ensuring network load balancing, while considering the link quality, packet loss rate, etc. In CTEF, the average energy of the network is accurately predicted per round (the lifetime of the network is denoted by rounds) in terms of the difference between the ideal and actual average residual energy using central limit theorem and normal distribution mechanism, simultaneously. On this basis, cluster heads are selected by cost function (including the energy, link quality and packet loss rate) and their distance. The non-cluster heads are determined to join the cluster through the energy, distance and link quality. Furthermore, several noncluster heads in each cluster are chosen as the relay nodes for transmitting data through multi-hop communication to decrease the load of each cluster-head and prolong the lifetime of the network. The simulation results show the efficiency of CTEF. Compared with low-energy adaptive clustering hierarchy (LEACH), energy dissipation forecast and clustering management (EDFCM) and efficient and dynamic clustering scheme (EDCS) protocols, CTEF has longer network lifetime and receives more data packets at base station.
MAS Based Distributed Automatic Generation Control for Cyber-Physical Microgrid System
Zhongwen Li, Chuanzhi Zang, Peng Zeng, Haibin Yu, Hepeng Li
2016, 3(1): 78-89.
Abstract(1276) HTML (29) PDF(23)
The microgrid is a typical cyber-physical microgrid system (CPMS). The physical unconventional distributed generators (DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components, such as the embedded computer and communication network, are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid, the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information (such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system (MAS). Based on the global information from cyber components of CPMS, automatic generation control (AGC) and automatic voltage control (AVC) are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods.
Performance Measures for Systems in Multiple Environments
Baoliang Liu, Lirong Cui, Shubin Si, Yanqing Wen
2016, 3(1): 90-95.
Abstract(1179) HTML (22) PDF(11)
In this paper, the system which operates in multiple environments is studied. The environment process is governed by a Markov process, and the deterioration process is governed by another Markov process given the system in a certain environment. In terms of the above two processes, a new Markov process is constructed to represent the evolution of the system. In terms of Ion-channel modeling theory, Markov process theory and matrix partition method, some reliability indexes for the system are obtained, i.e., system reliability, environment reliability, system multiple-interval reliability, system availability, environment availability, system multiple-point availability, etc. Finally, a numerical example is given to illustrate the results obtained in the paper.
Output-feedback Dynamic Surface Control for a Class of Nonlinear Non-minimum Phase Systems
Shanwei Su
2016, 3(1): 96-104.
Abstract(1181) HTML (25) PDF(12)
In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems. To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control (DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed outputfeedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.
Adaptive Robust Control for a Class of Uncertain MIMO Non-affine Nonlinear Systems
Longsheng Chen, Qi Wang
2016, 3(1): 105-112.
Abstract(1350) HTML (22) PDF(23)
In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multioutput (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO nonaffine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem, and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible "controller singularity" problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control (DSC) method is applied to solve the problem of "explosion of complexity" in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.