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.1, 2015

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Table of Contents
2015, 2(1): 0-0.
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EDITORIAL
Guest Editorial for Special Issue on Autonomous Control of Unmanned Aerial Vehicles
Derong Liu, Changyin Sun, Bin Xian
2015, 2(1): 1-1.
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PAPERS
Attitude Control of Multiple Rigid Bodies with Uncertainties and Disturbances
Yuanqing Xia, Ning Zhou, Kunfeng Lu, Yong Li
2015, 2(1): 2-10.
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Decentralized attitude synchronization and tracking control for multiple rigid bodies are investigated in this paper. In the presence of inertia uncertainties and environmental disturbances, we propose a class of decentralized adaptive sliding mode control laws. An adaptive control strategy is adopted to reject the uncertainties and disturbances. Using the Lyapunov approach and graph theory, it is shown that the control laws can guarantee a group of rigid bodies to track the desired time-varying attitude and angular velocity while maintaining attitude synchronization with other rigid bodies in the formation. Simulation examples are provided to illustrate the feasibility and advantage of the control algorithm.
A Predator-prey Particle Swarm Optimization Approach to Multiple UCAV Air Combat Modeled by Dynamic Game Theory
Haibin Duan, Pei Li, Yaxiang Yu
2015, 2(1): 11-18.
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Dynamic game theory has received considerable attention as a promising technique for formulating control actions for agents in an extended complex enterprise that involves an adversary. At each decision making step, each side seeks the best scheme with the purpose of maximizing its own objective function. In this paper, a game theoretic approach based on predatorprey particle swarm optimization (PP-PSO) is presented, and the dynamic task assignment problem for multiple unmanned combat aerial vehicles (UCAVs) in military operation is decomposed and modeled as a two-player game at each decision stage. The optimal assignment scheme of each stage is regarded as a mixed Nash equilibrium, which can be solved by using the PP-PSO. The effectiveness of our proposed methodology is verified by a typical example of an air military operation that involves two opposing forces: the attacking force Red and the defense force Blue.
Adaptive Backstepping Tracking Control of a 6-DOF Unmanned Helicopter
Bin Xian, Jianchuan Guo, Yao Zhang
2015, 2(1): 19-24.
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This paper presents an adaptive backstepping control design for a class of unmanned helicopters with parametric uncertainties. The control objective is to let the helicopter track some pre-defined position and yaw trajectories. In order to facilitate the control design, we divide the helicopter's dynamic model into three subsystems. The proposed controller combines the backstepping method with online parameter update laws to achieve the control objective. The global asymptotical stability (GAS) of the closed-loop system is proved by a Lyapunov based stability analysis. Numerical simulations demonstrate that the controller can achieve good tracking performance in the presence of parametric uncertainties.
Robust Tracking Control of Uncertain MIMO Nonlinear Systems with Application to UAVs
Yanlong Zhou, Mou Chen, Changsheng Jiang
2015, 2(1): 25-32.
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In this paper, we consider the robust adaptive tracking control of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance. The nonlinear disturbance observer (NDO) is employed to tackle the system uncertainty as well as the external disturbance. To handle the input saturation, an auxiliary system is constructed as a saturation compensator. By using the backstepping technique and the dynamic surface method, a robust adaptive tracking control scheme is developed. The closed-loop system is proved to be uniformly ultimately bounded thorough Lyapunov stability analysis. Simulation results with application to an unmanned aerial vehicle (UAV) demonstrate the effectiveness of the proposed robust control scheme.
Robust and Accurate Monocular Visual Navigation Combining IMU for a Quadrotor
Wei Zheng, Fan Zhou, Zengfu Wang
2015, 2(1): 33-44.
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In this paper, we present a multi-sensor fusion based monocular visual navigation system for a quadrotor with limited payload, power and computational resources. Our system is equipped with an inertial measurement unit (IMU), a sonar and a monocular down-looking camera. It is able to work well in GPS-denied and markerless environments. Different from most of the keyframe-based visual navigation systems, our system uses the information from both keyframes and keypoints in each frame. The GPU-based speeded up robust feature (SURF) is employed for feature detection and feature matching. Based on the flight characteristics of quadrotor, we propose a refined preliminary motion estimation algorithm combining IMU data. A multi-level judgment rule is then presented which is beneficial to hovering conditions and reduces the error accumulation effectively. By using the sonar sensor, the metric scale estimation problem has been solved. We also present the novel IMU+3P (IMU with three point correspondences) algorithm for accurate pose estimation. This algorithm transforms the 6-DOF pose estimation problem into a 4-DOF problem and can obtain more accurate results with less computation time. We perform the experiments of monocular visual navigation system in real indoor and outdoor environments. The results demonstrate that the monocular visual navigation system performing in real-time has robust and accurate navigation results of the quadrotor.
Continuous Sliding Mode Controller with Disturbance Observer for Hypersonic Vehicles
Chaoxu Mu, Qun Zong, Bailing Tian, Wei Xu
2015, 2(1): 45-55.
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In this paper, a continuous sliding mode controller with disturbance observer is proposed for the tracking control of hypersonic vehicles to suppress the chattering. The finite time disturbance observer is involved to make that the continuous sliding mode controller has the property of disturbance rejection. Due to continuous terms replacing the discontinuous term of traditional sliding mode control, switching modes of velocity and altitude firstly arrive at small regions with respect to disturbance observation errors. Switching modes keep zero and velocity and altitude asymptotically converge to their reference commands after disturbance observation errors disappear. Simulation results have proved the proposed method can guarantee the tracking of velocity and altitude with continuous sliding mode control laws, and also has the fast convergence rate and robustness.
Modeling and Robust Backstepping Sliding Mode Control with Adaptive RBFNN for a Novel Coaxial Eight-rotor UAV
Cheng Peng, Yue Bai, Xun Gong, Qingjia Gao, Changjun Zhao, Yantao Tian
2015, 2(1): 56-64.
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This paper focuses on the robust attitude control of a novel coaxial eight-rotor unmanned aerial vehicles (UAV) which has higher drive capability as well as greater robustness against disturbances than quad-rotor UAV. The dynamical and kinematical model for the coaxial eight-rotor UAV is developed, which has never been proposed before. A robust backstepping sliding mode controller (BSMC) with adaptive radial basis function neural network (RBFNN) is proposed to control the attitude of the eightrotor UAV in the presence of model uncertainties and external disturbances. The combinative method of backstepping control and sliding mode control has improved robustness and simplified design procedure benefiting from the advantages of both controllers. The adaptive RBFNN as the uncertainty observer can effectively estimate the lumped uncertainties without the knowledge of their bounds for the eight-rotor UAV. Additionally, the adaptive learning algorithm, which can learn the parameters of RBFNN online and compensate the approximation error, is derived using Lyapunov stability theorem. And then the uniformly ultimate stability of the eight-rotor system is proved. Finally, simulation results demonstrate the validity of the proposed robust control method adopted in the novel coaxial eight-rotor UAV in the case of model uncertainties and external disturbances.
Trajectory Tracking of Vertical Take-off and Landing Unmanned Aerial Vehicles Based on Disturbance Rejection Control
Lu Wang, Jianbo Su
2015, 2(1): 65-73.
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We investigate the trajectory tracking problem of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAV), and propose a practical disturbance rejection control strategy. Firstly, the nonlinear error model is established completely by the modified Rodrigues parameters, while considering dynamics of the servo actuators. Then, a hierarchical control scheme is applied to design the translational and rotational controllers based on the time-scale property of each subsystem, respectively. And the linear extended state observer and auxiliary observer are used to deal with the uncertainties and saturation. At last, global stability of the closed-loop system is analyzed based on the singular perturbation theory. Simulation results show the effectiveness of the proposed control strategy.
Dynamic Multi-team Antagonistic Games Model with Incomplete Information and Its Application to Multi-UAV
Wenzhong Zha, Jie Chen, Zhihong Peng
2015, 2(1): 74-84.
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At present, the studies on multi-team antagonistic games (MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets. Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information (DMTAGII) model. For this model, the corresponding concept of perfect Bayesian Nash equilibrium (PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles (UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm. Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems.
Probabilistic Robust Linear Parameter-varying Control of a Small Helicopter Using Iterative Scenario Approach
Zhou Fang, Hua Tian, Ping Li
2015, 2(1): 85-93.
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In this paper, we present an iterative scenario approach (ISA) to design robust controllers for complex linear parameter-varying (LPV) systems with uncertainties. The robust controller synthesis problem is transformed to a scenario design problem, with the scenarios generated by identically extracting random samples on both uncertainty parameters and scheduling parameters. An iterative scheme based on the maximum volume ellipsoid cutting-plane method is used to solve the problem. Heuristic logic based on relevance ratio ranking is used to prune the redundant constraints, and thus, to improve the numerical stability of the algorithm. And further, a batching technique is presented to remarkably enhance the computational efficiency. The proposed method is applied to design an output-feedback controller for a small helicopter. Multiple uncertain physical parameters are considered, and simulation studies show that the closed-loop performance is quite good in both aspects of model tracking and dynamic decoupling. For robust LPV control problems, the proposed method is more computationally efficient than the popular stochastic ellipsoid methods.
Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design
Jingmei Zhang, Changyin Sun, Ruimin Zhang, Chengshan Qian
2015, 2(1): 94-101.
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Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.
Finite-time Attitude Control: A Finite-time Passivity Approach
Shuochen Liu, Zhiyong Geng, Junyong Sun
2015, 2(1): 102-108.
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This paper studies the finite-time attitude control problem for a rigid body. It is known that linear asymptotically stabilizing control laws can be derived from passivity properties for the system which describes the kinematic and dynamic motion of the attitude. Our approach expands this framework by defining finite-time passivity and exploring the corresponding properties. For a rigid body, the desired attitude can be tracked in finite time using the designed finite-time attitude control law. Some finitetime passivity properties for the feedback connection systems are also shown. Numerical simulations are provided to demonstrate the effectiveness of the proposed control law.
Autonomous Landing of Small Unmanned Aerial Rotorcraft Based on Monocular Vision in GPS-denied Area
Cunxiao Miao, Jingjing Li
2015, 2(1): 109-114.
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Focusing on the low-precision attitude of a current small unmanned aerial rotorcraft at the landing stage, the present paper proposes a new attitude control method for the GPS-denied scenario based on the monocular vision. Primarily, a robust landmark detection technique is developed which leverages the well-documented merits of supporting vector machines (SVMs) to enable landmark detection. Then an algorithm of nonlinear optimization based on Newton iteration method for the attitude and position of camera is put forward to reduce the projection error and get an optimized solution. By introducing the wavelet analysis into the adaptive Kalman filter, the high frequency noise of vision is filtered out successfully. At last, automatic landing tests are performed to verify the method's feasibility and effectiveness.
BRIEF PAPER
Decoupling Trajectory Tracking for Gliding Reentry Vehicles
Zixuan Liang, Zhang Ren, Xingyue Shao
2015, 2(1): 115-120.
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A decoupling trajectory tracking method for gliding reentry vehicles is presented to improve the reliability of the guidance system. Function relations between state variables and control variables are analyzed. To reduce the coupling between control channels, the multiple-input multiple-output (MIMO) tracking system is separated into a series of two single-input single-output (SISO) subsystems. Tracking laws for both velocity and altitude are designed based on the sliding mode control (SMC). The decoupling approach is verified by the Monte Carlo simulations, and compared with the linear quadratic regulator (LQR) approach in some specific conditions. Simulation results indicate that the decoupling approach owns a fast convergence speed and a strong anti-interference ability in the trajectory tracking.

IEEE/CAA Journal of Automatica Sinica

  • CiteScore 2018: 5.31
    Rank:Top 9% (Category of Control and Systems Engineering), Top 10% (Categories of Information System and Artificial Intelligence)