Autonomous underwater vehicles (AUVs) navigating in complex sea conditions usually require a strong control system to keep the fastness and stability. The nonlinear trajectory tracking control system of a new AUV in c...Autonomous underwater vehicles (AUVs) navigating in complex sea conditions usually require a strong control system to keep the fastness and stability. The nonlinear trajectory tracking control system of a new AUV in complex sea conditions was presented. According to the theory of submarines,the six-DOF kinematic and dynamic models were decomposed into two mutually non-coupled vertical and horizontal plane subsystems. Then,different sliding mode control algorithms were used to study the trajectory tracking control. Because the yaw angle and yaw angle rate rather than the displacement of the new AUV can be measured directly on the horizontal plane,the sliding mode control algorithm combining cross track error method and line of sight method was used to fulfill its high-precision trajectory tracking control in the complex sea conditions. As the vertical displacement of the new AUV can be measured,in order to achieve the tracking of time-varying depth signal,a stable sliding mode controller was designed based on the single-input multi-state system,which took into account the characteristic of the hydroplane and the amplitude and rate constraints of the hydroplane angle. Moreover,the application of dynamic boundary layer can improve the robustness and control accuracy of the system. The computational results show that the designed sliding mode control systems of the horizontal and vertical planes can ensure the trajectory tracking performance and accuracy of the new AUV in complex sea conditions. The impacts of currents and waves on the sliding mode controller of the new AUV were analyzed qualitatively and quantitatively by comparing the trajectory tracking performance of the new AUV in different sea conditions,which provides an effective theoretical guidance and technical support for the control system design of the new AUV in real complex environment.展开更多
A dynamic velocity feed-forward compensation （RBF-NN） dynamic model identification was presented for control （DVFCC） approach with RBF neural network the adaptive trajectory tracking of industrial robots. The prop...A dynamic velocity feed-forward compensation （RBF-NN） dynamic model identification was presented for control （DVFCC） approach with RBF neural network the adaptive trajectory tracking of industrial robots. The proposed control approach combined the advantages of traditional feedback closed-loop position control and computed torque control based on inverse dynamic model. The feed-forward compensator used a nominal robot dynamics as accurate dynamic model and on-line identification with RBF-NN as uncertain part to improve dynamic modeling accu- racy. The proposed compensation was applied as velocity feed-forward by an inverse velocity controller that can con- vert torque signal into velocity in the standard industrial controller. Then, the need for a torque control interface was avoided in the real-time dynamic control of industrial robot. The simulations and experiments were carried out on a gas cutting manipulator. The results show that the proposed control approach can reduce steady-state error, suppress overshoot and enhance tracking accuracy and efficiency in joint space and Cartesian space, especially under high- speed condition.展开更多
This paper investigates the H∞ trajectory tracking control for a class of nonlinear systems with time- varying delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality （LMI） techniq...This paper investigates the H∞ trajectory tracking control for a class of nonlinear systems with time- varying delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality （LMI） technique. A unified model consisting of a linear delayed dynamic system and a bounded static nonlinear operator is introduced, which covers most of the nonlinear systems with bounded nonlinear terms, such as the one-link robotic manipulator, chaotic systems, complex networks, the continuous stirred tank reactor （CSTR）, and the standard genetic regulatory network （SCRN）. First, the definition of the tracking control is given. Second, the H∞ performance analysis of the closed-loop system including this unified model, reference model, and state feedback controller is presented. Then criteria on the tracking controller design are derived in terms of LMIs such that the output of the closed-loop system tracks the given reference signal in the H∞ sense. The reference model adopted here is modified to be more flexible. A scaling factor is introduced to deal with the disturbance such that the control precision is improved. Finally, a CSTR system is provided to demonstrate the effectiveness of the established control laws.展开更多
基金Project(2006AA09Z235) supported by the National High Technology Research and Development Program of ChinaProject(CX2009B003) supported by Hunan Provincial Innovation Foundation For Postgraduates,China
文摘Autonomous underwater vehicles (AUVs) navigating in complex sea conditions usually require a strong control system to keep the fastness and stability. The nonlinear trajectory tracking control system of a new AUV in complex sea conditions was presented. According to the theory of submarines,the six-DOF kinematic and dynamic models were decomposed into two mutually non-coupled vertical and horizontal plane subsystems. Then,different sliding mode control algorithms were used to study the trajectory tracking control. Because the yaw angle and yaw angle rate rather than the displacement of the new AUV can be measured directly on the horizontal plane,the sliding mode control algorithm combining cross track error method and line of sight method was used to fulfill its high-precision trajectory tracking control in the complex sea conditions. As the vertical displacement of the new AUV can be measured,in order to achieve the tracking of time-varying depth signal,a stable sliding mode controller was designed based on the single-input multi-state system,which took into account the characteristic of the hydroplane and the amplitude and rate constraints of the hydroplane angle. Moreover,the application of dynamic boundary layer can improve the robustness and control accuracy of the system. The computational results show that the designed sliding mode control systems of the horizontal and vertical planes can ensure the trajectory tracking performance and accuracy of the new AUV in complex sea conditions. The impacts of currents and waves on the sliding mode controller of the new AUV were analyzed qualitatively and quantitatively by comparing the trajectory tracking performance of the new AUV in different sea conditions,which provides an effective theoretical guidance and technical support for the control system design of the new AUV in real complex environment.
文摘A dynamic velocity feed-forward compensation （RBF-NN） dynamic model identification was presented for control （DVFCC） approach with RBF neural network the adaptive trajectory tracking of industrial robots. The proposed control approach combined the advantages of traditional feedback closed-loop position control and computed torque control based on inverse dynamic model. The feed-forward compensator used a nominal robot dynamics as accurate dynamic model and on-line identification with RBF-NN as uncertain part to improve dynamic modeling accu- racy. The proposed compensation was applied as velocity feed-forward by an inverse velocity controller that can con- vert torque signal into velocity in the standard industrial controller. Then, the need for a torque control interface was avoided in the real-time dynamic control of industrial robot. The simulations and experiments were carried out on a gas cutting manipulator. The results show that the proposed control approach can reduce steady-state error, suppress overshoot and enhance tracking accuracy and efficiency in joint space and Cartesian space, especially under high- speed condition.
基金supported by the National Natural Science Foundation of China(Nos.61222310,61174142,and 61374021)the Zhejiang Provincial Natural Science Foundation of China(No.LZ14F030002)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education of China(Nos.20120101110115 and 20130101110109)the Fundamental Research Funds for the Central Universities,China(No.2014XZZX003-12)
文摘This paper investigates the H∞ trajectory tracking control for a class of nonlinear systems with time- varying delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality （LMI） technique. A unified model consisting of a linear delayed dynamic system and a bounded static nonlinear operator is introduced, which covers most of the nonlinear systems with bounded nonlinear terms, such as the one-link robotic manipulator, chaotic systems, complex networks, the continuous stirred tank reactor （CSTR）, and the standard genetic regulatory network （SCRN）. First, the definition of the tracking control is given. Second, the H∞ performance analysis of the closed-loop system including this unified model, reference model, and state feedback controller is presented. Then criteria on the tracking controller design are derived in terms of LMIs such that the output of the closed-loop system tracks the given reference signal in the H∞ sense. The reference model adopted here is modified to be more flexible. A scaling factor is introduced to deal with the disturbance such that the control precision is improved. Finally, a CSTR system is provided to demonstrate the effectiveness of the established control laws.
