This work focuses on motion control of high-velocity autonomous underwater vehicle(AUV).Conventional methods are effective solutions to motion control of low-and-medium-velocity AUV.Usually not taken into consideratio...This work focuses on motion control of high-velocity autonomous underwater vehicle(AUV).Conventional methods are effective solutions to motion control of low-and-medium-velocity AUV.Usually not taken into consideration in the control model,the residual dead load and damping force which vary with the AUV’s velocity tend to result in difficulties in motion control or even failure in convergence in the case of high-velocity movement.With full consideration given to the influence of residual dead load and changing damping force upon AUV motion control,a novel sliding-mode controller(SMC)is proposed in this work.The stability analysis of the proposed controller is carried out on the basis of Lyapunov function.The sea trials results proved the superiority of the sliding-mode controller over sigmoid-function-based controller(SFC).The novel controller demonstrated its effectiveness by achieving admirable control results in the case of high-velocity movement.展开更多
This paper considers the fourth stage of development of hierarchical control ofindustrial processes to the intelligent control and optimization stage, and reviews what theauthor and his Group have been investigating f...This paper considers the fourth stage of development of hierarchical control ofindustrial processes to the intelligent control and optimization stage, and reviews what theauthor and his Group have been investigating for the past decade in the on-line steadystate hierarchical intelligent control of large-scale industrial processes (LSIP). This papergives a definition of intelligent control of large-scale systems first, and then reviews the useof neural networks for identification and optimization, the use of expert systems to solvesome kinds of hierarchical multi-objective optimization problems by an intelligent decisionunit (ID), the use of fuzzy logic control, and the use of iterative learning control. Severalimplementation examples are introduced. This paper reviews other main achievements ofthe Group also. Finally this paper gives a perspective of future development.展开更多
基金Project(2011AA09A106)supported by the Hi-tech Research and Development Program of ChinaProjects(51179035,51779057)supported by the National Natural Science Foundation of ChinaProject(2015ZX01041101)supported by Major National Science and Technology of China
文摘This work focuses on motion control of high-velocity autonomous underwater vehicle(AUV).Conventional methods are effective solutions to motion control of low-and-medium-velocity AUV.Usually not taken into consideration in the control model,the residual dead load and damping force which vary with the AUV’s velocity tend to result in difficulties in motion control or even failure in convergence in the case of high-velocity movement.With full consideration given to the influence of residual dead load and changing damping force upon AUV motion control,a novel sliding-mode controller(SMC)is proposed in this work.The stability analysis of the proposed controller is carried out on the basis of Lyapunov function.The sea trials results proved the superiority of the sliding-mode controller over sigmoid-function-based controller(SFC).The novel controller demonstrated its effectiveness by achieving admirable control results in the case of high-velocity movement.
基金This research is supported by the National Science Fund and is supported by the High Technology Plan (863 plan)of P.R.of China
文摘This paper considers the fourth stage of development of hierarchical control ofindustrial processes to the intelligent control and optimization stage, and reviews what theauthor and his Group have been investigating for the past decade in the on-line steadystate hierarchical intelligent control of large-scale industrial processes (LSIP). This papergives a definition of intelligent control of large-scale systems first, and then reviews the useof neural networks for identification and optimization, the use of expert systems to solvesome kinds of hierarchical multi-objective optimization problems by an intelligent decisionunit (ID), the use of fuzzy logic control, and the use of iterative learning control. Severalimplementation examples are introduced. This paper reviews other main achievements ofthe Group also. Finally this paper gives a perspective of future development.
