A new active control scheme, based on neural network, for the suppression of oscillation in multiple-degree-of-freedom (MDOF) offshore platforms, is studied in this paper. With the main advantages of neural network, i...A new active control scheme, based on neural network, for the suppression of oscillation in multiple-degree-of-freedom (MDOF) offshore platforms, is studied in this paper. With the main advantages of neural network, i.e. the inherent robustness, fault tolerance, and generalized capability of its parallel massive interconnection structure, the active structural control of offshore platforms under random waves is accomplished by use of the BP neural network model. The neural network is trained offline with the data generated from numerical analysis, and it simulates the process of Classical Linear Quadratic Regular Control for the platform under random waves. After the learning phase, the trained network has learned about the nonlinear dynamic behavior of the active control system, and is capable of predicting the active control forces of the next time steps. The results obtained show that the active control is feasible and effective, and it finally overcomes time delay owing to the robustness, fault tolerance, and generalized capability of artificial neural network.展开更多
A cosimulation platform was established for distributed control systems via heterogeneous network,which integrated OPNET and Matlab/Simulink.The communication node in this cosimulation platform was built based on OSI ...A cosimulation platform was established for distributed control systems via heterogeneous network,which integrated OPNET and Matlab/Simulink.The communication node in this cosimulation platform was built based on OSI model and UDP protocol,which was adopted as the transportation layer protocol.Data exchanged between the data source module and the specified node.It was fulfilled by revising the corresponding protocol modules based on the characteristics of UDP.The effectiveness of the constructed simulation platform was demonstrated by a numerical example.展开更多
文摘A new active control scheme, based on neural network, for the suppression of oscillation in multiple-degree-of-freedom (MDOF) offshore platforms, is studied in this paper. With the main advantages of neural network, i.e. the inherent robustness, fault tolerance, and generalized capability of its parallel massive interconnection structure, the active structural control of offshore platforms under random waves is accomplished by use of the BP neural network model. The neural network is trained offline with the data generated from numerical analysis, and it simulates the process of Classical Linear Quadratic Regular Control for the platform under random waves. After the learning phase, the trained network has learned about the nonlinear dynamic behavior of the active control system, and is capable of predicting the active control forces of the next time steps. The results obtained show that the active control is feasible and effective, and it finally overcomes time delay owing to the robustness, fault tolerance, and generalized capability of artificial neural network.
基金National Natural Science Foundation of China(No.61573237)Natural Science Foundation of Shanghai,China(No.13ZR1416300)
文摘A cosimulation platform was established for distributed control systems via heterogeneous network,which integrated OPNET and Matlab/Simulink.The communication node in this cosimulation platform was built based on OSI model and UDP protocol,which was adopted as the transportation layer protocol.Data exchanged between the data source module and the specified node.It was fulfilled by revising the corresponding protocol modules based on the characteristics of UDP.The effectiveness of the constructed simulation platform was demonstrated by a numerical example.
