This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.Based on the estimation theory,a synthetic error-i...This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.Based on the estimation theory,a synthetic error-index(SEI)criterion for the neural network models has been developed.By using the powerful training algorithm of recursive prediction error (RPE),two simulated non-linear systems are studied,and the results show that the synthetic error-index criterion can be used to verify the dynamic neural network models.Furthermore,the proposed technique is much simple in calculation than that of the effective correlation tests.Finally,some problems required by further study are discussed.展开更多
To provide a suitable model for AUV simulation and control purposes, a general nonlinear dynamic model including a novel thruster hydrodynamics model was derived. Based on the modeling method, the "AUV-XX" s...To provide a suitable model for AUV simulation and control purposes, a general nonlinear dynamic model including a novel thruster hydrodynamics model was derived. Based on the modeling method, the "AUV-XX" simulation platform was established to carry out fundamental tests on its motion characteristics, stability, and controllability. A motion control strategy consisting of both position and speed control in a horizontal plane was designed for different task assignments of underwater vehicles. Combined control of heave and pitch was adopted to compensate for the reduction of vertical tunnel thrusters when the vehicle is moving at a high speed. An improved S-surface controller based on the capacitor plate model was developed with flexible gain selections made possible by different forms of restricting the error and changing the rate of the error. Simulation results show that the derived general mathematical model together with simulation platform can provide a test bed for fundamental tests of motion control. Additionally, the capacitor plate model S-surface control shows a good performance in guiding the vehicle to achieve the desired position and speed with sufficient accuracy.展开更多
文摘This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.Based on the estimation theory,a synthetic error-index(SEI)criterion for the neural network models has been developed.By using the powerful training algorithm of recursive prediction error (RPE),two simulated non-linear systems are studied,and the results show that the synthetic error-index criterion can be used to verify the dynamic neural network models.Furthermore,the proposed technique is much simple in calculation than that of the effective correlation tests.Finally,some problems required by further study are discussed.
基金the National Science Foundation under Grant No.50879014,No.50909025
文摘To provide a suitable model for AUV simulation and control purposes, a general nonlinear dynamic model including a novel thruster hydrodynamics model was derived. Based on the modeling method, the "AUV-XX" simulation platform was established to carry out fundamental tests on its motion characteristics, stability, and controllability. A motion control strategy consisting of both position and speed control in a horizontal plane was designed for different task assignments of underwater vehicles. Combined control of heave and pitch was adopted to compensate for the reduction of vertical tunnel thrusters when the vehicle is moving at a high speed. An improved S-surface controller based on the capacitor plate model was developed with flexible gain selections made possible by different forms of restricting the error and changing the rate of the error. Simulation results show that the derived general mathematical model together with simulation platform can provide a test bed for fundamental tests of motion control. Additionally, the capacitor plate model S-surface control shows a good performance in guiding the vehicle to achieve the desired position and speed with sufficient accuracy.
