Aimed at uncertainties and model's impreciseness, nonlinearity and time-variability of depth control system in autonomous underwater vehicle (AUV), a depth predictive control method was put forward based on rough ...Aimed at uncertainties and model's impreciseness, nonlinearity and time-variability of depth control system in autonomous underwater vehicle (AUV), a depth predictive control method was put forward based on rough set (RS) and least squares support vector machine (LSSVM). By using RS theory, the monitor data attribute of AUV was reduced to eliminate the redundant information and to improve efficiency. Then, LSSVM model was trained by using the reduced rules, and its parameters were optimized by using chaos theory for the higher accurate control. Taken an AUV typed NPS Phoenix as an example, its depth step response, horizontal rudder and pitch change were simulated. The simulation results show that the method improves the model's accuracy and has better real-time response, fault-tolerant ability, reliability and strong anti-interfere capability.展开更多
As an energy generating equipment, the engine-generator set supplies power to the electric transmission. Therefore, its control is one of the key technologies of electric vehicles. Based on the discussion about the de...As an energy generating equipment, the engine-generator set supplies power to the electric transmission. Therefore, its control is one of the key technologies of electric vehicles. Based on the discussion about the demands to the engine-generator set in tracked vehicles, the detailed function of engine-generator and the control strategy are determined. The hardware and software of the control system are also developed and tested in a prototype vehicle. The experiment results show that the control system has good reliability and can satisfy the power requirements of vehicles under all operating conditions.展开更多
文摘Aimed at uncertainties and model's impreciseness, nonlinearity and time-variability of depth control system in autonomous underwater vehicle (AUV), a depth predictive control method was put forward based on rough set (RS) and least squares support vector machine (LSSVM). By using RS theory, the monitor data attribute of AUV was reduced to eliminate the redundant information and to improve efficiency. Then, LSSVM model was trained by using the reduced rules, and its parameters were optimized by using chaos theory for the higher accurate control. Taken an AUV typed NPS Phoenix as an example, its depth step response, horizontal rudder and pitch change were simulated. The simulation results show that the method improves the model's accuracy and has better real-time response, fault-tolerant ability, reliability and strong anti-interfere capability.
文摘As an energy generating equipment, the engine-generator set supplies power to the electric transmission. Therefore, its control is one of the key technologies of electric vehicles. Based on the discussion about the demands to the engine-generator set in tracked vehicles, the detailed function of engine-generator and the control strategy are determined. The hardware and software of the control system are also developed and tested in a prototype vehicle. The experiment results show that the control system has good reliability and can satisfy the power requirements of vehicles under all operating conditions.
