Active control of turbine blade tip clearance continues to be a concern in design and control of gas turbines. Ever increasing demands for improved efficiency and higher operating temperatures require more stringent t...Active control of turbine blade tip clearance continues to be a concern in design and control of gas turbines. Ever increasing demands for improved efficiency and higher operating temperatures require more stringent tolerances on turbine tip clearance. In this paper, a turbine tip clearance control apparatus and a model of turbine tip clearance are proposed; an implicit active generalized predictive control （GPC）, with auto-regressive （AR） error modification and fuzzy adjustment on control horizon, is presented, as well as a quantitative analysis method of robust per- turbation radius of the system. The active clearance control （ACC） of aero-engine turbine tip clear- ance is evaluated in a lapse-rate take-off transient, along with the comparative and quantitative analysis of the stability and robustness of the active tip clearance control system. The results show that the resultant active tip clearance control system with the improved GPC has favorable steadystate and dynamic performance and benefits of increased efficiency, reduced specific fuel consump- tion, and additional service life.展开更多
To develop the pressure control algorithm for active braking of adaptive cruise control（ACC） system,a test bench with real parts of the tested vehicle is built.With the dynamic analysis of the active braking actuato...To develop the pressure control algorithm for active braking of adaptive cruise control（ACC） system,a test bench with real parts of the tested vehicle is built.With the dynamic analysis of the active braking actuators,it is demonstrated that different duty of pulse-width modulation（PWM） signals could control the pressure changing rate of the wheel cylinder.To obtain that signal,a modified proportional-integral-differential（PID） control algorithm is developed using the variable parameter method,the control value reset method,the dead zone method and the integral saturation method.Experimental results show that the delay and overshoot of the pressure response could be reduced considerably using the modified PID algorithm compared with the conventional one.The proposed pressure control algorithm could be used for the further development of the ACC＇s controller.展开更多
This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed ra...This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in Taiwan.The MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient navigation.Simulated onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and ACC.The simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel efficiency.Specifically,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning methods.These findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic scenarios.Future research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental conditions.This study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems.展开更多
A new adaptive cruise control (ACC) method based on the desired safety headway distance is investigated for improving the vehicle traffic safety at high speed by regulating the additional throttle opening and braking ...A new adaptive cruise control (ACC) method based on the desired safety headway distance is investigated for improving the vehicle traffic safety at high speed by regulating the additional throttle opening and braking torque of driving wheels only. The selection of headway distance sensors, the determination of desired safety headway distance and desired deceleration are elaborated. The ACC flowchart and simulation, as well as signal misinformation and its resolutions are described. The simulation proves that the new ACC method is simpler and feasible. The new method is easily integrated ACC with ABS/ASR to form an organic ABS/ASR/ACC system.展开更多
文摘Active control of turbine blade tip clearance continues to be a concern in design and control of gas turbines. Ever increasing demands for improved efficiency and higher operating temperatures require more stringent tolerances on turbine tip clearance. In this paper, a turbine tip clearance control apparatus and a model of turbine tip clearance are proposed; an implicit active generalized predictive control （GPC）, with auto-regressive （AR） error modification and fuzzy adjustment on control horizon, is presented, as well as a quantitative analysis method of robust per- turbation radius of the system. The active clearance control （ACC） of aero-engine turbine tip clear- ance is evaluated in a lapse-rate take-off transient, along with the comparative and quantitative analysis of the stability and robustness of the active tip clearance control system. The results show that the resultant active tip clearance control system with the improved GPC has favorable steadystate and dynamic performance and benefits of increased efficiency, reduced specific fuel consump- tion, and additional service life.
基金Supported by the Ministerial Level Advanced Research Foundation(40401040302)
文摘To develop the pressure control algorithm for active braking of adaptive cruise control（ACC） system,a test bench with real parts of the tested vehicle is built.With the dynamic analysis of the active braking actuators,it is demonstrated that different duty of pulse-width modulation（PWM） signals could control the pressure changing rate of the wheel cylinder.To obtain that signal,a modified proportional-integral-differential（PID） control algorithm is developed using the variable parameter method,the control value reset method,the dead zone method and the integral saturation method.Experimental results show that the delay and overshoot of the pressure response could be reduced considerably using the modified PID algorithm compared with the conventional one.The proposed pressure control algorithm could be used for the further development of the ACC＇s controller.
基金National Science and Technology Council,Taiwan,for financially supporting this research(Grant No.NSTC 113-2221-E-018-011)Ministry of Education’s Teaching Practice Research Program,Taiwan(PSK1120797 and PSK1134099).
文摘This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in Taiwan.The MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient navigation.Simulated onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and ACC.The simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel efficiency.Specifically,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning methods.These findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic scenarios.Future research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental conditions.This study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems.
文摘A new adaptive cruise control (ACC) method based on the desired safety headway distance is investigated for improving the vehicle traffic safety at high speed by regulating the additional throttle opening and braking torque of driving wheels only. The selection of headway distance sensors, the determination of desired safety headway distance and desired deceleration are elaborated. The ACC flowchart and simulation, as well as signal misinformation and its resolutions are described. The simulation proves that the new ACC method is simpler and feasible. The new method is easily integrated ACC with ABS/ASR to form an organic ABS/ASR/ACC system.
