This work is to develop a blending-based multiple model adaptive explicit predictive control scheme for nonlinear MiMo systems that can handle parametric uncertainties.Here,for each identification model,an explicit no...This work is to develop a blending-based multiple model adaptive explicit predictive control scheme for nonlinear MiMo systems that can handle parametric uncertainties.Here,for each identification model,an explicit nonlinear model predictive control(ENMPC)law is computed in advance for the corresponding model.The generated control inputs from the set of ENMPC controllers are being blended online using a weighting vector that is continuously updated by the proposed adaptive identification schemes.The proposed control scheme is used to govern the tracking of a highly nonlinear helicopter model known as the twin rotor MIMO system(TRMS).Here,an extended Kalman filter(EKF)is used to estimate the unavailable states of the TRMS.Finally,simulation and experimental results are presented to prove that the proposed controller gives better performance than some reported works in the literature.The effectiveness of the proposed controller is demonstrated by experimental studies of the TRMS model.展开更多
The suspension system is a key element in motor vehicles. Advancements in electronics and microprocessor technology have led to the realization of mechatronic suspensions. Since its introduction in some production mot...The suspension system is a key element in motor vehicles. Advancements in electronics and microprocessor technology have led to the realization of mechatronic suspensions. Since its introduction in some production motorcars in the 1980 s, it has remained an area which sees active research and development, and this will likely continue for many years to come. With the aim of identifying current trends and future focus areas, this paper presents a review on the state-of-the-art of mechatronic suspensions. First, some commonly used classifications of mechatronic suspensions are presented. This is followed by a discussion on some of the actuating mechanisms used to provide control action. A survey is then reported on the many types of control approaches, including look-ahead preview, predictive, fuzzy logic, proportional–integral–derivative(PID), optimal, robust, adaptive, robust adaptive,and switching control. In conclusion, hydraulic actuators are most commonly used, but they impose high power requirements, limiting practical realizations of active suspensions. Electromagnetic actuators are seen to hold the promise of lower power requirements, and rigorous research and development should be conducted to make them commercially usable. Current focus on control methods that are robust to suspension parameter variations also seems to produce limited performance improvements, and future control approaches should be adaptive to the changeable driving conditions.展开更多
文摘This work is to develop a blending-based multiple model adaptive explicit predictive control scheme for nonlinear MiMo systems that can handle parametric uncertainties.Here,for each identification model,an explicit nonlinear model predictive control(ENMPC)law is computed in advance for the corresponding model.The generated control inputs from the set of ENMPC controllers are being blended online using a weighting vector that is continuously updated by the proposed adaptive identification schemes.The proposed control scheme is used to govern the tracking of a highly nonlinear helicopter model known as the twin rotor MIMO system(TRMS).Here,an extended Kalman filter(EKF)is used to estimate the unavailable states of the TRMS.Finally,simulation and experimental results are presented to prove that the proposed controller gives better performance than some reported works in the literature.The effectiveness of the proposed controller is demonstrated by experimental studies of the TRMS model.
基金Project supported by the Ministry of Education,Malaysia(No.ERGS/1/2012/TK01/UKM/02/4)
文摘The suspension system is a key element in motor vehicles. Advancements in electronics and microprocessor technology have led to the realization of mechatronic suspensions. Since its introduction in some production motorcars in the 1980 s, it has remained an area which sees active research and development, and this will likely continue for many years to come. With the aim of identifying current trends and future focus areas, this paper presents a review on the state-of-the-art of mechatronic suspensions. First, some commonly used classifications of mechatronic suspensions are presented. This is followed by a discussion on some of the actuating mechanisms used to provide control action. A survey is then reported on the many types of control approaches, including look-ahead preview, predictive, fuzzy logic, proportional–integral–derivative(PID), optimal, robust, adaptive, robust adaptive,and switching control. In conclusion, hydraulic actuators are most commonly used, but they impose high power requirements, limiting practical realizations of active suspensions. Electromagnetic actuators are seen to hold the promise of lower power requirements, and rigorous research and development should be conducted to make them commercially usable. Current focus on control methods that are robust to suspension parameter variations also seems to produce limited performance improvements, and future control approaches should be adaptive to the changeable driving conditions.
