Functional inspection is a type of preventive maintenance of Reliability Centered Maintenance （ RCM）. We, in this paper, establish a functional inspection model（ FIM） the cost model and the availability model for ...Functional inspection is a type of preventive maintenance of Reliability Centered Maintenance （ RCM）. We, in this paper, establish a functional inspection model（ FIM） the cost model and the availability model for the immeasurable potential failure state based on the delay time concept. This model can be used to determine the appropriate Functional Inspection Interval（FII） to achieve the goal of specific cost and availability and to assist in maintenance decision making.展开更多
This paper deals with the observer design for a class of Interconnected Takagi±Sugeno(TS)systems with Immeasurable Premise Variables(IPV).We first investigate the D-stability of Luenberger-like interconnected mul...This paper deals with the observer design for a class of Interconnected Takagi±Sugeno(TS)systems with Immeasurable Premise Variables(IPV).We first investigate the D-stability of Luenberger-like interconnected multiple observers.However,the resulting constraints can be somewhat conservative due to the use of a common Lyapunov matrix.Then,the so-called Finsler's lemma is used to relax the D-stability conditions through the introduction of additional slack variables providing more flexibility and extra degrees of freedom.The designed conditions are expressed as Linear Matrix Inequalities(LMIs).The proposed approaches are applied in simulation to a Proton Exchange Membrane Fuel Cell(PEMFC)system and a four-tank system.展开更多
In this paper,an adaptive neural-network(NN)output feedback optimal control problem is studied for a class of strict-feedback nonlinear systems with unknown internal dynamics,input saturation and state constraints.Neu...In this paper,an adaptive neural-network(NN)output feedback optimal control problem is studied for a class of strict-feedback nonlinear systems with unknown internal dynamics,input saturation and state constraints.Neural networks are used to approximate unknown internal dynamics and an adaptive NN state observer is developed to estimate immeasurable states.Under the framework of the backstepping design,by employing the actor-critic architecture and constructing the tan-type Barrier Lyapunov function(BLF),the virtual and actual optimal controllers are developed.In order to accomplish optimal control effectively,a simplified reinforcement learning(RL)algorithm is designed by deriving the updating laws from the negative gradient of a simple positive function,instead of employing existing optimal control methods.In addition,to ensure that all the signals in the closed-loop system are bounded and the output can follow the reference signal within a bounded error,all state variables are confined within their compact sets all times.Finally,a simulation example is given to illustrate the effectiveness of the proposed control strategy.展开更多
Article title:OBSERVER DESIGN BASED ON D-STABILITY AND FINSLER’S LEMMA FOR INTERCONNECTED TAKAGI-SUGENO SYSTEMS WITH IMMEASURABLE PREMISE VARIABLES Authors:Lamia Ouhib,&Redouane and KARA.
基金the National Equipment Advanced Research Foundation under Grant No.9140A04050707JW0507
文摘Functional inspection is a type of preventive maintenance of Reliability Centered Maintenance （ RCM）. We, in this paper, establish a functional inspection model（ FIM） the cost model and the availability model for the immeasurable potential failure state based on the delay time concept. This model can be used to determine the appropriate Functional Inspection Interval（FII） to achieve the goal of specific cost and availability and to assist in maintenance decision making.
文摘This paper deals with the observer design for a class of Interconnected Takagi±Sugeno(TS)systems with Immeasurable Premise Variables(IPV).We first investigate the D-stability of Luenberger-like interconnected multiple observers.However,the resulting constraints can be somewhat conservative due to the use of a common Lyapunov matrix.Then,the so-called Finsler's lemma is used to relax the D-stability conditions through the introduction of additional slack variables providing more flexibility and extra degrees of freedom.The designed conditions are expressed as Linear Matrix Inequalities(LMIs).The proposed approaches are applied in simulation to a Proton Exchange Membrane Fuel Cell(PEMFC)system and a four-tank system.
基金This work was supported by National Natural Science Foundation of China(61822307,61773188).
文摘In this paper,an adaptive neural-network(NN)output feedback optimal control problem is studied for a class of strict-feedback nonlinear systems with unknown internal dynamics,input saturation and state constraints.Neural networks are used to approximate unknown internal dynamics and an adaptive NN state observer is developed to estimate immeasurable states.Under the framework of the backstepping design,by employing the actor-critic architecture and constructing the tan-type Barrier Lyapunov function(BLF),the virtual and actual optimal controllers are developed.In order to accomplish optimal control effectively,a simplified reinforcement learning(RL)algorithm is designed by deriving the updating laws from the negative gradient of a simple positive function,instead of employing existing optimal control methods.In addition,to ensure that all the signals in the closed-loop system are bounded and the output can follow the reference signal within a bounded error,all state variables are confined within their compact sets all times.Finally,a simulation example is given to illustrate the effectiveness of the proposed control strategy.
文摘Article title:OBSERVER DESIGN BASED ON D-STABILITY AND FINSLER’S LEMMA FOR INTERCONNECTED TAKAGI-SUGENO SYSTEMS WITH IMMEASURABLE PREMISE VARIABLES Authors:Lamia Ouhib,&Redouane and KARA.
