This article describes a method of vehicle dynamics estimation for impending rollover detection. We estimate vehicle dynamic states in presence of the road bank angle as a disturbance in the vehicle model using a robu...This article describes a method of vehicle dynamics estimation for impending rollover detection. We estimate vehicle dynamic states in presence of the road bank angle as a disturbance in the vehicle model using a robust observer. The estimated roll angle and roll rate are used to compute the rollover index which is based on the prediction of the lateral load transfer. In order to anticipate rollover detection, a new method is proposed to compute the time to rollover(TTR) using the load transfer ratio(LTR). The nonlinear model, deduced from the vehicle lateral and roll dynamics, is represented by a Takagi-Sugeno(T-S) fuzzy model. This representation is used to account for the nonlinearities of lateral cornering forces. The proposed T-S observer is designed with unmeasurable premise variables to cater for non-availability of the slip angles measurement. The proposed approach is evaluated using Car Sim simulator under different driving scenarios. Simulation results show good efficiency of the proposed T-S observer and the rollover detection method.展开更多
A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuz...A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuzzy models. The SNNM is composed of a discrete-time linear dynamic system and a bounded static nonlinear operator. Based on the global asymptotic stability analysis of the SNNMs, linear and nonlinear dynamic output feedback controllers are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities （LMIs） which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based （or fuzzy） discrete-time intelligent systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Three application examples show that the SNNMs not only make controller synthesis of neural-network-based （or fuzzy） discrete-time intelligent systems much easier, but also provide a new approach to the synthesis of the controllers for the other type of nonlinear systems.展开更多
This paper is concerned with the problem of stabilization of the Roesser type discrete-time nonlinear 2-D system that plays an important role in many practical applications. First, a discrete-time 2-D T-S fuzzy model ...This paper is concerned with the problem of stabilization of the Roesser type discrete-time nonlinear 2-D system that plays an important role in many practical applications. First, a discrete-time 2-D T-S fuzzy model is proposed to represent the underlying nonlinear 2-D system. Second, new quadratic stabilization conditions are proposed by applying relaxed quadratic stabilization technique for 2-D case. Third, for sake of further reducing conservatism, new non-quadratic stabilization conditions are also proposed by applying a new parameter-dependent Lyapunov function, matrix transformation technique, and relaxed technique for the underlying discrete-time 2-D T-S fuzzy system. Finally, a numerical example is provided to illustrate the effectiveness of the proposed results.展开更多
In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotica...In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi Sugeno （T-S） fuzzy model is employed to represent the chaotic system dynamics. To acquire good performance and produce a less conservative analysis result, a new parameter-dependent Lyapunov-Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.展开更多
The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability theor...The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability theory.Based on linear matrix inequalities（LMIs）,we originally propose robust fuzzy control to guarantee the global robust asymptotical stability of TSFNNs.Compared with the existing literature,this paper removes the assumptions on the neuron activations such as Lipschitz conditions,bounded,monotonic increasing property or the right-limit value is bigger than the left one at the discontinuous point.Thus,the results are more general and wider.Finally,two numerical examples are given to show the effectiveness of the proposed stability results.展开更多
基金Supported by National Natural Science Foundation of China （61034005, 60974071）, Program for New Century Excellent Talents in University （NCET-08-0101）, and Fundamental Research Funds for the Central Universities （N100104102, Nl10604007）
基金supported by the"Conseil Régional de Picardie"and the European Regional Development Fund within the framework of the project"SEDVAC"
文摘This article describes a method of vehicle dynamics estimation for impending rollover detection. We estimate vehicle dynamic states in presence of the road bank angle as a disturbance in the vehicle model using a robust observer. The estimated roll angle and roll rate are used to compute the rollover index which is based on the prediction of the lateral load transfer. In order to anticipate rollover detection, a new method is proposed to compute the time to rollover(TTR) using the load transfer ratio(LTR). The nonlinear model, deduced from the vehicle lateral and roll dynamics, is represented by a Takagi-Sugeno(T-S) fuzzy model. This representation is used to account for the nonlinearities of lateral cornering forces. The proposed T-S observer is designed with unmeasurable premise variables to cater for non-availability of the slip angles measurement. The proposed approach is evaluated using Car Sim simulator under different driving scenarios. Simulation results show good efficiency of the proposed T-S observer and the rollover detection method.
基金the National Natural Science Foundation of China (Grant No. 60504024)the Zhejiang Provincial Natural Science Foundation of China (Grant No. Y106010)the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP), China (Grant No. 20060335022)
文摘A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuzzy models. The SNNM is composed of a discrete-time linear dynamic system and a bounded static nonlinear operator. Based on the global asymptotic stability analysis of the SNNMs, linear and nonlinear dynamic output feedback controllers are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities （LMIs） which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based （or fuzzy） discrete-time intelligent systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Three application examples show that the SNNMs not only make controller synthesis of neural-network-based （or fuzzy） discrete-time intelligent systems much easier, but also provide a new approach to the synthesis of the controllers for the other type of nonlinear systems.
基金Supported by National Natural Science Foundation of China （50977008, 60904017, 60774048, 60728307）, the Funds for Creative Research Groups of China （60521003）, the Program for Cheung Kong Scholars and Innovative Research Team in University （IRT0421）, and the 111 Project （B08015）, National High Technology Research and Development Program of China （863 Program） （2006AA04Z183）
文摘This paper is concerned with the problem of stabilization of the Roesser type discrete-time nonlinear 2-D system that plays an important role in many practical applications. First, a discrete-time 2-D T-S fuzzy model is proposed to represent the underlying nonlinear 2-D system. Second, new quadratic stabilization conditions are proposed by applying relaxed quadratic stabilization technique for 2-D case. Third, for sake of further reducing conservatism, new non-quadratic stabilization conditions are also proposed by applying a new parameter-dependent Lyapunov function, matrix transformation technique, and relaxed technique for the underlying discrete-time 2-D T-S fuzzy system. Finally, a numerical example is provided to illustrate the effectiveness of the proposed results.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 50977008,60774048,and 60774093)the National High Technology Research and Development Program of China (Grant No. 2009AA04Z127)+1 种基金the Special Grant of Financial Support from China Postdoctoral Science Foundation (Grant No. 200902547)Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 200801451096)
文摘In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi Sugeno （T-S） fuzzy model is employed to represent the chaotic system dynamics. To acquire good performance and produce a less conservative analysis result, a new parameter-dependent Lyapunov-Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.
基金supported by the National Natural Science Foundation of China(6077504760835004)+2 种基金the National High Technology Research and Development Program of China(863 Program)(2007AA04Z244 2008AA04Z214)the Graduate Innovation Fundation of Hunan Province(CX2010B132)
文摘The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability theory.Based on linear matrix inequalities（LMIs）,we originally propose robust fuzzy control to guarantee the global robust asymptotical stability of TSFNNs.Compared with the existing literature,this paper removes the assumptions on the neuron activations such as Lipschitz conditions,bounded,monotonic increasing property or the right-limit value is bigger than the left one at the discontinuous point.Thus,the results are more general and wider.Finally,two numerical examples are given to show the effectiveness of the proposed stability results.
