The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Yijing Wang - One of the best experts on this subject based on the ideXlab platform.
-
robust h control of discrete time markovian jump systems in the presence of Incomplete Knowledge of transition probabilities and saturating actuator
International Journal of Robust and Nonlinear Control, 2012Co-Authors: Yijing Wang, Michael Z Q ChenAbstract:SUMMARY This paper deals with the problem of robust H ∞ control for a class of discrete-time Markovian jump systems subject to both actuator saturation and Incomplete Knowledge of transition probability. Different from the previous results where the transition probability is completely known, a more general situation where only partial information on the exact values of elements in transition probability matrix is considered. By introducing some free parameters to express the relationship for the known and the unknown elements of transition probability matrix in stability analysis, a criterion is established to guarantee the stochastic stability of the closed-loop system as well as an H ∞ performance index. The concept of domain of attraction in mean square sense is used to analyze the closed-loop stability, and the mode-dependent H ∞ state-feedback controller is designed. It is shown that, even in the absence of actuator saturation, the obtained result is less conservative than the existing one. A numerical example is provided to illustrate the effectiveness of the proposed method. Copyright © 2011 John Wiley & Sons, Ltd.
-
controller synthesis for markovian jump systems with Incomplete Knowledge of transition probabilities and actuator saturation
Journal of The Franklin Institute-engineering and Applied Mathematics, 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:Abstract This paper is concerned with Markovian jump systems subject to Incomplete Knowledge of transition probabilities and actuator saturation. The system under consideration is more general, which covers the systems with completely known and completely unknown transition probabilities. By introducing some free-connection weighting matrices to handle the inaccessible elements of transition probabilities, a new criterion is established to guarantee the stochastic stability of the closed-loop system. An optimization problem with LMI constraints is then formulated to determine the largest contractively invariant set in mean square sense. Finally, two numerical examples are provided to illustrate the merits of our method.
-
Robust H ∞ control of discrete-time Markovian jump systems in the presence of Incomplete Knowledge of transition probabilities and saturating actuator
International Journal of Robust and Nonlinear Control, 2011Co-Authors: Yijing Wang, Michael Z Q ChenAbstract:SUMMARY This paper deals with the problem of robust H ∞ control for a class of discrete-time Markovian jump systems subject to both actuator saturation and Incomplete Knowledge of transition probability. Different from the previous results where the transition probability is completely known, a more general situation where only partial information on the exact values of elements in transition probability matrix is considered. By introducing some free parameters to express the relationship for the known and the unknown elements of transition probability matrix in stability analysis, a criterion is established to guarantee the stochastic stability of the closed-loop system as well as an H ∞ performance index. The concept of domain of attraction in mean square sense is used to analyze the closed-loop stability, and the mode-dependent H ∞ state-feedback controller is designed. It is shown that, even in the absence of actuator saturation, the obtained result is less conservative than the existing one. A numerical example is provided to illustrate the effectiveness of the proposed method. Copyright © 2011 John Wiley & Sons, Ltd.
-
Controller synthesis for Markovian jump systems subject to Incomplete Knowledge of transition probabilities and actuator saturation
Proceedings of the 30th Chinese Control Conference, 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:This paper is concerned with Markovian jump systems subject to Incomplete Knowledge of transition probabilities and actuator saturation. The system under consideration is more general, which covers the systems with completely known and completely unknown transition probabilities. By introducing some free-connection weighting matrices to handle the inaccessible elements of transition probabilities, a new criterion is established to guarantee the stochastic stability of the closed-loop system. An optimization problem with LMI constraints is then formulated to determine the largest contractively invariant set in mean square sense. Finally, two numerical examples are provided to illustrate the merits of our method.
-
Stochastic stability and stabilization of discrete-time Markovian jump systems in the presence of Incomplete Knowledge of transition probabilities
Proceedings of the 30th Chinese Control Conference, 2011Co-Authors: Yijing WangAbstract:This paper is concerned with the stability analysis and controller design for a class of discrete-time Markovian jump systems subject to Incomplete Knowledge of transition probabilities. Different from the previous results, some free-weighting matrices are introduced to obtain some new criteria with less conservatism. It is theoretically shown that the previous results are special cases if the free-weighting matrices are chosen to be some special forms. This brings much less conservatism compared with the previous ones. A numerical example is provided to show the effectiveness the proposed method.
Poogyeon Park - One of the best experts on this subject based on the ideXlab platform.
-
h control for singular markovian jump systems with Incomplete Knowledge of transition probabilities
Applied Mathematics and Computation, 2017Co-Authors: Nam Kyu Kwon, In Seok Park, Poogyeon ParkAbstract:This paper proposes a H state-feedback control for singular Markovian jump systems with Incomplete Knowledge of transition probabilities. Different from the previous results where the transition rates are completely known or the bounds of the unknown transition rates are given, a more general situation where the transition rates are partly unknown and the bounds of the unknown transition rates are also unknown is considered. Moreover, in contrast to the singular Markovian jump systems studied recently, the proposed method does not require any tuning parameters that arise when handling non-convex terms related to the mode-dependent Lyapunov matrices and the corresponding self-mode transition rates. Also, this paper uses all possible slack variables related to the transition rates into the relaxation process which contributes to reduce the conservatism. Finally, two numerical examples are provided to demonstrate the performance of H mode-dependent control.
-
improved h state feedback control for continuous time markovian jump fuzzy systems with Incomplete Knowledge of transition probabilities
Journal of The Franklin Institute-engineering and Applied Mathematics, 2016Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon Park, In Seok ParkAbstract:Abstract This paper proposes the improved H ∞ state-feedback control for Markovian jump fuzzy systems (MJFSs) with Incomplete Knowledge of transition probabilities. From the fundamental first-order properties of the transition rates, two second-order properties are introduced without information on the lower and upper bounds of the transition rates, differently from other approaches in the literature. Based on these properties, this paper uses all possible slack variables into the relaxation process which contributes to reduce the conservatism. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.
-
Improved H∞ state-feedback control for continuous-time Markovian jump fuzzy systems with Incomplete Knowledge of transition probabilities☆
Journal of The Franklin Institute-engineering and Applied Mathematics, 2016Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon Park, In Seok ParkAbstract:Abstract This paper proposes the improved H ∞ state-feedback control for Markovian jump fuzzy systems (MJFSs) with Incomplete Knowledge of transition probabilities. From the fundamental first-order properties of the transition rates, two second-order properties are introduced without information on the lower and upper bounds of the transition rates, differently from other approaches in the literature. Based on these properties, this paper uses all possible slack variables into the relaxation process which contributes to reduce the conservatism. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.
-
less conservative stabilization conditions for markovian jump systems with Incomplete Knowledge of transition probabilities and input saturation
Optimal Control Applications & Methods, 2016Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon ParkAbstract:Summary This paper proposes less conservative stabilization conditions for Markovian jump systems with Incomplete Knowledge of transition probabilities and input saturation. The transition rates associated with the transition probabilities are expressed in terms of three properties, which do not require the lower and upper bounds of the transition rates, differently from other approaches in the literature. The resulting conditions are converted into the second-order matrix polynomial of the unknown transition rates. The polynomial can be represented as quadratic form of vectorized identity matrices scaled by one and the unknown transition rates. And then, the LMI conditions are obtained from the quadratic form. Also, an optimization problem is formulated to find the largest estimate of the domain of attraction in mean square sense of the closed-loop systems. Finally, two numerical examples are provided to illustrate the effectiveness of the derived stabilization conditions. Copyright © 2016 John Wiley & Sons, Ltd.
-
Improved ℋ ∞ state-feedback control for discrete-time Markovian jump systems with Incomplete Knowledge of transition probabilities(ICCAS 2015)
2015 15th International Conference on Control Automation and Systems (ICCAS), 2015Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon ParkAbstract:This paper considers improved ℋ ∞ state-feedback control for discrete-time Markovian jump systems with Incomplete Knowledge of transition probabilities. To achieve the better ℋ ∞ performance, this paper proposes two valuable approaches. First, under the assumption that the lower and upper bounds of unknown transition probabilities are known, the closed-loop stabilization conditions are represented as convex combination with these bounds. Second, a new lower bound lemma for the inversion of the matrix summation is investigated. This lemma enables the inversion of the matrix summation to be replaced by free variable which does not contain the transition probabilities. Thus, the ℋ ∞ stabilization conditions consist of two parts which are transition probability independent part and dependent part. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.
Chunhui Wang - One of the best experts on this subject based on the ideXlab platform.
-
controller synthesis for markovian jump systems with Incomplete Knowledge of transition probabilities and actuator saturation
Journal of The Franklin Institute-engineering and Applied Mathematics, 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:Abstract This paper is concerned with Markovian jump systems subject to Incomplete Knowledge of transition probabilities and actuator saturation. The system under consideration is more general, which covers the systems with completely known and completely unknown transition probabilities. By introducing some free-connection weighting matrices to handle the inaccessible elements of transition probabilities, a new criterion is established to guarantee the stochastic stability of the closed-loop system. An optimization problem with LMI constraints is then formulated to determine the largest contractively invariant set in mean square sense. Finally, two numerical examples are provided to illustrate the merits of our method.
-
Controller synthesis for Markovian jump systems subject to Incomplete Knowledge of transition probabilities and actuator saturation
Proceedings of the 30th Chinese Control Conference, 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:This paper is concerned with Markovian jump systems subject to Incomplete Knowledge of transition probabilities and actuator saturation. The system under consideration is more general, which covers the systems with completely known and completely unknown transition probabilities. By introducing some free-connection weighting matrices to handle the inaccessible elements of transition probabilities, a new criterion is established to guarantee the stochastic stability of the closed-loop system. An optimization problem with LMI constraints is then formulated to determine the largest contractively invariant set in mean square sense. Finally, two numerical examples are provided to illustrate the merits of our method.
-
Robust H∞ Control of Markovian Jump Systems subject to Saturating Actuator and Incomplete Knowledge of Transition Probability
2011 Chinese Control and Decision Conference (CCDC), 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:This paper deals with the problem of robust H∞ control for a class of discrete-time Markovian jump systems subject to both actuator saturation and Incomplete Knowledge of transition probability. Different from the previous results where the complete Knowledge of transition probability is available, a more general case is considered and the concept of domain of attraction in mean square sense is used to analyze the closed-loop stability. A sufficient condition is established to guarantee the stochastic stability of the closed-loop system. The mode-dependent H∞ state-feedback controller are designed using the LMI approach. Finally, a numerical example is provided to show the effectiveness of our method.
-
Robust H ∞ Control of Markovian Jump Systems subject to Saturating Actuator and Incomplete Knowledge of Transition Probability
2011 Chinese Control and Decision Conference (CCDC), 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:This paper deals with the problem of robust H ∞ control for a class of discrete-time Markovian jump systems subject to both actuator saturation and Incomplete Knowledge of transition probability. Different from the previous results where the complete Knowledge of transition probability is available, a more general case is considered and the concept of domain of attraction in mean square sense is used to analyze the closed-loop stability. A sufficient condition is established to guarantee the stochastic stability of the closed-loop system. The mode-dependent H ∞ state-feedback controller are designed using the LMI approach. Finally, a numerical example is provided to show the effectiveness of our method.
Melissa A Bowles - One of the best experts on this subject based on the ideXlab platform.
-
back to basics Incomplete Knowledge of differential object marking in spanish heritage speakers
Bilingualism: Language and Cognition, 2009Co-Authors: Silvina Montrul, Melissa A BowlesAbstract:The obligatory use of the preposition a with animate, specific direct objects in Spanish (Juan conoce a Maria “Juan knows Maria”) is a well-known instance of Differential Object Marking (DOM; Torrego, 1998; Leonetti, 2004). Recent studies have documented the loss and/or Incomplete acquisition of several grammatical features in Spanish heritage speakers (Silva-Corvalan, 1994; Montrul, 2002), including DOM (Montrul, 2004a). This study assesses the extent of Incomplete Knowledge of DOM in Spanish heritage speakers raised in the United States by comparing it with Knowledge of DOM in fully competent native speakers. Experiment 1 examined whether omission of a affected grammatical competence, as measured by the linguistic behavior of 67 heritage speakers and 22 monolingual speakers in an oral production task and in a written acceptability judgment task. Experiment 2 followed up on the results of the acceptability judgment task with 13 monolingual speakers and 69 heritage speakers, and examined whether problems with DOM generalize to other instances of structural and inherent dative case, including ditransitive verbs and gustar-type psychological verbs. Results of the two experiments confirmed that heritage speakers' recognition and production of DOM is probabilistic, even for speakers with advanced proficiency in Spanish. This suggests that many heritage speakers' grammars may not actually instantiate inherent case. We argue that language loss under reduced input conditions in childhood is, in this case, like “going back to basics”: it leads to simplification of the grammar by letting go of the non-core options, while retaining the core functional structure.
-
Back to basics: Incomplete Knowledge of Differential Object Marking in Spanish heritage speakers *
Bilingualism: Language and Cognition, 2009Co-Authors: Silvina Montrul, Melissa A BowlesAbstract:The obligatory use of the preposition a with animate, specific direct objects in Spanish (Juan conoce a Maria “Juan knows Maria”) is a well-known instance of Differential Object Marking (DOM; Torrego, 1998; Leonetti, 2004). Recent studies have documented the loss and/or Incomplete acquisition of several grammatical features in Spanish heritage speakers (Silva-Corvalan, 1994; Montrul, 2002), including DOM (Montrul, 2004a). This study assesses the extent of Incomplete Knowledge of DOM in Spanish heritage speakers raised in the United States by comparing it with Knowledge of DOM in fully competent native speakers. Experiment 1 examined whether omission of a affected grammatical competence, as measured by the linguistic behavior of 67 heritage speakers and 22 monolingual speakers in an oral production task and in a written acceptability judgment task. Experiment 2 followed up on the results of the acceptability judgment task with 13 monolingual speakers and 69 heritage speakers, and examined whether problems with DOM generalize to other instances of structural and inherent dative case, including ditransitive verbs and gustar-type psychological verbs. Results of the two experiments confirmed that heritage speakers' recognition and production of DOM is probabilistic, even for speakers with advanced proficiency in Spanish. This suggests that many heritage speakers' grammars may not actually instantiate inherent case. We argue that language loss under reduced input conditions in childhood is, in this case, like “going back to basics”: it leads to simplification of the grammar by letting go of the non-core options, while retaining the core functional structure.
Bum Yong Park - One of the best experts on this subject based on the ideXlab platform.
-
H ∞ Control of Markovian Jump Systems with Incomplete Knowledge of Transition Probabilities
International Journal of Control Automation and Systems, 2019Co-Authors: Jaewook Shin, Bum Yong ParkAbstract:An H∞ state-feedback controller for Markovian jump systems with Incomplete Knowledge of transition probabilities and input quantization is proposed. To derive the less conservative stabilization conditions, the conditions are developed into the second-order matrix polynomials of the unknown transition rate using an appropriate weighting method. Furthermore, the proposed controller not only accomplishes an H∞ performance but also removes the matched disturbances and the effect of input quantization. Two examples show the effectiveness of the proposed method.
-
improved h state feedback control for continuous time markovian jump fuzzy systems with Incomplete Knowledge of transition probabilities
Journal of The Franklin Institute-engineering and Applied Mathematics, 2016Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon Park, In Seok ParkAbstract:Abstract This paper proposes the improved H ∞ state-feedback control for Markovian jump fuzzy systems (MJFSs) with Incomplete Knowledge of transition probabilities. From the fundamental first-order properties of the transition rates, two second-order properties are introduced without information on the lower and upper bounds of the transition rates, differently from other approaches in the literature. Based on these properties, this paper uses all possible slack variables into the relaxation process which contributes to reduce the conservatism. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.
-
Improved H∞ state-feedback control for continuous-time Markovian jump fuzzy systems with Incomplete Knowledge of transition probabilities☆
Journal of The Franklin Institute-engineering and Applied Mathematics, 2016Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon Park, In Seok ParkAbstract:Abstract This paper proposes the improved H ∞ state-feedback control for Markovian jump fuzzy systems (MJFSs) with Incomplete Knowledge of transition probabilities. From the fundamental first-order properties of the transition rates, two second-order properties are introduced without information on the lower and upper bounds of the transition rates, differently from other approaches in the literature. Based on these properties, this paper uses all possible slack variables into the relaxation process which contributes to reduce the conservatism. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.
-
less conservative stabilization conditions for markovian jump systems with Incomplete Knowledge of transition probabilities and input saturation
Optimal Control Applications & Methods, 2016Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon ParkAbstract:Summary This paper proposes less conservative stabilization conditions for Markovian jump systems with Incomplete Knowledge of transition probabilities and input saturation. The transition rates associated with the transition probabilities are expressed in terms of three properties, which do not require the lower and upper bounds of the transition rates, differently from other approaches in the literature. The resulting conditions are converted into the second-order matrix polynomial of the unknown transition rates. The polynomial can be represented as quadratic form of vectorized identity matrices scaled by one and the unknown transition rates. And then, the LMI conditions are obtained from the quadratic form. Also, an optimization problem is formulated to find the largest estimate of the domain of attraction in mean square sense of the closed-loop systems. Finally, two numerical examples are provided to illustrate the effectiveness of the derived stabilization conditions. Copyright © 2016 John Wiley & Sons, Ltd.
-
Improved ℋ ∞ state-feedback control for discrete-time Markovian jump systems with Incomplete Knowledge of transition probabilities(ICCAS 2015)
2015 15th International Conference on Control Automation and Systems (ICCAS), 2015Co-Authors: Nam Kyu Kwon, Bum Yong Park, Poogyeon ParkAbstract:This paper considers improved ℋ ∞ state-feedback control for discrete-time Markovian jump systems with Incomplete Knowledge of transition probabilities. To achieve the better ℋ ∞ performance, this paper proposes two valuable approaches. First, under the assumption that the lower and upper bounds of unknown transition probabilities are known, the closed-loop stabilization conditions are represented as convex combination with these bounds. Second, a new lower bound lemma for the inversion of the matrix summation is investigated. This lemma enables the inversion of the matrix summation to be replaced by free variable which does not contain the transition probabilities. Thus, the ℋ ∞ stabilization conditions consist of two parts which are transition probability independent part and dependent part. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.
