The Experts below are selected from a list of 30198 Experts worldwide ranked by ideXlab platform

Alexander Zemliak - One of the best experts on this subject based on the ideXlab platform.

  • EWDTS - Control Vector structure for circuit optimization
    Proceedings of IEEE East-West Design & Test Symposium (EWDTS 2014), 2014
    Co-Authors: Alexander Zemliak, Fernando Reyes, T. Markina
    Abstract:

    The methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time algorithm. The Lyapunov function of the optimization process was proposed to define optimal structure of Control Vector.

  • Stability of analogue circuit optimization process and Control Vector structure
    Radioelectronics and Communications Systems, 2013
    Co-Authors: Alexander Zemliak, T. Markina
    Abstract:

    Analogue circuit optimization process may be Controlled using a generalized design methodology. Lyapunov function is an integral function that carries information on this process. The use of Lyapunov function concept for a dynamic system allowed for comparison of various design strategies with respect to their stability and convergence. Study of Lyapunov function’s and its derivative’s behavior allowed for revealing significant correlation between this function’s properties and processor time for circuit design. Analysis of processor time dependence on Control Vector switching points provided a possibility to find this Vector’s optimal structure. Numerical results prove bright future of such approach for finding quasi-optimal algorithm of analogue circuits design.

  • On optimal structure of Control Vector for analog circuit optimization
    2013
    Co-Authors: Alexander Zemliak
    Abstract:

    The circuit optimization process is formulated as a dynamic Controllable system. A special Control Vector is defined to redistribute the compute expense between a network analysis and a parametric optimization. This redistribution permits the minimization a computer time. The problem of a minimal-time circuit optimization can be formulated in this case as a classical problem of the optimal Control for some functional minimization. The conception of the Lyapunov function of dynamic Controllable system is used to analyze the principal characteristics of the process of designing. The analysis of the Lyapunov function and its time derivative gives us a possibility to predict the optimal structure of the Control Vector and to construct the quasi optimal algorithm of circuit designing.

  • Control Vector optimal structure for minimal-time networks optimization
    2010
    Co-Authors: Alexander Zemliak, Miguel Torres, Antonio Michua
    Abstract:

    The methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm. The special function that is a combination of Lyapunov function of the design process and its time derivative was proposed to predict the optimal Control Vector to construct an optimal system design algorithm.

  • Analysis of the Control Vector structure in analog networks design
    Radioelectronics and Communications Systems, 2009
    Co-Authors: Alexander Zemliak
    Abstract:

    The methodology of analog networks design developed on the basis of the optimum Control theory is used for determining the Vector structure Controlling the optimization process. The analysis of Control Vector structure is performed by using the Lyapunov function concept of design process. The investigation of behavior of this function and its time derivative makes it possible to determine optimal switching points of the Control Vector. Such an approach allows us to minimize the total processor time of network design by correcting the Control Vector structure in terms of the characteristics of the initial period of design. Numerical results of the optimization process of networks with arbitrary number of transistors indicate the possibility of design process Control for minimization of the total processor time.

A.m. Zemliak - One of the best experts on this subject based on the ideXlab platform.

  • Analysis of the structure of different optimization strategies
    Compel-the International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 2020
    Co-Authors: A.m. Zemliak, Jorge Espinosa-garcia
    Abstract:

    Purpose In this paper, on the basis of a previously developed approach to circuit optimization, the main element of which is the Control Vector that changes the form of the basic equations, the structure of the Control Vector is determined, which minimizes CPU time. Design/methodology/approach The circuit optimization process is defined as a Controlled dynamic system with a special Control Vector. This Vector serves as the main tool for generalizing the problem of circuit optimization and produces a huge number of different optimization strategies. The task of finding the best optimization strategy that minimizes processor time can be formulated. There is a need to find the optimal structure of the Control Vector that minimizes processor time. A special function, which is a combination of the Lyapunov function of the optimization process and its time derivative, was proposed to predict the optimal structure of the Control Vector. The found optimal positions of the switching points of the Control Vector give a large gain in CPU time in comparison with the traditional approach. Findings The optimal positions of the switching points of the components of the Control Vector were calculated. They minimize processor time. Numerical results are obtained for various circuits. Originality/value The Lyapunov function, which is one of the main characteristics of any dynamic system, is used to determine the optimal structure of the Control Vector, which minimizes the time of the circuit optimization process.

  • EWDTS - Control Vector structure for a minimal-time circuit optimization process
    2015 IEEE East-West Design & Test Symposium (EWDTS), 2015
    Co-Authors: A.m. Zemliak, Fernando Reyes, T. Markina
    Abstract:

    The circuit optimization process is formulated as a dynamic Controllable system. A special Control Vector is defined to redistribute the compute expense between a network analysis and a parametric optimization. The problem of a minimal-time circuit optimization was formulated as a classical problem of the optimal Control for minimization of one functional. The conception of the Lyapunov function of dynamic system is used to analyze the principal characteristics of the design process. The analysis of the Lyapunov function and its time derivative gives us a possibility to predict the optimal Control Vector structure for constructing a minimal-time circuit design algorithm.

  • Study of structure of the Control Vector for the best optimization strategy
    The Experience of Designing and Application of CAD Systems in Microelectronics, 2015
    Co-Authors: A.m. Zemliak
    Abstract:

    The generalized methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm.

  • Analysis of the switch points of Control Vector for the process of circuit optimization
    2011
    Co-Authors: A.m. Zemliak, Miguel Torres
    Abstract:

    The circuit optimization process is formulated as a dynamic Controllable system. A special Control Vector is defined to redistribute the compute expense between a network analysis and a parametric optimization. This redistribution permits the minimization a computer time. The problem of a minimal-time circuit optimization can be formulated in this case as a classical problem of the optimal Control for some functional minimization. The conception of the Lyapunov function of dynamic Controllable system is used to analyze the principal characteristics of the design process. The analysis of the Lyapunov function and its time derivative gives us a possibility to predict the optimal Control Vector structure for constructing a minimal-time circuit design algorithm.

  • On structure of the Control Vector for minimal-time networks design strategy
    WSEAS Transactions on Circuits and Systems archive, 2009
    Co-Authors: A.m. Zemliak, Miguel Torres
    Abstract:

    The generalized methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm. The special function that is a combination of Lyapunov function of the design process and its time derivative was proposed to predict the optimal Control Vector to construct an optimal system design algorithm.

Miguel Torres - One of the best experts on this subject based on the ideXlab platform.

  • Analysis of the switch points of Control Vector for the process of circuit optimization
    2011
    Co-Authors: A.m. Zemliak, Miguel Torres
    Abstract:

    The circuit optimization process is formulated as a dynamic Controllable system. A special Control Vector is defined to redistribute the compute expense between a network analysis and a parametric optimization. This redistribution permits the minimization a computer time. The problem of a minimal-time circuit optimization can be formulated in this case as a classical problem of the optimal Control for some functional minimization. The conception of the Lyapunov function of dynamic Controllable system is used to analyze the principal characteristics of the design process. The analysis of the Lyapunov function and its time derivative gives us a possibility to predict the optimal Control Vector structure for constructing a minimal-time circuit design algorithm.

  • Control Vector optimal structure for minimal-time networks optimization
    2010
    Co-Authors: Alexander Zemliak, Miguel Torres, Antonio Michua
    Abstract:

    The methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm. The special function that is a combination of Lyapunov function of the design process and its time derivative was proposed to predict the optimal Control Vector to construct an optimal system design algorithm.

  • On structure of the Control Vector for minimal-time networks design strategy
    WSEAS Transactions on Circuits and Systems archive, 2009
    Co-Authors: A.m. Zemliak, Miguel Torres
    Abstract:

    The generalized methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm. The special function that is a combination of Lyapunov function of the design process and its time derivative was proposed to predict the optimal Control Vector to construct an optimal system design algorithm.

  • On optimal structure of the Control Vector for the minimal-time circuit design process
    2009
    Co-Authors: A.m. Zemliak, Miguel Torres
    Abstract:

    The generalized methodology for the electronic networks optimization system was elaborated by means of the optimal Control theory approach. The problem of the electronic system design is formulated in this case as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm. The special function that is a combination of Lyapunov function and its time derivative was proposed to predict the optimal Control Vector structure to construct a minimal-time system design algorithm.

  • Analysis of the optimal position of the Control Vector's switching points for the minimal-time circuit design strategy prediction
    2008
    Co-Authors: A.m. Zemliak, Miguel Torres
    Abstract:

    The generalized methodology for the electronic networks optimization system was elaborated by means of the optimal Control theory approach. The problem of the electronic system design is formulated in this case as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time system design algorithm. The special function that is a combination of Lyapunov function and its time derivative was proposed to predict the optimal Control Vector structure to construct a minimal-time system design algorithm.

T. Markina - One of the best experts on this subject based on the ideXlab platform.

  • EWDTS - Control Vector structure for a minimal-time circuit optimization process
    2015 IEEE East-West Design & Test Symposium (EWDTS), 2015
    Co-Authors: A.m. Zemliak, Fernando Reyes, T. Markina
    Abstract:

    The circuit optimization process is formulated as a dynamic Controllable system. A special Control Vector is defined to redistribute the compute expense between a network analysis and a parametric optimization. The problem of a minimal-time circuit optimization was formulated as a classical problem of the optimal Control for minimization of one functional. The conception of the Lyapunov function of dynamic system is used to analyze the principal characteristics of the design process. The analysis of the Lyapunov function and its time derivative gives us a possibility to predict the optimal Control Vector structure for constructing a minimal-time circuit design algorithm.

  • EWDTS - Control Vector structure for circuit optimization
    Proceedings of IEEE East-West Design & Test Symposium (EWDTS 2014), 2014
    Co-Authors: Alexander Zemliak, Fernando Reyes, T. Markina
    Abstract:

    The methodology for the electronic networks optimization was elaborated by means of the optimal Control theory approach. In this case the problem of the electronic system design is formulated as a classical problem of functional minimization of the optimal Control theory. The minimal time system design algorithm was defined as a Controllable dynamic process with an optimal Control Vector. By this methodology the aim of the system design process with minimal computer time is presented as a transition process of some dynamic system that has the minimal transition time. The optimal position of the Control Vector switch points was determined as a principal characteristic of the minimal-time algorithm. The Lyapunov function of the optimization process was proposed to define optimal structure of Control Vector.

  • Stability of analogue circuit optimization process and Control Vector structure
    Radioelectronics and Communications Systems, 2013
    Co-Authors: Alexander Zemliak, T. Markina
    Abstract:

    Analogue circuit optimization process may be Controlled using a generalized design methodology. Lyapunov function is an integral function that carries information on this process. The use of Lyapunov function concept for a dynamic system allowed for comparison of various design strategies with respect to their stability and convergence. Study of Lyapunov function’s and its derivative’s behavior allowed for revealing significant correlation between this function’s properties and processor time for circuit design. Analysis of processor time dependence on Control Vector switching points provided a possibility to find this Vector’s optimal structure. Numerical results prove bright future of such approach for finding quasi-optimal algorithm of analogue circuits design.

Wassim M. Haddad - One of the best experts on this subject based on the ideXlab platform.

  • Control Vector Lyapunov Functions for Large-Scale Impulsive Systems
    Stability and Control of Large-Scale Dynamical Systems, 2011
    Co-Authors: Wassim M. Haddad, Sergey G. Nersesov
    Abstract:

    This chapter extends the notion of Control Vector Lyapunov functions to impulsive dynamical systems. Vector Lyapunov theory has been developed to weaken the hypothesis of standard Lyapunov theory to enlarge the class of Lyapunov functions that can be used for analyzing system stability. In particular, the use of Vector Lyapunov functions in dynamical system theory offers a very flexible framework since each component of the Vector Lyapunov function can satisfy less rigid requirements as compared to a single scalar Lyapunov function. Using Control Vector Lyapunov functions, the chapter develops a universal hybrid decentralized feedback stabilizer for a decentralized affine in the Control nonlinear impulsive dynamical system that possesses guaranteed gain and sector margins in each decentralized input channel. These results are used to develop hybrid decentralized Controllers for large-scale impulsive dynamical systems with robustness guarantees against full modeling and input uncertainty.

  • Finite-Time Stabilization of Large-Scale Systems via Control Vector Lyapunov Functions
    Stability and Control of Large-Scale Dynamical Systems, 2011
    Co-Authors: Wassim M. Haddad, Sergey G. Nersesov
    Abstract:

    This chapter develops a general framework for finite-time stability analysis based on Control Vector Lyapunov functions. Specifically, it develops a Vector comparison system whose solution is finite-time stable and relates this finite-time stability property to the stability properties of a nonlinear dynamical system using a Vector comparison principle. The results are specialized to the case of a scalar Lyapunov function to obtain universal finite-time stabilizers for nonlinear systems that are affine in the Control. Finally, the utility of the proposed framework is demonstrated using two numerical examples: the first involves a large-scale dynamical system with Control signals for each decentralized Control channel as a function of time; the second example considers Control of thermoacoustic instabilities in combustion processes.

  • Control Vector Lyapunov functions for large-scale impulsive dynamical systems
    Nonlinear Analysis: Hybrid Systems, 2007
    Co-Authors: Sergey G. Nersesov, Wassim M. Haddad
    Abstract:

    Vector Lyapunov theory has been developed to weaken the hypothesis of standard Lyapunov theory in order to enlarge the class of Lyapunov functions that can be used for analyzing system stability. In this paper, we provide generalizations to the recent extensions of Vector Lyapunov theory for continuous-time systems to address stability and Control design of impulsive dynamical systems via Vector Lyapunov functions. Specifically, we provide a generalized comparison principle involving hybrid comparison dynamics that are dependent on the comparison system states as well as the nonlinear impulsive dynamical system states. Furthermore, we develop stability results for impulsive dynamical systems that involve Vector Lyapunov functions and hybrid comparison inequalities. Based on these results, we show that partial stability for state-dependent impulsive dynamical systems can be addressed via Vector Lyapunov functions. Furthermore, we extend the recently developed notion of Control Vector Lyapunov functions to impulsive dynamical systems. Using Control Vector Lyapunov functions, we construct a universal hybrid decentralized feedback stabilizer for a decentralized affine in the Control nonlinear impulsive dynamical system that possesses guaranteed gain and sector margins in each decentralized input channel. These results are then used to develop hybrid decentralized Controllers for large-scale impulsive dynamical systems with robustness guarantees against full modeling and input uncertainty.

  • Control Vector Lyapunov Functions for Large-Scale Impulsive Dynamical Systems
    Proceedings of the 45th IEEE Conference on Decision and Control, 2006
    Co-Authors: Sergey G. Nersesov, Wassim M. Haddad
    Abstract:

    Vector Lyapunov theory has been developed to weaken the hypothesis of standard Lyapunov theory in order to enlarge the class of Lyapunov functions that can be used for analyzing system stability. In this paper, we provide generalizations to the recent extensions of Vector Lyapunov theory for continuous-time systems to address stability and Control design of impulsive dynamical systems via Vector Lyapunov functions. Specifically, we provide a generalized comparison principle involving hybrid comparison dynamics that are dependent on comparison system states as well as the nonlinear impulsive dynamical system states. Furthermore, we develop stability results for impulsive dynamical systems that involve Vector Lyapunov functions and hybrid comparison inequalities. Based on these results, we show that partial stability for state-dependent impulsive dynamical systems can be addressed via Vector Lyapunov functions. Furthermore, we extend the novel notion of Control Vector Lyapunov functions to impulsive dynamical systems. Using Control Vector Lyapunov functions, we present a universal decentralized feedback stabilizer for a decentralized affine in the Control nonlinear impulsive dynamical system. These results are then used to develop decentralized Controllers for large-scale impulsive dynamical systems with robustness guarantees against full modeling uncertainty.