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    Conceptual Evaluation of Brain Internal Models and Modeling their Uncertainty

    , M.Sc. Thesis Sharif University of Technology Sirjani, Nasim (Author) ; Jahed, Mehran (Supervisor)
    Abstract
    In the literature of motor behavior, rapid and harmonious human movements and adaptation to limb dynamics are described with reference to internal models. Concepts of internal models in neuroscience cognitive sciences and computational modeling have been investigated and their structure and performance have been evaluated by behavioral, neurophysiological and medical imaging data. The purpose of the theory of internal models is to explain the mechanism of human movement. Based on this theory, the central nervous system uses internal models to predict and adjust movements and reduce uncertainty. Uncertainty refers to the unknown dynamics of the system due to the lack of access to accurate... 

    Design of Control for Fractional Order Systems with Output Constraints

    , M.Sc. Thesis Sharif University of Technology Sadeghi, Hamed (Author) ; Sharokhi, Mohammad (Supervisor)
    Abstract
    Identifying fractional systems and designing controllers for these systems is one of the leading challenges due to their limitations. Systems can have constraints on output, input, and states. These constraints make it difficult to design a controller. In this project, controller design methods for fractional-order systems with output constraints are investigated. A controller is designed for a strict feedback nonlinear system with unknown dynamics subject to asymmetric and variable output constraints, unknown direction of the controller, and unmeasurable states. To design the controller, the direct and backstepping technique is used and the Lyapunov barrier function is applied for the first... 

    Control Design for Nonlinear Stochastic Processes in the Presence of Input Constraint

    , M.Sc. Thesis Sharif University of Technology Mozaffari Bezi, Ali (Author) ; Shahrokhi, Mohammad (Supervisor)
    Abstract
    Due to the presence of a random variable in the process dynamics or due to the presence of measurement noise, many processes have stochastic in nature. Behaviors of these processes are different from the deterministic processes and therefore their controllers are also different. The aim of this research is to design adaptive controller for stochastic processes with a non-strict feedback structure and in the presence of input constraints. Also, the considered system has other limitations such as the unmeasured states, actuator failure, unknown dynamics and fixed time stability is desired. The input limitation can be caused by the limitation of the final control element, because the input... 

    Control of continuous time chaotic systems with unknown dynamics and limitation on state measurement

    , Article Journal of Computational and Nonlinear Dynamics ; Volume 14, Issue 1 , 2019 ; 15551415 (ISSN) Kaveh, H ; Salarieh, H ; Sharif University of Technology
    American Society of Mechanical Engineers (ASME)  2019
    Abstract
    This paper has dedicated to study the control of chaos when the system dynamics is unknown and there are some limitations on measuring states. There are many chaotic systems with these features occurring in many biological, economical and mechanical systems. The usual chaos control methods do not have the ability to present a systematic control method for these kinds of systems. To fulfill these strict conditions, we have employed Takens embedding theorem which guarantees the preservation of topological characteristics of the chaotic attractor under an embedding named "Takens transformation." Takens transformation just needs time series of one of the measurable states. This transformation... 

    Control of continuous time chaotic systems with unknown dynamics and limitation on state measurement

    , Article Journal of Computational and Nonlinear Dynamics ; Volume 14, Issue 1 , 2019 ; 15551415 (ISSN) Kaveh, H ; Salarieh, H ; Sharif University of Technology
    American Society of Mechanical Engineers (ASME)  2019
    Abstract
    This paper has dedicated to study the control of chaos when the system dynamics is unknown and there are some limitations on measuring states. There are many chaotic systems with these features occurring in many biological, economical and mechanical systems. The usual chaos control methods do not have the ability to present a systematic control method for these kinds of systems. To fulfill these strict conditions, we have employed Takens embedding theorem which guarantees the preservation of topological characteristics of the chaotic attractor under an embedding named "Takens transformation." Takens transformation just needs time series of one of the measurable states. This transformation...