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    Computational load reduction in model predictive control of nonlinear systems via decomposition

    , Article 5th International Conference on Control, Instrumentation, and Automation, ICCIA 2017, 21 November 2017 through 23 November 2017 ; Volume 2018-January , 2018 , Pages 216-221 ; 9781538621349 (ISBN) Adelipour, S ; Rastgar, M ; Haeri, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    The aim of this study is to reduce the computational load in model predictive control of multi-input nonlinear systems. First, the nonlinear system which has a high number of states and inputs is decomposed into several subsystems by solving a linear integer programming problem offline. Then, the model of each subsystem is revised by considering the effect of coupling and interactions of other subsystems. Next, the robust model predictive technique based on linear matrix inequalities is employed to compute control signal for each subsystem. An industrial chemical reaction example is used to illustrate the effectiveness of the proposed method. © 2017 IEEE  

    Control of a Bioreactor Using Artificial Intelligent Methods

    , M.Sc. Thesis Sharif University of Technology Shamsi, Zahra (Author) ; Shahrokhi, Mohammad (Supervisor)
    Abstract
    The goal of this project is finding an appropriate method for controlling four different bioreactors with unknown dynamics. At first, an introduction to bioreactor dynamic hase been presented, then their nonlinear behavior has been discussed. In the following, four output control systems using adaptive neural network have been designed separately for four different dynamics. The applied control method has been adapted from a method of references with some changes. Performances of designed controllers in set point tracking, load rejection and model mismatch have been evaluated using simulation. In these studies, input saturation has been considered in simulations but it is not existed in... 

    Control of Nonlinear Systems With Predefined Output Transient Performance

    , M.Sc. Thesis Sharif University of Technology Kamal Amiri, Ali (Author) ; Shahrokhi, Mohammad (Supervisor)
    Abstract
    This project is aimed to design a controller for nonlinear systems that satisfy a prescribed performance while guaranteeing close-loop stability. To do this, the controller must be designed in such a way that the transient response of the system has had these performance indices and does not exceed them. These performance indices predefine some constraints for systems’ output.A comprehensive form for the model system, the unknown dynamics of the system, consideration of a variety of constraints on the system input, usage of the time-finite method for the residence time and consideration of just one tuning parameter to reduce the computation load, are among the other benefits for the proposed... 

    Adaptive fixed-time consensus control for a class of non-strict feedback multi-agent systems subject to input nonlinearities, state constraints, unknown control directions, and actuator faults

    , Article European Journal of Control ; Volume 66 , 2022 ; 09473580 (ISSN) Mohit, M ; Shahrokhi, M ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    In this work, an adaptive fixed-time controller has been designed for a class of uncertain non-strict feedback multi-agent systems (MASs) subject to different types of input nonlinearities, time-varying asymmetric state constraints, unknown control directions, infinite number of actuator faults and external disturbances. Compared to the existing consensus control schemes, the proposed controller can handle input nonlinearities, actuator faults and unknown control directions simultaneously, while guaranteeing fixed-time convergence of the consensus tracking error and satisfying state constraints for non-strict feedback MASs. By employing a nonlinear mapping, the constrained MAS has been... 

    Observer-based controller for nonaffine time-delayed systems subject to input nonlinearities, state constraints, and unknown control direction

    , Article International Journal of Adaptive Control and Signal Processing ; Volume 36, Issue 8 , 2022 , Pages 2122-2149 ; 08906327 (ISSN) Mohit, M ; Shahrokhi, M ; Kamalamiri, A ; Sharif University of Technology
    John Wiley and Sons Ltd  2022
    Abstract
    In this work, an adaptive observer-based control scheme has been designed for uncertain nonaffine nonstrict feedback systems subject to state time delay, various types of input nonlinearities, time-varying asymmetric state constraints, and unknown control direction. Compared to the existing controllers for systems with state constraints, the designed control scheme in this work can be applied to state-constrained systems with nonaffine structure subject to state delays, unknown control direction, and different types of input nonlinearities, while full-states measurement is not required. Moreover, by introducing a novel saturated Nussbaum function in the present work, not only has the problem... 

    Fault-tolerant adaptive fractional controller design for incommensurate fractional-order nonlinear dynamic systems subject to input and output restrictions

    , Article Chaos, Solitons and Fractals ; Volume 157 , 2022 ; 09600779 (ISSN) Pishro, A ; Shahrokhi, M ; Sadeghi, H ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    In this article, a fault-tolerant adaptive neural network fractional controller has been proposed for a class of uncertain multi-input single-output (MISO) incommensurate fractional-order non-strict nonlinear systems subject to five different types of unknown input nonlinearities, infinite number of actuators failures and arbitrary independent time-varying output constraints. The barrier Lyapunov function (BLF)-based backstepping technique and fractional Lyapunov direct method (FLDM) have been used to design the controller and establish system stability. To tackle the incommensurate derivatives problem, in each step of the backstepping technique, an appropriate Lyapunov function has been... 

    Controller ِِDesign for Switched Systems

    , M.Sc. Thesis Sharif University of Technology Malek, Alireza (Author) ; Shahrokhi, Mohammad (Supervisor) ; Vafa, Ehsan (Supervisor)
    Abstract
    The aim of this thesis is investigating the approaches proposed for controlling switched systems and designing a controller for MIMO switched systems. The system under consideration is in strict feedback form with unknown dynamics, unmodeled dynamics, state-dependent delays and disturbances and input nonlinearity (saturation, backlash, dead-zone). In this work, the unknown dynamics are estimated by an intelligent approximator. The arbitrary switching law is assumed and for control purpose the switching instances are not required. The backstepping technique has been utilize for controller design and by using a nonnegative switching function and a common lyapunov function, the closed loop... 

    Control of Fractional Order Systems with Input Constraints

    , M.Sc. Thesis Sharif University of Technology Pishro, Abouzar (Author) ; Shahrokhi, Mohammad (Supervisor)
    Abstract
    Considering input constraints is an essential task in the controller design. In this thesis, a controller has been designed for incommensurate fractional order nonlinear systems in the nonstrict feedback form subject to unknown dynamics, input nonlinearity and actuator failures. The Lyapunov direct method and the backstepping technique have been used to design the controller and stability analysis. The number of actuator faults can be infinite. In addition, the proposed control algorithm can cope with different types of input nonlinearities namely, saturation, dead zone, dead zone-saturation, backlash and hysteresis. To estimate the system uncertainties, neural networks have been employed... 

    Adaptive prescribed performance control of switched MIMO uncertain nonlinear systems subject to unmodeled dynamics and input nonlinearities

    , Article International Journal of Robust and Nonlinear Control ; Volume 28, Issue 18 , 2018 , Pages 5981-5996 ; 10498923 (ISSN) Malek, S. A ; Shahrokhi, M ; Vafa, E ; Moradvandi, A ; Sharif University of Technology
    Abstract
    In this paper, the design of an adaptive tracking control for a class of switched uncertain multiple-input–multiple-output nonlinear systems in the strict-feedback form with unmodeled dynamics in the presence of three types of input nonlinearity under arbitrary switching has been addressed. By means of an intelligent approximator like a fuzzy logic system or a neural network, the unknown dynamics are estimated. The unmodeled dynamics have been tackled with a dynamic signal. A universal framework for describing different types of input nonlinearity including saturation, backlash, and dead zone has been utilized. By applying the backstepping approach and the common Lyapunov function method,... 

    Adaptive synchronization of two different uncertain chaotic systems with unknown dead-zone input nonlinearities

    , Article JVC/Journal of Vibration and Control ; Volume 26, Issue 21-22 , 2020 , Pages 1956-1968 Heidarzadeh, S ; Shahmoradi, S ; Shahrokhi, M ; Sharif University of Technology
    SAGE Publications Inc  2020
    Abstract
    The present work addresses chaos synchronization between two different general chaotic systems with parametric and structural uncertainties, subject to external disturbances and input dead-zone nonlinearities. In this regard, a novel robust controller has been designed that guarantees asymptotic stability of synchronization errors and boundedness of all closed-loop signals. One advantage of the proposed controller over the existing control algorithms is using only one update law for estimating the structural uncertainties, external disturbances, and unknown characteristics of the dead-zone nonlinearities, which reduces the computational burden considerably. The designed controller is... 

    Adaptive finite-time neural control of non-strict feedback systems subject to output constraint, unknown control direction, and input nonlinearities

    , Article Information Sciences ; Volume 520 , 2020 , Pages 271-291 Kamalamiri, A ; Shahrokhi, M ; Mohit, M ; Sharif University of Technology
    Elsevier Inc  2020
    Abstract
    This paper addresses the finite-time controller design for a class of nonlinear systems in the non-strict feedback form subject to unknown system dynamics and disturbances, arbitrary asymmetric time-varying output constraints, four types of input nonlinearities, and unknown control direction. Utilizing the barrier Lyapunov function (BLF) and backstepping technique, an adaptive finite-time controller has been proposed. The difficulties associating with non-strict feedback systems have been handled using the variable separation approach. Furthermore, the unknown control direction problem has been tackled by using the Nussbaum gain function. A unified framework has been utilized for handling... 

    Adaptive finite-time fault-tolerant controller for a class of uncertain MIMO nonlinear switched systems subject to output constraints and unknown input nonlinearities

    , Article Nonlinear Analysis: Hybrid Systems ; Volume 35 , February , 2020 Moradvandi, A ; Malek, S. A ; Shahrokhi, M ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    In this work, design of an adaptive finite-time fault-tolerant controller for a class of uncertain multi-input multi-output (MIMO) nonlinear switched systems with unmodeled dynamics subject to asymmetric time-varying output constraints and unknown faulty input nonlinearities has been addressed. The number of actuator faults can be infinite. In addition, the proposed control algorithm can cope with different unknown types of input nonlinearities namely, saturation, dead zone, backlash, and hysteresis. Actuator faults and input nonlinearities can be different in different modes. To estimate the system uncertainties, neural networks (NNs) have been employed and the unmodeled dynamics has been... 

    Observer-Based Controller Design for Nonlinear Fractional Order Systems

    , M.Sc. Thesis Sharif University of Technology Rahmani Nooshabadi, Ali (Author) ; Shahrokhi, Mohammad (Supervisor)
    Abstract
    In this study, an adaptive controller design for nonlinear fractional order systems in the strict-feedback form has been investigated. The system is subject to unknown dynamics, unmeasured state variables, quantized input and output, and input nonlinearity. A linear observer is used to solve the problem of unmeasured state variables. The fuzzy logic system is used to estimate the unknown functions, and instead of updating all the regressor weights, only the upper bound of their norms is updated, which significantly reduces the computational load. In the controller design, limitations due to the bandwidth of data transmission have been considered by applying quantizers in the input and output... 

    A novel robust decentralized adaptive fuzzy control for swarm formation of multiagent systems

    , Article IEEE Transactions on Industrial Electronics ; Volume 59, Issue 8 , 2012 , Pages 3124-3134 ; 02780046 (ISSN) Ranjbar-Sahraei, B ; Shabaninia, F ; Nemati, A ; Stan, S. D ; Sharif University of Technology
    IEEE  2012
    Abstract
    In this paper, a novel decentralized adaptive control scheme for multiagent formation control is proposed based on an integration of artificial potential functions with robust control techniques. Fully actuated mobile agents with partially unknown models are considered, where an adaptive fuzzy logic system is used to approximate the unknown system dynamics. The robust performance criterion is used to attenuate the adaptive fuzzy approximation error and external disturbances to a prescribed level. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, and applicability on a large diversity of autonomous...