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نمایش تعداد 1-9 از 9

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    Approximate Dynamic Programming for Two-player Zero-sum Game Related to H∞ Control of Unknown Nonlinear Continuous-time Systems 

    نوع: Journal Paper
    نویسنده : شعله یاسینی; محمدباقر نقیبی سیستانی; علی کریم پور; Sholeh Yasini; Mohammad Bagher Naghibi Sistani; Ali Karimpour
    سال: 2015
    خلاصه:

    This paper develops a novel concurrent learning-based approximate dynamics programming (ADP) algorithm for solving the two-player zero-sum (ZS) game arising in H∞ control of continuous-time (CT) systems with unknown nonlinear ...

    Reinforcement learning and neural networks for multi-agent nonzero-sum games of nonlinear constrained-input systems 

    نوع: Journal Paper
    نویسنده : شعله یاسینی; محمدباقر نقیبی سیستانی; علی کریم پور; Sholeh Yasini; Mohammad Bagher Naghibi Sistani; Ali Karimpour
    سال: 2015
    خلاصه:

    This paper presents an online adaptive optimal control method based on reinforcement learning to solve the multi-agent nonzero-sum (NZS) differential games of nonlinear constrained-input continuous-time systems. A non-quadratic ...

    Policy Iteration Algorithm Based on Experience Replay to Solve H∞ Control Problem of Partially Unknown Nonlinear Systems 

    نوع: Conference Paper
    نویسنده : شعله یاسینی; محمدباقر نقیبی سیستانی; علی کریم پور; Sholeh Yasini; Mohammad Bagher Naghibi Sistani; Ali Karimpour
    سال: 2014
    خلاصه:

    In this paper, an online adaptive optimal control algorithm based on policy iteration (PI) is developed to solve the H∞ control problem of partially unknown nonlinear continuous-time (CT) systems. The convergence of existing ...

    Data-based Reinforcement Learning Algorithm with Experience Replay for Solving Constrained Nonzero-sum Differential Games 

    نوع: Conference Paper
    نویسنده : شعله یاسینی; علی کریم پور; محمدباقر نقیبی سیستانی; Sholeh Yasini; Ali Karimpour; Mohammad Bagher Naghibi Sistani
    سال: 2014
    خلاصه:

    Abstract—In this paper a partially model-free reinforcement learning (RL) algorithm based on experience replay is developed for finding online the Nash equilibrium solution of the multi-player nonzero-sum (NZS) differential ...

    Active insulin infusion using fuzzy-based closed-loop 

    نوع: Conference Paper
    نویسنده : شعله یاسینی; محمدباقر نقیبی سیستانی; علی کریم پور; Sholeh Yasini; Mohammad Bagher Naghibi Sistani; Ali Karimpour
    سال: 2008
    خلاصه:

    Active insulin infusion using fuzzy-based closed-loop

    Agent-based Simulation for Blood Glucose 

    نوع: Journal Paper
    نویسنده : شعله یاسینی; محمدباقر نقیبی سیستانی; علی کریم پور; Sholeh Yasini; Mohammad Bagher Naghibi Sistani; Ali Karimpour
    سال: 2009
    خلاصه:

    This paper employs a new approach to regulate the

    blood glucose level of type I diabetic patient under an intensive

    insulin treatment. The closed-loop control scheme incorporates

    expert knowledge about ...

    Knowledge-based Closed-loop Control of Blood Glucose Concentration in Diabetic Patients and Comparison with H∞ Control Technique 

    نوع: Journal Paper
    نویسنده : شعله یاسینی; علی کریم پور; محمدباقر نقیبی سیستانی; Sholeh Yasini; Ali Karimpour; Mohammad Bagher Naghibi Sistani
    سال: 2012
    خلاصه:

    In this paper, fuzzy-based closed-loop controller is applied to obtain a robust controller for blood glucose regulation in type I diabetes mellitus patients. The control technique incorporates expert knowledge about treatment ...

    An Automatic Insulin Infusion System based on H-Infinity 

    نوع: Conference Paper
    نویسنده : شعله یاسینی; علی کریم پور; محمدباقر نقیبی سیستانی; sahar ghareh; Sholeh Yasini; Ali Karimpour; Mohammad Bagher Naghibi Sistani
    سال: 2008
    خلاصه:

    This paper presents a control algorithm for a type I diabetes mellitus patient under an intensive insulin treatment. The control algorithm employs a robust Hoc controller to regulate the blood glucose level. The control ...

    Online Concurrent Reinforcement Learning Algorithm to Solve Two-player Zero-sum Games for Partially-unknown Nonlinear Continuous-time Systems 

    نوع: Journal Paper
    نویسنده : شعله یاسینی; علی کریم پور; محمدباقر نقیبی سیستانی; حمید رضا مدرّس; Sholeh Yasini; Ali Karimpour; Mohammad Bagher Naghibi Sistani; Hamidreza Modares
    سال: 2014
    خلاصه:

    Online adaptive optimal control methods based on reinforcement learning algorithms typically need to check for the persistence of excitation condition, which is necessary to be known a priori for convergence of the algorithm. ...

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