List of Articles Ahmad Fakharian

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  1 - On the Design of Extended State-Dependent Differential Riccati Equation Controller for Nonlinear Reaction-Advection-Diffusion Partial Differential Equation with Multiple Delays
  Fariba Bouzari Liavoli Ahmad Fakharian Hamid Khaloozadeh
  10.30495/ijsee.2023.1998804.1287
  This paper proposes a sub-optimal Extended State-Dependent Differential Riccati Equation (ESDDRE) controller for nonlinear Reaction-Advection-Diffusion (R-A-D) Partial Differential Equation (PDE) systems with multiple delays. A State-Dependent Riccati Equation (SDRE) is More

  This paper proposes a sub-optimal Extended State-Dependent Differential Riccati Equation (ESDDRE) controller for nonlinear Reaction-Advection-Diffusion (R-A-D) Partial Differential Equation (PDE) systems with multiple delays. A State-Dependent Riccati Equation (SDRE) is a nonlinear version of Linear Quadratic Regulator (LQR) in optimal control and it is used to analyze nonlinear optimal control problems. Instead of the linearization or the Jacobin procedure, the ESDDRE technique applies a State-Dependent Coefficients (SDC) for parameterization to construct an Extended Pseudo-Linearization (EPL) representation. All of the multiple delays sections in this presentation can be located in the system matrices and input vectors. The control effort of ESDDRE method is derived based on the Hamiltonian equation and also cost function according to the PDE systems. In addition, the L_2 stability is guaranteed by Poincaré inequality and as well as Lyapunov function regarded on the ESDDRE control strategy for the closed-loop system. The simulation results for the nonlinear R-A-D partial differential equation with one and two constant delays indicate that the proposed ESDDRE controller technique is efficient. Manuscript profile
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  2 - Long Term Optimal Control for HIV Treatment Using Spline Functions
  Hamed Fereidouni Ahmad Fakharian
  10.30495/ijsee.2021.685122
  20.1001.1.22519246.2021.10.04.6.1
  This paper presents a long term optimal control treatment of human immunodeficiency virus (HIV) infection. HIV destroys the body immune system, increases the risk of certain pathologies, damages body organs such as the brain, kidney, and heart, and causes death. Unfortu More

  This paper presents a long term optimal control treatment of human immunodeficiency virus (HIV) infection. HIV destroys the body immune system, increases the risk of certain pathologies, damages body organs such as the brain, kidney, and heart, and causes death. Unfortunately, this infectious disease currently has no cure; however, there are effective retroviral drugs for improving the patients’ health conditions. In this paper, two treatment drugs are considered to decrease the free HIV virus particles in the blood. Since excessive use of these drugs is not without harmful side effects, the prescription dosage should be minimum. Thus, we formulate an optimal control problem to reduce the HIV virus particles in the blood by using minimum drugs. To solve the obtained optimal control, direct method and spline functions are utilized. The main advantage of the direct method to the indirect method is the low computational cost of this solution. Spline functions are tools used in the direct solving approach to achieve the better solutions. Also, three different models are considered in this paper to evaluate the effectiveness of the proposed method in different conditions. In addition, in the end, we compare the results from the proposed approach with the results of the problem solving by indirect method. Furthermore, the sensitivity analysis is checked to demonstrate the performance of control system against parametric uncertainties. Manuscript profile
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  3 - Design of a Free Model Adaptive-Neural Controller for Level and Temperature Control of Liquid Storage Tanks
  Mohammad Hosein Ebrahimi Ebrahimi Mohammad Bagher Menhaj Morteza Nazari Monfared Ahmad Fakharian
  10.30495/ijsee.2021.684012
  20.1001.1.22519246.2021.10.03.1.4
  In this paper, an adaptive-neural free model scheme is proposed to control a widely-used nonlinear multivariable industrial system, a quadruple-tank process (QTP). The system consists of four tanks that are arranged in two upper and two lower formations. The main object More

  In this paper, an adaptive-neural free model scheme is proposed to control a widely-used nonlinear multivariable industrial system, a quadruple-tank process (QTP). The system consists of four tanks that are arranged in two upper and two lower formations. The main objective is defined as maintaining the level of the liquid in lower tanks via two pumps. Controlling this system is not an easy task since it has nonlinear dynamics, strong interaction between different channels, and highly interacted input and output variables. In the adaptive part of the proposed controller, the parameters and rules obtained from Lyapunov stability analysis, along with the estimation of nonlinear functions performed with the neural network, constitute the controller design steps. To highlight the controller's abilities, an additional object is defined, which is controlling the temperature of liquid of those two tanks by adding a heater to the QTP system as a modified system. Obviously, the interactions amongst the control loops are multiplied because the modified quadruple tank process (MQTP) system has four inputs and four outputs. One of the main contributions of this paper is the implementation of the closed-loop system. Regarding the importance of such a system in the industry and to test the controller practically, the closed-loop system is implemented in an industrial automation environment with the connection of Process Control System SIMATIC (PCS7) industrial software to MATLAB with Open Platform Communications (OPC) protocol. The effectiveness of the introduced scheme is verified by performing some experimental validation. Manuscript profile
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  4 - Robust H_2 / H_∞ Multi Objective Controller Design with Takagi-Sugeno Fuzzy Model for a Mobile Two-Wheeled Inverted Pendulum
  Davood Allahverdy Ahmad Fakharian
  20.1001.1.22519246.2022.11.1.2.8
  In this study, a robust H_2/H_∞ multi-objective state-feedback controller and tracking design are presented for a mobile two-wheeled inverted pendulum (MTWIP). The proposed control has to track the desired angular velocity while keeping the mobile two-wheeled inve More

  In this study, a robust H_2/H_∞ multi-objective state-feedback controller and tracking design are presented for a mobile two-wheeled inverted pendulum (MTWIP). The proposed control has to track the desired angular velocity while keeping the mobile two-wheeled inverted pendulum balanced. First, error of output states are added to the dynamic of system for better tracking control. And uncertainties of parameters are defined by affine parameters. Next, Takagi-Sugeno (T-S) fuzzy model is used for estimating the uncertainty of nonlinear model parameters. Robust H_2/H_∞ controller is designed and analyzed for each local linear subsystem of mobile two-wheeled inverted pendulum by using a linear matrix inequalities method. To sum up, in order to calculate the whole dynamic of system from each local linear subsystem, weight average defuzzifer method is used and the total controller is designed and analyzed according to parallel distribute compensation. The simulation indicate that the proposed scheme has high accuracy, robustness, good tracking, fast transient responses and lower control effort for a mobile two-wheeled inverted pendulum despite the uncertainties and external disturbance. Manuscript profile