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Control of Fractional Order Systems with Input Constraints
, M.Sc. Thesis Sharif University of Technology ; 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...
Observer-based controller for treatment of hepatitis C infection using fractional order model
, Article Mathematical Methods in the Applied Sciences ; Volume 45, Issue 17 , 2022 , Pages 10689-10709 ; 01704214 (ISSN) ; Shahrokhi, M ; Pishro, A ; Sharif University of Technology
John Wiley and Sons Ltd
2022
Abstract
In this study, a stable observer-based feedback controller has been designed for treatment of hepatitis C infectious disease under interferon (IFN) therapy. In order to consider the memory behavior and uncertain nature of this biological system, an unknown dynamics fractional-order (FO) model has been utilized for describing the interactions between the healthy cells, infected cells, and hepatitis C virus (HCV). To cope with unknown dynamics, the fuzzy logic system (FLS) has been utilized. Limitation of the drug efficacy due to its negative side effects has been taken into account as an input saturation. In order to estimate the unknown states which are required for treatment, a full-order...
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) ; 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...
Adaptive neural quantized control for fractional-order full-state constrained non-strict feedback systems subject to input fault and nonlinearity
, Article Chaos, Solitons and Fractals ; Volume 166 , 2023 ; 09600779 (ISSN) ; Shahrokhi, M ; Mohit, M ; Sharif University of Technology
Elsevier Ltd
2023
Abstract
In this work, an adaptive neural network (NN)-based quantized fault-tolerant controller (FTC) has been designed for incommensurate fractional-order (FO) nonlinear systems (NSs) in the non-strict feedback form subject to independent asymmetric time-varying full-state constraints, input quantization, unknown dynamics, infinite number of actuator faults and unknown input nonlinearities. It is assumed that the controller communicates with the actuator via a network with limited bandwidth. To avoid network congestion, the control signal is first quantized by an asymmetric hysteresis quantizer (HQ), then transmitted to the actuator via the network. By incorporating the backstepping algorithm,...
Synthesis and Biological Evaluation of Superparamagnetic Iron Oxide Nanoparticles as Contrast Agents for Bioimaging Applications
,
M.Sc. Thesis
Sharif University of Technology
;
Maddah Hosseini, Hamid
(Supervisor)
;
Oghabian, Mohammad Ali
(Supervisor)
Abstract
A biocompatible ferrofluid containing ?Fe?_3 O_4 nanoparticles was produced using co precipitation of ?FeCl?_2.?4H?_(2 )O and ?FeCl?_3 ?6H?_2 O under ultrasonic irradiation power with NaOH being the alkaline. Two variables studied in this research were concentration and molecular weight of PEG, as the coating agent. The impact of these variables were carefully monitored on shape, size distribution and magnetic behavior of nanoparticles through SEM, DLS, XRD and VSM characterization techniques. Moreover, MRI relaxation times,T_1and T_2, were calculated using synthesized nanoparticles as contrast agents. Accordingly these nanoparticles were biologically evaluated by MTT assay. Results...