DESAIN KONTROL PENGOBATAN PADA MODEL SIRD UNTUK PENYEBARAN VIRUS COVID-19 MENGGUNAKAN BACKSTEPPING

In this article, we present a control design on a SIRD model with treatment in infected individuals. The SIRD model with treatment is obtained from literature study and the parameter model is obtained from covid-19 daily case in the Riau province using the Particle Swarm Optimization method. The control design is carried out based on the backstepping method combined with feedback linearization based on input and output (IOFL). The SIRD model which is a nonlinear system will be transformed into a normal form using IOFL. Each variable is then stabilized Lyapunov using virtual control which at the same time generates a new state variable. This stage will be carried out iteratively until the last state variable is stabilized using a real control function. This control function is then applied to the SIRD model using the inverse of IOFL transformation. The simulation results compared with the Pontryagin Minimum Principle (PMP) method show that by selecting the appropriate control parameters, backstepping obtains better control performance which is a smaller number of infected populations.

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Minimum time control of a two DOF robotic arm with noised measurements

Algerian Journal of Signals and Systems ◽

10.51485/ajss.v2i1.29 ◽

2017 ◽

Vol 2 (1) ◽

pp. 21-30

Author(s):

El-H. Guechi ◽

Y. Zennir ◽

L. Messikh ◽

M-L. Benloucif

Keyword(s):

Feedback Linearization ◽

Minimum Principle ◽

Minimum Time ◽

State Variables ◽

Nonlinear Dynamic Model ◽

Pontryagin Minimum Principle ◽

New Approach ◽

Luenberger Observer ◽

Time Control ◽

Feedback Linearization Control

This paper presents a new approach for minimum time control dynamics of a two links manipulator robot in the case of noised outputs. Briefly, this technique consists of linearizing a nonlinear dynamic model of the robot by using a feedback linearization control. Once, the linear model has been obtained, a minimum time control with constraints, using the Pontryagin Minimum Principle will be developed. Here, the objective is to control the arm robot from an initial configuration to the final configuration in minimum time. The state variables are estimated by a Kalman-Luenberger observer. In order to show the efficiency of the proposed method, some simulation results are given.

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OPTIMAL CONTROL MODELLING OF COVID-19 OUTBREAK IN SEMARANG CITY INDONESIA

Journal of Fundamental Mathematics and Applications (JFMA) ◽

10.14710/jfma.v3i2.8546 ◽

2020 ◽

Vol 3 (2) ◽

pp. 158-169

Author(s):

Dhimas Mahardika ◽

R. Heru Tjahjana ◽

Sunarsih Sunarsih

Keyword(s):

Optimal Control ◽

Control Function ◽

Human Life ◽

Minimum Principle ◽

Dynamic Modelling ◽

Control Measures ◽

Pontryagin Minimum Principle ◽

Infected Population ◽

Corona Virus ◽

Spread Model

Corona virus infection is lethal and life threatening to human life, for prevention it is necessary to carry out quarantined for a portion of susceptible, exposed, and infected population, this kind of quarantine is intended to reduce the spread of the corona virus. The optimal control that will be carried out in this research is conducting quarantine for a portion of susceptible, exposed, and infected individuals. This control function will be applied to the dynamic modelling of Covid-19 spread using Pontryagin Minimum Principle. We will describe the formulation of dynamic system of Covid-19 spread with optimal control, then we use Pontryagin Minimum Principle to find optimal solution of the control. The optimal control will aim to minimize the number of infected population and control measures. Numerical experiments will be performed to illustrate and compare the graph of Covid-19 spread model with and without control.

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An Intrinsic Material Tailoring Approach for Functionally Graded Axisymmetric Hollow Bodies Under Plane Elasticity

Journal of Elasticity ◽

10.1007/s10659-021-09822-y ◽

2021 ◽

Author(s):

Hassan Mohamed Abdelalim Abdalla ◽

Daniele Casagrande

Keyword(s):

Optimization Problem ◽

Volume Fraction ◽

Minimum Principle ◽

Equivalent Stress ◽

Micromechanical Model ◽

Plane Elasticity ◽

Functionally Graded ◽

Pontryagin Minimum Principle ◽

Volume Fractions ◽

Material Tailoring

AbstractOne of the main requirements in the design of structures made of functionally graded materials is their best response when used in an actual environment. This optimum behaviour may be achieved by searching for the optimal variation of the mechanical and physical properties along which the material compositionally grades. In the works available in the literature, the solution of such an optimization problem usually is obtained by searching for the values of the so called heterogeneity factors (characterizing the expression of the property variations) such that an objective function is minimized. Results, however, do not necessarily guarantee realistic structures and may give rise to unfeasible volume fractions if mapped into a micromechanical model. This paper is motivated by the confidence that a more intrinsic optimization problem should a priori consist in the search for the constituents’ volume fractions rather than tuning parameters for prefixed classes of property variations. Obtaining a solution for such a class of problem requires tools borrowed from dynamic optimization theory. More precisely, herein the so-called Pontryagin Minimum Principle is used, which leads to unexpected results in terms of the derivative of constituents’ volume fractions, regardless of the involved micromechanical model. In particular, along this line of investigation, the optimization problem for axisymmetric bodies subject to internal pressure and for which plane elasticity holds is formulated and analytically solved. The material is assumed to be functionally graded in the radial direction and the goal is to find the gradation that minimizes the maximum equivalent stress. A numerical example on internally pressurized functionally graded cylinders is also performed. The corresponding solution is found to perform better than volume fraction profiles commonly employed in the literature.

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Optimal Stochastic Control of Energy Storage System Based on Pontryagin Minimum Principle for Flattening PEV Fast Charging in a Service Area

IEEE Control Systems Letters ◽

10.1109/lcsys.2021.3066155 ◽

2021 ◽

pp. 1-1

Author(s):

Francesco Liberati ◽

Alessandro Di Giorgio ◽

Giorgio Koch

Keyword(s):

Energy Storage ◽

Stochastic Control ◽

Minimum Principle ◽

Storage System ◽

Energy Storage System ◽

Service Area ◽

Optimal Stochastic Control ◽

Pontryagin Minimum Principle ◽

Fast Charging

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IMPERFECT COORDINATION IN OPTIMIZATION

International Journal of Modern Physics C ◽

10.1142/s0129183109013868 ◽

2009 ◽

Vol 20 (04) ◽

pp. 527-538 ◽

Cited By ~ 1

Author(s):

ELENA RAMÍREZ BARRIOS ◽

JUAN G. DÍAZ OCHOA

Keyword(s):

Control Function ◽

Optimization Method ◽

Free Lattice ◽

Conventional Methods ◽

Definition Of

We present a novel optimization method for an Ising like system suspended in a lattice with nonstatic defects. Depending on the size of the experimental probe the system spontaneously defines a defect free lattice where the control function can be optimized using conventional methods as Metropolis heuristics. We illustrate this method in a lattice with variable defects and show how the magnetization of the system depends on the spontaneous definition of the defect-free lattice. This approximation should be useful as a basis for the definition of systems of agents with imperfect coordination.

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Co-state variable determination in Pontryagin’s Minimum Principle for energy management of hybrid vehicles

International Journal of Precision Engineering and Manufacturing ◽

10.1007/s12541-016-0146-1 ◽

2016 ◽

Vol 17 (9) ◽

pp. 1215-1222 ◽

Cited By ~ 16

Author(s):

Jianxing Zhang ◽

Chunhua Zheng ◽

Suk Won Cha ◽

Shanxu Duan

Keyword(s):

Energy Management ◽

Minimum Principle ◽

Hybrid Vehicles ◽

Pontryagin’S Minimum Principle ◽

State Variable ◽

Pontryagin's Minimum Principle

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Design of Magnetic Flux Feedback Controller in Hybrid Suspension System

Mathematical Problems in Engineering ◽

10.1155/2013/712764 ◽

2013 ◽

Vol 2013 ◽

pp. 1-7 ◽

Cited By ~ 6

Author(s):

Wenqing Zhang ◽

Jie Li ◽

Kun Zhang ◽

Peng Cui

Keyword(s):

Magnetic Flux ◽

Feedback Linearization ◽

Control Algorithm ◽

Suspension System ◽

Magnetic Suspension ◽

Magnetic Flux Density ◽

Stable Suspension ◽

State Variable ◽

Suspension Control ◽

National University

Hybrid suspension system with permanent magnet and electromagnet consumes little power consumption and can realize larger suspension gap. But realizing stable suspension of hybrid magnet is a tricky problem in the suspension control sphere. Considering from this point, we take magnetic flux signal as a state variable and put this signal back to suspension control system. So we can get the hybrid suspension mathematical model based on magnetic flux signal feedback. By application of MIMO feedback linearization theory, we can further realize linearization of the hybrid suspension system. And then proportion, integral, differentiation, magnetic flux density B (PIDB) controller is designed. Some hybrid suspension experiments have been done on CMS04 magnetic suspension bogie of National University of Defense Technology (NUDT) in China. The experiments denote that the new hybrid suspension control algorithm based on magnetic flux signal feedback designed in this paper has more advantages than traditional position-current double cascade control algorithm. Obviously, the robustness and stability of hybrid suspension system have been enhanced.

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