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  • Open Access

    ARTICLE

    Optimal Control of Slurry Pressure during Shield Tunnelling Based on Random Forest and Particle Swarm Optimization

    Weiping Luo1,2, Dajun Yuan1,2, Dalong Jin1,2,*, Ping Lu1,2, Jian Chen3

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 109-127, 2021, DOI:10.32604/cmes.2021.015683

    Abstract The control of slurry pressure aiming to be consistent with the external water and earth pressure during shield tunnelling has great significance for face stability, especially in urban areas or underwater where the surrounding environment is very sensitive to the fluctuation of slurry pressure. In this study, an optimal control method for slurry pressure during shield tunnelling is developed, which is composed of an identifier and a controller. The established identifier based on the random forest (RF) can describe the complex non-linear relationship between slurry pressure and its influencing factors. The proposed controller based on More >

  • Open Access

    ARTICLE

    Optimal and Memristor-Based Control of A Nonlinear Fractional Tumor-Immune Model

    Amr M. S. Mahdy1,2,*, Mahmoud Higazy1,3, Mohamed S. Mohamed1,4

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3463-3486, 2021, DOI:10.32604/cmc.2021.015161

    Abstract In this article, the reduced differential transform method is introduced to solve the nonlinear fractional model of Tumor-Immune. The fractional derivatives are described in the Caputo sense. The solutions derived using this method are easy and very accurate. The model is given by its signal flow diagram. Moreover, a simulation of the system by the Simulink of MATLAB is given. The disease-free equilibrium and stability of the equilibrium point are calculated. Formulation of a fractional optimal control for the cancer model is calculated. In addition, to control the system, we propose a novel modification of… More >

  • Open Access

    ARTICLE

    COVID-19 and Unemployment: A Novel Bi-Level Optimal Control Model

    Ibrahim M. Hezam1,2,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1153-1167, 2021, DOI:10.32604/cmc.2021.014710

    Abstract Since COVID-19 was declared as a pandemic in March 2020, the world’s major preoccupation has been to curb it while preserving the economy and reducing unemployment. This paper uses a novel Bi-Level Dynamic Optimal Control model (BLDOC) to coordinate control between COVID-19 and unemployment. The COVID-19 model is the upper level while the unemployment model is the lower level of the bi-level dynamic optimal control model. The BLDOC model’s main objectives are to minimize the number of individuals infected with COVID-19 and to minimize the unemployed individuals, and at the same time minimizing the cost… More >

  • Open Access

    ARTICLE

    Optimal Control Model for the Transmission of Novel COVID-19

    Isa Abdullahi Baba1,*, Bashir Ahmad Nasidi1, Dumitru Baleanu2,3,4

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3089-3106, 2021, DOI:10.32604/cmc.2021.012301

    Abstract As the corona virus (COVID-19) pandemic ravages socio-economic activities in addition to devastating infectious and fatal consequences, optimal control strategy is an effective measure that neutralizes the scourge to its lowest ebb. In this paper, we present a mathematical model for the dynamics of COVID-19, and then we added an optimal control function to the model in order to effectively control the outbreak. We incorporate three main control efforts (isolation, quarantine and hospitalization) into the model aimed at controlling the spread of the pandemic. These efforts are further subdivided into five functions; u1(t) (isolation of the… More >

  • Open Access

    ARTICLE

    Systematic Procedure for Optimal Controller Implementation Using Metaheuristic Algorithms

    Viorel Minzu*, Adrian Serbencu

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 663-677, 2020, DOI:10.32604/iasc.2020.010101

    Abstract The idea for this work starts from the situation in which a metaheuristic-based algorithm has already been developed in order to solve an optimal control problem. This algorithm yields an offline "optimal" solution. On the other hand, the Receding Horizon Control (RHC) structure can be implemented if a process model is available. This work underlines some of the practical aspects of joining the RHC to an existing metaheuristic-based algorithm in order to obtain a closed-loop control structure that can be further used in real-time control. The result is a systematic procedure that integrates a given More >

  • Open Access

    ARTICLE

    Fractional Optimal Control of Navier-Stokes Equations

    Abd-Allah Hyder1, 2, *, M. El-Badawy3

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 859-870, 2020, DOI:10.32604/cmc.2020.09897

    Abstract In this paper, the non-stationary incompressible fluid flows governed by the Navier-Stokes equations are studied in a bounded domain. This study focuses on the timefractional Navier-Stokes equations in the optimal control subject, where the control is distributed within the domain and the time-fractional derivative is proposed as RiemannLiouville sort. In addition, the control object is to minimize the quadratic cost functional. By using the Lax-Milgram lemma with the assistance of the fixed-point theorem, we demonstrate the existence and uniqueness of the weak solution to this system. Moreover, for a quadratic cost functional subject to the More >

  • Open Access

    ARTICLE

    Solving the Optimal Control Problems of Nonlinear Duffing Oscillators By Using an Iterative Shape Functions Method

    Cheinshan Liu1, 2, Chunglun Kuo1, Jiangren Chang3, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 33-48, 2020, DOI:10.32604/cmes.2020.08490

    Abstract In the optimal control problem of nonlinear dynamical system, the Hamiltonian formulation is useful and powerful to solve an optimal control force. However, the resulting Euler-Lagrange equations are not easy to solve, when the performance index is complicated, because one may encounter a two-point boundary value problem of nonlinear differential algebraic equations. To be a numerical method, it is hard to exactly preserve all the specified conditions, which might deteriorate the accuracy of numerical solution. With this in mind, we develop a novel algorithm to find the solution of the optimal control problem of nonlinear… More >

  • Open Access

    ARTICLE

    MTN Optimal Control of SISO Nonlinear Time-varying Discrete-time Systems for Tracking by Output Feedback*

    Hong-Sen Yan1,2, Jiao-Jun Zhang1,2, Qi-Ming Sun1,2

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 487-507, 2019, DOI:10.31209/2018.100000037

    Abstract MTN optimal control scheme of SISO nonlinear time-varying discrete-time systems based on multi-dimensional Taylor network (MTN) is proposed to achieve the real-time output tracking control for a given reference signal. Firstly, an ideal output signal is selected and Pontryagin minimum principle adopted to obtain the numerical solution of the optimal control law for the system relative to the ideal output signal, with the corresponding optimal output termed as desired output signal. Then, MTN optimal controller (MTNC) is generated automatically to fit the optimal control law, and the conjugate gradient (CG) method is employed to train… More >

  • Open Access

    ABSTRACT

    Inverse Estimation of 3-D Traction Stress Field of Adhered Cell based on Optimal Control Technique using Image Intensities

    Satoshi Ii1,*, Keisuke Ito1, Naoya Takakusaki1, Naoya Sakamoto1

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 49-49, 2019, DOI:10.32604/mcb.2019.07378

    Abstract Cells adhere to a substrate and generate traction forces in focal adhesions that enable them to apprehend extracellular mechanical properties [1]. Current concerns are focused on mechanisms how the mechanical balances hold in the cell and affect the cell behavior, and therefore non-invasive measurement techniques for the cell traction forces are required. The cell traction force microscopy (TFM) generalized by Dembo and Wang [2] is an attractive approach to non-invasively estimate cell traction force fields, in which an inverse problem is solved using a mechanical model of the substrate and displacement fields from fluorescent images… More >

  • Open Access

    ARTICLE

    Long Endurance and Long Distance Trajectory Optimization for Engineless UAV by Dynamic Soaring

    B. J. Zhu1,2, Z. X. Hou1, X. Z. Wang3, Q. Y. Chen1

    CMES-Computer Modeling in Engineering & Sciences, Vol.106, No.5, pp. 357-377, 2015, DOI:10.3970/cmes.2015.106.357

    Abstract The paper presents a comprehensive study on the performance of long endurance and long distance trajectory optimization of engineless UAV in dynamic soaring. A dynamic model of engineless UAV in gradient wind field is developed. Long endurance and long distance trajectory optimization problems are modelled by non-linear optimal control equations. Two different boundary conditions are considered and results are compared: (i) open long endurance pattern, (ii) closed long endurance pattern, (iii) open long distance pattern. In patterns of (i) and (ii), the UAV return to original position with the maximum flying time in pattern (ii) More >

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