• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1012-1019
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• 2016

A robust control intended for a nonholonomic mobile robot is considered to guarantee good tracking a desired trajectory. The main drawbacks of the mobile robot model are the existence of nonholonomic constraints, uncertain system parameters and un-modeled dynamics. in order to overcome these drawbacks, we propose a robust control based on Lyapunov theory associated with sliding-mode control, this solution shows good robustness with respect to parameter variations, measurement errors, noise and guarantees position and velocity tracking. The global asymptotic stability of the overall system is proven theoretically. The simulation results largely confirm the effectiveness of the proposed control.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1611-1624
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• 2017

With the rapid development of microgrid technology, microgrid projects are no longer limited to laboratory demonstrations and pilot platforms. It shows greater value in practical applications. Hence, the smooth interaction between a microgrid and the main grid plays a critical role. In this paper, a control method based on active disturbance rejection control (ADRC) is proposed in order to realize seamless transitions between grid-connected and islanding operation modes and stable operation with variable loads. It is verified by simulations that the proposed ADRC-based method features better performance when compared to conventional proportional-integral-differential (PID) control. Meanwhile, the stability of the third-order extended state observer (ESO) in second-order ADRC is validated by using Lyapunov stability criteria.

• Journal of Drive and Control
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• v.14 no.4
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• pp.61-70
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• 2017

In this study, an extended-state-observer (ESO) based non-linear servo control is introduced for an electro-hydrostatic actuator (EHA). Almost hydraulic systems not only are highly non-linear system that has mismatched uncertainties and external disturbances, but also can not measure some states. ESO that only use an output signal can be used to compensate these uncertainties and estimate unmeasurable states. To improve the position tracking performance, the barrier Lyapunov function (BLF) that can guarantee an output tolerance is introduced for the position tracking error signal of back stepping control procedures. Finally, the proposed servo control is compared with the proportional-integral (PI) control.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.307-312
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• 2021

This paper proposes an adaptive time-delayed control approach with the integral sliding-mode surface for the fast convergence rate of robot manipulators. Adaptive switching gain aims to guarantee the system stability in such a way as to suppress time-delayed estimation error in the proposed control approach. Moreover, it makes an effort to increase the convergence ability in reaching the phase. An integral sliding-mode surface is employed to achieve a fast convergence rate in the sliding phase. The stability of the proposed one is proved to be asymptotically stable in the Lyapunov stability. The efficiency of the proposed control approach is illustrated with a tutorial example in robot manipulator, which is compared to that of the existing control approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.850-856
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• 2018

In this paper, a controller based on repetitive learning control is designed to control an unmanned surface vessel with nonlinear characteristics and unknown parameters. First, we define the equations of motion and error system of the unmanned vessel, and then design an repetitive learning controller composed of system error and estimated unknown parameters based on repetitive learning control and adaptive control. The stability of the unmanned vessel model controlled by the designed controller is verified through the analysis of the Lyapunov stability. Simulation shows that the error converges asymptotically to zero with semi-global result, confirming that the unmanned vessel is moving toward a given ideal path, and verifies that the controller is also feasible.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.1
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• pp.39-63
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• 2019

In this paper, we study the effect of Cytotoxic T Lymphocyte (CTL) and antibody immune responses on the virus dynamics with both virus-to-cell and cell-to-cell transmissions. The infection rate is given by Holling type-II. We first show that the model is biologically acceptable by showing that the solutions of the model are nonnegative and bounded. We find the equilibria of the model and investigate their global stability analysis. We derive five threshold parameters which fully determine the existence and stability of the five equilibria of the model. The global stability of all equilibria of the model is proven using Lyapunov method and applying LaSalle's invariance principle. To support our theoretical results we have performed some numerical simulations for the model. The results show the CTL and antibody immune response can control the disease progression.

• Bulletin of the Korean Mathematical Society
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• v.58 no.3
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• pp.669-688
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• 2021

The aim of this paper is to prove the existence of an admissible inertial manifold for mild solutions to infinite delay evolution equation of the form $$\{{\frac{du}{dt}}+Au=F(t,\;u_t),\;t{\geq}s,\\\;u_s({\theta})={\phi}({\theta}),\;{\forall}{\theta}{\in}(-{{\infty}},\;0],\;s{\in}{\mathbb{R}},$$ where A is positive definite and self-adjoint with a discrete spectrum, the Lipschitz coefficient of the nonlinear part F may depend on time and belongs to some admissible function space defined on the whole line. The proof is based on the Lyapunov-Perron equation in combination with admissibility and duality estimates.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.66-72
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• 2021

Since the behavior of an autonomous underwater vehicle (AUV) is influenced by disturbances and moments that are not accurately known, the depth control law of AUVs must have the ability to track the input signal and to reject disturbances simultaneously. Here, we proposed robust tracking control for controlling the depth of an AUV. An augmented closed-loop system is represented by an error dynamic equation, and we can easily show the asymptotic stability of the overall system by using a Lyapunov function. The robust tracking controller is consisted of the internal model of the command signal and a state feedback controller, and it has the ability to track the input signal and reject disturbances. The closed-loop control system is robust to parameter uncertainties. Simulation results showed the control performance of the robust tracking controller to be better than that of a P + PD controller.

• Honam Mathematical Journal
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• v.44 no.3
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• pp.402-418
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• 2022

Noise is a fundamental factor to increased validity and regularity of spike propagation and neuronal firing in the nervous system. In this paper, we examine the stochastic version of the Izhikevich-FitzHugh neuron dynamical model. This approach is based on techniques presented by Luo and Guo, which provide a general framework for the bifurcation and stability analysis of two dimensional stochastic dynamical system as an Itô averaging diffusion system. By using largest lyapunov exponent, local and global stability of the stochastic system at the equilibrium point are investigated. We focus on the two kinds of stochastic bifurcations: the P-bifurcation and the D-bifurcations. By use of polar coordinate, Taylor expansion and stochastic averaging method, it is shown that there exists choices of diffusion and drift parameters such that these bifurcations occurs. Finally, numerical simulations in various viewpoints, including phase portrait, evolution in time and probability density, are presented to show the effects of the diffusion and drift coefficients that illustrate our theoretical results.