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Kanticha Kittipeerachon,Noriyuki Hori 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
An exact discrete-time model of a matrix differential Riccati equation that has recently been proposed is applied to a finite-horizon optimal control problem. This discretization method can always be used for a usual backward-in-time computation of a time-varying feedback control gain, which can be stored then in a memory for later use. Unlike existing methods that involve errors, the proposed algorithm yields gain values that are exact to those of the continuous-time case at discrete-time instants for any discrete-time period. Furthermore, an approach is suggested for extending this method to an on-line computation of the optimal gain, by converting the boundary value condition into an initial value condition using the backward differential Riccati equation. It was found from simulation studies that the proposed on-line algorithm can yield the correct gain sequence under a certain condition, eliminating the need to prepare the gain sequence a priori. However, a further investigation is needed to clarify this condition.
Ruan, Xiaoe,Bien, Zeungnam Taylor Francis 2008 International Journal of Systems Science Vol.39 No.5
<P> In this article, a set of decentralised open-loop and closed-loop iterative learning controllers are embedded into the procedure of steady-state hierarchical optimisation utilising feedback information for large-scale industrial processes. The task of the learning controllers is to generate a sequence of upgraded control inputs iteratively to take responsibility for sequential step function-type control decisions, each of which is determined by the steady-state optimisation layer and then imposed on the real system for feedback information. In the learning control scheme, the learning gains are designated to be time-varying which are adjusted by virtue of expertise experiences-based IF-THEN rules, and the magnitudes of the learning control inputs are amplified by the sequential step function-type control decisions. The aim of learning schemes is to further effectively improve the transient performance. The convergence of the updating laws is deduced in the sense of Lebesgue 1-norm by taking advantage of the Hausdorff-Young inequality of convolution integral and the Hoelder inequality of Lebesgue norm. Numerical simulations manifest that both the open-loop and the closed-loop time-varying learning gain-based schemes can effectively decrease the overshoot, accelerate the rising speed and shorten the settling time, etc.</P>
An Ji Ho,Kim Han Sol 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.5
This paper proposes a novel approach to designing a fault-tolerant H∞ sampled-data fuzzy fi lter using exponential time-varying gains. The utilization of exponential time-varying gains not only achieves a reduction in convergence time but also provides relaxation in the numerical optimization of design conditions. Also, through the use of a robust control technique, the designed fi lter is equipped with enhanced fault-tolerant capabilities. In addition, suffi cient conditions for ensuring H∞ -based state estimation performance are derived as linear matrix inequalities (LMIs) based on the Lyapunov–Krasovskii functional (LKF). Finally, simulation results demonstrate the superior performance of the proposed method when compared to existing methodologies.
Optimal Guidance Law for Impact Angle and Acceleration Constraints with Time-Varying Gains
Junseong Kim,조성진 한국항공우주학회 2022 International Journal of Aeronautical and Space Sc Vol.23 No.3
In this paper, we establish an optimal guidance law for impact angle and acceleration constraints (OGL-IAAC). The optimal guidance law for impact angle (OGL) is widely used due to its energy optimality and analytic solutions. However, acceleration constraints may degrade the performance of the OGL owing to the significant guidance command at the initial and terminal time and hence saturated acceleration values may generate guidance errors. We introduce a new weighting function based on the guidance command closed-form solution of the OGL to address this problem. Then, we derive a new guidance law by using Schwarz’s inequality. The proposed guidance law generates time-varying gains to ensure that the guidance command is within the acceleration constraint. Moreover, the gains converge to the same values as those of the OGL when the time-to-go approaches zero. The proposed guidance law is demonstrated by simulations to investigate the performance and effect of varying coefficients of the weighting function.
Kanghui He,Chao-Yang Dong,Qing Wang 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.5
In this paper, we consider the problem of predictor design for nonlinear systems in the presence of unknown time-varying input-delays. A cascade integral high-gain predictor is proposed to estimate the future state. With a distinctive structure, the predictor can handle unknown delays and eliminate the “peaking phenomenon” during the transient period. Then, a predictor-based output feedback control is designed to guarantee the boundedness of system states. Lyapunov-Krasovskii functional and perturbation theories are used to prove the convergence of the estimation error and the closed-loop system. Finally, simulation results illustrate the superior performance of the cascade integral predictor compared to the standard high-gain predictor.
$H^$\infty$$ Gain-Scheduling 기법을 이용한 컨테이너 크레인의 흔들임 제어에 관한 연구
김영복,정용길,Kim, Yeong-Bok,Jeong, Yong-Gil 제어로봇시스템학회 2001 제어·로봇·시스템학회 논문지 Vol.7 No.7
The sway control problem of the pendulum motion of a container hanging on the trolly, which transports containers from a container ship to trucks, is considered in the paper. In the container crane control problem, suppressing the residual swing motion of the container at the end of acceleration, deceleration or the case of that the unexpected disturbance input exists is main issue. For this problem, in general, the trolley motion control strategy is introduced and applied. In this paper, we introduce and synthesize a new type of swing motion control system in which a small auxiliary mass is installed on the spreader. The actuator reacting against the auxiliary mall applies inertial control forces to the container to reduce the swing motion in the desired manner. In this paper, we apply the $H^$\infty$$ based gain-scheduling control technique to the anti-swing motion control system design problem of the controlled plant. In this control system, the controller dynamics are adjusted in real-time according to time-varying plant parameters. And the simulation result shows that the proposed control strategy is shown to be useful for the case of time-varying system and, robust to disturbances such as winds and initial sway motion.
Ji-Sun Park,Ho-Lim Choi,오상영 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.9
In this study, we reanalyze the global regulation problem for an input-delayed chain of integrators by output feedback. Our main objective is to achieve the faster/improved system regulation over the existing result. We propose a reduced-order observer based output feedback controller with a dynamic gain-scaling factor to achieve our main objective. The key feature of our control method is a newly designed reduced-order observer coupled with a dynamic gain-scaling factor. We analytically show that the controlled system is regulated with improved performance over the existing result. An example is given for illustration.
Ouarda Lamrabet,El Houssaine Tissir,Nabil El Fezazi,Fatima El Haoussi 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.9
This article presents some novel results on sampled-data H∞ control for a class of linear systems. The proposed system is affected by time-varying delay and external disturbance. The main goal of this paper is to transform the original system into an equivalent two interconnected subsystems through the combination of input-output approach and scaled small gain (SSG) theorem. Then, the three term approximation method is adopted to approximate the time-varying delay. By incorporating Lyapunov-Krasovskii functional and wirtinger integral inequality,a new set of sufficient conditions is obtained in terms of linear matrix inequalities (LMIs), which guarantee the stability of the closed loop system, and a H∞ norm bound performances. Finally, the applicability of the developed control design technique and its less conservativeness over other existing ones are proven by means of simulation Examples.
Redouane Chaibi,Hicham El Aiss,Ahmed El Hajjaji,Abdelaziz Hmamed 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.7
This paper investigates the problem of delay dependent stability and H∞ control design with derivatives of membership functions of uncertain Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delay. A model transformation is employed by considering a three-term approximation of delayed state vector. Using Scaled Small Gain (SSG) theorem and fuzzy weighting-dependent Lyapunov functions with some useful slack variables, less conservative robust stability and stabilization criteria are formulated in terms of linear matrix inequalities (LMIs), which can be easily solved by using standard numerical packages. Finally, numerical experiments are presented to illustrate the effectiveness of the proposed method.
이용만 한국부동산분석학회 2002 不動産學硏究 Vol.8 No.2
The objective of this article is to estimate 'expected growth rate of housing price' in Korea. Because it is rational to suppose that 'expected growth rate of housing price' is varying as time goes by, this article estimates 'expected growth rate' by Time-Varying Parameter Model. This article is using 'Junsei price to housing price ratio' data and corporation bond rate from January 1986 to November 2002 as time series data. From the output, this article concludes as follows : First, 'expected growth rate of housing price' has a property of random walk process. Second, 'expected growth rate of housing price' has a downward drift from November 1991. Third, 'expected growth rate of housing price' is about 2.5% ∼ 2.8% in November 2002.