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Fuchun Jin 서울대학교 경제연구소 1998 Seoul journal of economics Vol.11 No.2
In this paper, I use an approximate solution to model the optimal consumption when the representative consumer faces labor income uncertainty. This approximate consumption function is based on Zeldes' (1989) numerical solution to the optimal consumption problem with CRRA utility and stochastic labor income. Unlike the certainty equivalence solution, this model assumes that the consumer discounts expected future labor income at a rate higher than the real interest rate. It therefore takes into consideration the precautionary savings of the consumer. The first order implications of the approximate consumption function, with and without the liquidity constrained consumers, are tested using quarterly US data. The evidence lends support to the claims of the approximate consumption function, particularly when liquidity constrained consumers are included. The empirical results of this paper imply that current consumption should be Granger caused by variables in the lagged information set. Meanwhile, consumption should be smoother than labor income, even when the latter follows an integrated process. Both implications have been documented in the literature. Based on this evidence, I conclude that the approximate model is a promising way of getting around the difficulties involved in obtaining a closed form solution when utility is of the general decreasing absolute risk aversion type.
Data Fusion-based Resilient Control System under DoS Attacks: A Game Theoretic Approach
Yuan Yuan,Fuchun Sun 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.3
In this paper, the resilient control under the Denial-of-Service (DoS) attack is rebuilt within the framework of Joint Directors of Laboratories (JDL) data fusion model. The JDL data fusion process is characterized by the so-called Game-in-Game approach, where decisions are made at different layers. The interactions between different JDL levels are considered which take the form of Packet Delivery Rate of the communication channel. Some criterions to judge whether the cyber defense system is able to protect the underlying control system is provided. Finally, a numerical example is proposed to verify the validity of the proposed method.
Li Li,Fuchun Sun 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.2
A class of nonlinear singularly perturbed systems can be approximated by the Fuzzy Singularly Perturbed Model (FSPM).This paper proposes a new direct adaptive controller on the basis of the FSPM. The aim is to make the states of the closed-loop system follow those of the reference model. The feedback gains of the controller can be adjusted on line; and we don’t require the parameters known in prior. Lyapunov constitute techniques are used to prove the stability of the closed loop sys-tems. Finally the simulations illustrate the effectiveness of this approach.
Resilient Control in the Presence of DoS Attack: Switched System Approach
Yuan Yuan,Fuchun Sun,Quanyan Zhu 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.6
This paper studies the switched resilient control of the Cyber-Physical Systems (CPSs) under Denial-of-Service (DoS) attack. We interpret the term ‘resilience’ as the ability to be both robust to the external disturbances in the physical layer, and defending against DoS attacks in the cyber layer. A hybrid-theoretical framework is proposed which is comprised of a physical control subsystem, a cyber security subsystem, and an interface which integrates the control design with the security configuration. Within this framework, the controller will switch in accordance with the competing result of the cyber attacker and defender. Our approach highlights the interaction between the physical control layer and cyber security layer and achieves the goal of coupled design. Some algorithms are provided to obtain the so-called joint defense strategies. Finally, the proposed method is applied to the voltage regulation of the Uninterrupted Power System (UPS).
Relative Diagnosability of Discrete-Event Systems and Its Opacity-Based Test Algorithm
Rui Zhao,Fuchun Liu,Zhusong Liu 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.4
The notion of relative diagnosability is proposed for logical automata and the concept of diagnosablerate is introduced to characterize the diagnosability property of a discrete-event system, which takes values in theinterval [0, 1]. The relationship between relative diagnosability and diagnosability introduced by Sampath et al. that relative diagnosability is weaker than diagnosability for discrete-event systems is analysed. Furthermore, anecessary and sufficient condition for relative diagnosability is presented. In particular, an opacity-based algorithmis developed to test the relative diagnosability, which is polynomial in the number of states of the system. Inaddition, the proposed algorithm may be used to deal with the problem of diagnosability.
Xi Ma,Fuchun Sun,Hongbo Li,Bing He 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.4
This paper investigates the tracking control problem of second-order multi-agent systems (MASs) inthe presence of unmatched disturbances and completely unknown dynamics. The extended state observer (ESO)and neural networks (NNs) are utilized to estimate and compensated the unmatched disturbances and unknowndynamics, respectively. By constructed a novel integral sliding-mode manifold incorporated with ESO output,a neural-network-based control algorithm is developed. Meanwhile, by Lyapunov theoretical analysis, the UUBstability of the tracking errors as well as within a sufficiently small region is guaranteed by the appropriate choiceof the parameters. Simulation results show that the proposed method exhibits much better control performancesthan the traditional I-SMC method, such as great robustness, reduced chattering and more accurate.
Appearance-based Robot Visual Servo via a Wavelet Neural Network
Qingjie Zhao,Zengqi Sun,Fuchun Sun,Jihong Zhu 대한전기학회 2008 International Journal of Control, Automation, and Vol.6 No.4
This paper proposes a robot visual servo approach based on image appearance and a wavelet function neural network. The inputs of the wavelet neural network are changes of image features or the elements of image appearance vector, and the outputs are changes of robot joint angles. Image appearance vector is calculated by using eigen subspace transform algorithm. The proposed approach does not need a priori knowledge of the robot kinematics, hand-eye geometry and camera models. The experiment results on a real robot system show that the proposed method is practical and simple.
Robust Consensus for Networked Mechanical Systems with Coupling Time Delay
Haibo Min,Shicheng Wang,Fuchun Sun,Jinsheng Zhang 제어·로봇·시스템학회 2012 International Journal of Control, Automation, and Vol.10 No.2
This paper studies the state consensus for a class of networked nonlinear mechanical systems with coupling time delay. In particular, robust consensus protocols for both deterministic and uncertain systems with time delay are investigated. For deterministic systems, we develop a P-like protocol which allows for variable coupling time delay. We show that it is sufficient to have only the relative position information together with a damping control term, whereas the relative velocity information is not needed for state consensus. Then, an adaptive robust control protocol is proposed for uncertain sys-tems with unknown parameters in the system dynamics and arbitrary constant coupling time delays. By introducing the passivity-based framework, we demonstrate that state consensus is still reachable in this case. Finally, a numerical example is included to illustrate the obtained results.
Xiong Luo,Zengqi Sun,Fuchun Sun 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.1
The study on nonlinear control system has received great interest from the international research field of automatic engineering. There are currently some alternative and complementary methods used to predict the behavior of nonlinear systems and design nonlinear control systems. Among them, characteristic modeling (CM) and fuzzy dynamic modeling are two effective methods. However, there are also some deficiencies in dealing with complex nonlinear system. In order to overcome the deficiencies, a novel intelligent modeling method is proposed by combining fuzzy dynamic modeling and characteristic modeling methods. Meanwhile, the proposed method also introduces the low-level learning power of neural network into the fuzzy logic system to implement parameters identification. This novel method is called neuro-fuzzy dynamic characteristic modeling (NFDCM). The neuro-fuzzy dynamic characteristic model based overall fuzzy control law is also discussed. Meanwhile the local adaptive controller is designed through the golden section adaptive control law and feedforward control law. In addition, the stability condition for the proposed closed-loop control system is briefly analyzed. The proposed approach has been shown to be effective via an example.
Seismic Investigation in the Central Korean Peninsula Using the Artificial Chemical Explosions
Kim, So Gu,Gao, Fuchun 한국지진연구소 1996 SAFE Vol.2 No.1
In April, 1996, seismic experiments were carried out in Kangwon province by the Seismological Institute of Hanyang University(SIHY). Several explosions are recorded through the whole experiments. The study here is to present preliminary results of (a) source parameters determined by using polarization method as well as the travel time method; (b) the shallow substructure determination by using pS converted waves. So study here is of interest for future study as well as further experiment.