• 제어로봇시스템학회논문지
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• 제6권5호
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• pp.333-338
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• 2000

This paper considers the decentralized control problem of linear time-invariant interconnected systems with delays. A decentralized output-feedback controller to obtain both stability and performance of the interconnected system is designed using the standard $H_\infty$ control theory, This paper provides sufficient conditions for such a controller to exist and provides an output feedback controller.

• 제어로봇시스템학회논문지
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• 제14권4호
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• pp.381-384
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• 2008

In this paper, we consider the problem of designing decentralized sliding mode static output feedback control laws for a class of large scale systems with mismatched uncertainties. We derive a sufficient condition for the existence of a linear switching surface in terms of constrained linear matrix inequalities(LMIs), and we parameterize the linear switching surfaces in terms of the solution matrices to the given constrained LMI existence conditions. We also give an LMI-based algorithm for designing decentralized switching feedback control laws. Finally, we give a design example in order to show the effectiveness of our method.

• 제어로봇시스템학회논문지
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• 제11권8호
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• pp.651-655
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• 2005

In this paper, we consider the problem of designing decentralized sliding mode control laws far a class of large scale systems with mismatched uncertainties. We derive a sufficient condition far the existence of a linear switching surface in terms of a linear matrix inequalities(LMIs), and we parameterize the linear switching surfaces in terms of the solution matrices to the given LMI existence conditions. We also give an algorithm for designing decentralized switching feedback control laws. Finally, we give a design example in order to show the effectiveness of our method.

• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.140-146
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• 2002

We consider a class of large-scale interconnected time delay systems and investigate a decentralized robust passive control problem. sufficient conditions for unforced interconnected uncertain systems with time delay to be robustly stable with extended strictly passivity is given in terms of algebraic Riccati inequality and linear matrix inequality. The decentralized robust passive control problem for norm-bounded and positive real uncertainty is shown to be converted to extended strictly positive real control problem for a modified system which contains neither time delay nor uncertainty.

• 제어로봇시스템학회논문지
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• 제2권2호
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• pp.88-95
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• 1996

It is inevitable for local systems to have deviations which represent interactions and modeling errors originated from the decomposition process of a large scale system. This paper presents a decentralized control scheme for interconnected systems using local linear models and a neuro-coordinator. In the proposed method, the local system is composed of a linear model and unknown deviations caused by linearizing the subsystems around operating points or by estimating parameters of the subsystems. Because the local system has unmeasurable deviations we define a local reference model which consists of a local linear model and a neural network to estimate the deviations indirectly. The reference model is reformed into a linear model which has no deviations through a transformation of input variables and we obtain an optimum feedback control law which minimizes a local performance index. Finally, we derive a decentralized feedback control law which consists of local linear states and neural network outputs. In the decentralized control, the neuro-coordinator generates a corrective control signal to cancel the effect of deviations through backpropagation learning with the errors obtained from the differences of the local system outputs and reference model outputs. Also, the stability of local system is proved by the degree of learning of the neural network under an assumption on a neural network learning index. It is shown by computer simulations that the proposed control scheme can be applied successfully to the control of a biased two-link planar robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.26-30
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• 2005

An LMI based method to construct a decentralized control law for large scale systems is discussed. It is extended to assure the stability not only of the overall system but also of each subsystem without interconnection. Then, it is simplified to have local feedback loops only for some selected subsystems.

• 대한산업공학회지
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• 제23권1호
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• pp.1-22
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• 1997

Learning control refers to controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented a theory of indirect decentralized learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper extends these results to apply to the indirect repetitive control problem in which a periodic (i.e., repetitive) command is given to a control system. Decentralized indirect repetitive control algorithms are presented that have guaranteed convergence to zero tracking error under very general conditions. The original motivation of the repetitive control and learning control fields was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the desired trajectory. Decentralized repetitive control is natural for this application because the feedback control for link rotations is normally implemented in a decentralized manner, treating each link as if it is independent of the other links.

• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.1-23
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• 2005

The decentralized static output feedback design problem is considered. A constrained trust region method is developed that solves this optimal control problem when a complete set of state variables is not available. The considered problem is interpreted as a non-linear (non-convex) constrained matrix optimization problem. Then, a decentralized constrained trust region method is developed for this problem class exploiting the diagonal structure of the problem and using inexact computations. Finally, numerical results are given for the proposed method.

• International Journal of Precision Engineering and Manufacturing
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• 제7권1호
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• 한국정밀공학회지
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• 제22권4호
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.