Control of Large-Scale Systems: Beyond Decentralized Feedback

Šiljak, D. D.; Zečević, A.I.

doi:10.1016/s1474-6670(17)31582-3

Cited by 69 publications

(43 citation statements)

References 24 publications

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“…Yet, the overall system must remain structurally stable in the first place hence the controlled systemic structure must retain its reachability (Siljak, 1991). Numerous methods and techniques have been developed to study "static properties" of complex control systems (Siljak and Zecevic, 2005) that go beyond reachability, including structural controllability, structurally fixed modes, and almost invariant subspaces, as well as structural decompositions of hierarchical and weak coupling variety (Siljak, 1991).…”

Section: The 2002 Unesco Publication Encyclopaedia Of Lifementioning

confidence: 99%

Applied System and Control Sciences to Social Systems: Globalization Age Paradigms

Dimirovski

2008

IFAC Proceedings Volumes

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Modern advanced information technologies resulting from automation of control and decision processes along with ubiquitous communications have a multitude of impacts on development of national economies within the global economy. Thus all kinds of social systems, being essentially human centred systems, is a cross-, inter-and multi-disciplinary challenge to systems and control researchers. Social systems in modern civilization are reviewed from the systems science viewpoint and on the grounds of recent developments in control science and technology and with regard to globalization paradigm. The innovative systems approaches employing results from hybrid systems theory and dynamical networks are needed to address the now-old challenges of combined knowledge and technology transfer world-wide for sustainable development that may remedy climate change and some of the negative socio-economic aspects of globalization.

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Section: The 2002 Unesco Publication Encyclopaedia Of Lifementioning

confidence: 99%

Applied System and Control Sciences to Social Systems: Globalization Age Paradigms

Dimirovski

2008

IFAC Proceedings Volumes

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“…Then, the overall plant is no longer controlled by a single controller but by an array of independent controllers that all together represent a decentralized controller. Therefore, the decentralized control has been a control of choice for large-scale systems because it is computationally efficient to formulate control law that use only locally available subsystem states or outputs [2]. Actually, considerable attention has been paid to the decentralized stabilization of large-scale systems during the last several decades [3]- [7].…”

Section: Introductionmentioning

confidence: 99%

Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach

Liu

Wang

2014

IEEE Trans. Neural Netw. Learning Syst.

304

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Abstract-In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuoustime nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.Index Terms-Adaptive dynamic programming, decentralized control, large-scale systems, neural networks, nonlinear interconnected systems, optimal control, policy iteration, reinforcement learning.

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“…However, the local state feedback controllers designed using this approach need complete state information (which may not be feasible to obtain). An output-feedback robust decentralised control using linear matrix inequality (LMI) techniques has been presented in [12].…”

Section: Introductionmentioning

confidence: 99%

Improved low-voltage-ride-through capability of fixed-speed wind turbines using decentralised control of STATCOM with energy storage system

Hossain

Pota

Ramos³

2012

IET Gener. Transm. Distrib.

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Control of Large-Scale Systems: Beyond Decentralized Feedback

Cited by 69 publications

References 24 publications

Applied System and Control Sciences to Social Systems: Globalization Age Paradigms

Applied System and Control Sciences to Social Systems: Globalization Age Paradigms

Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach

Improved low-voltage-ride-through capability of fixed-speed wind turbines using decentralised control of STATCOM with energy storage system

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