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Feedback control of large-scale systems
01 Jan 1992-
TL;DR: A survey of the results and open problems in feedback control of large-scale systems of multivariable feedback systems and structure of interconnected systems.
Abstract: Large scale control systems results of multivariable feedback systems models and structure of interconnected systems decentralized stabilizability the decentralized stabilization and pole assignment optimal decentralized control stability analysis of interconnected systems decentralized design for strongly coupled subsystems decentralized design for weakly coupled systems decentralized PI controllers strongly coupled symmetric composite systems survey of the results and open problems in feedback control of large-scale systems.
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TL;DR: A classification of a number of decentralized, distributed and hierarchical control architectures for large scale systems is proposed and attention is focused on the design approaches based on Model Predictive Control.
1,234 citations
Cites background from "Feedback control of large-scale sys..."
...are [98,56], while a milestone paper in the field is [91]....
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TL;DR: In this paper, an extensive review on control schemes and architectures applied to dc microgrids (MGs) is presented, covering multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects, as well as nonlinear control algorithms.
Abstract: This paper performs an extensive review on control schemes and architectures applied to dc microgrids (MGs). It covers multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects, as well as nonlinear control algorithms. Islanding detection, protection, and MG clusters control are also briefly summarized. All the mentioned issues are discussed with the goal of providing control design guidelines for dc MGs. The future research challenges, from the authors’ point of view, are also provided in the final concluding part.
452 citations
Cites background from "Feedback control of large-scale sys..."
...When the complexity of local control synthesis is independent of the number of DGs in the MG, the design becomes scalable [16]....
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...In these cases, control synthesis is centralized [ [16] and the main problem is that design complexity can increase tremendously with the MG size....
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...Decentralized control, as defined in [15] and [16], performs regulation based on local measurements, while in comparison, distributed control is based on both local measurement and neighboring communication [17]....
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TL;DR: The overview is focused on recent decomposition approaches in interconnected dynamic systems due to their potential in providing the extension of decentralized control into networked control systems.
417 citations
Cites background from "Feedback control of large-scale sys..."
...The decision makers and the controllers have available only parts of the overall a priori and a posteriori information in decentralized control (Bakule & Lunze, 1988; Lunze, 1992)....
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...The principal ways of decentralizing the design tasks belong to two groups (Lunze, 1992):...
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...The first three items belong to strongly coupled subsystems, while the last two items are weakly coupled subsystems (Bakule & Lunze, 1988; Lunze, 1992; Šiljak, 1991)....
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TL;DR: In this article, the status of using many, distributed optimization-based controllers for feedback control of large-scale, dynamic processes is presented and evaluated, and the issue of taking advantage of the structure of the connections between the subsystems to reduce the required communication is discussed.
329 citations
01 Dec 2012
TL;DR: It is shown that the designed controller can guarantee all the signals in the closed-loop system to be semiglobally uniformly ultimately bounded in a mean square.
Abstract: This paper focuses on the problem of neural-network-based decentralized adaptive output-feedback control for a class of nonlinear strict-feedback large-scale stochastic systems. The dynamic surface control technique is used to avoid the explosion of computational complexity in the backstepping design process. A novel direct adaptive neural network approximation method is proposed to approximate the unknown and desired control input signals instead of the unknown nonlinear functions. It is shown that the designed controller can guarantee all the signals in the closed-loop system to be semiglobally uniformly ultimately bounded in a mean square. Simulation results are provided to demonstrate the effectiveness of the developed control design approach.
284 citations
Cites background from "Feedback control of large-scale sys..."
...The applications of largescale systems have been found in many practical systems, such as power systems, computer network systems, and economic systems [6], [7]....
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References
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TL;DR: In this paper, it was shown that there is a robust controller for a linear, time-invariant, multivariable system (plant) that asymptotic tracking/regulation occurs independent of input disturbances and arbitrary perturbations in the plant parameters of the system.
Abstract: Necessary and sufficient conditions are found for there to exist a robust controller for a linear, time-invariant, multivariable system (plant) so that asymptotic tracking/regulation occurs independent of input disturbances and arbitrary perturbations in the plant parameters of the system. In this problem, the class of plant parameter perturbations allowed is quite large; in particular, any perturbations in the plant data are allowed as long as the resultant closed-loop system remains stable. A complete characterization of all such robust controllers is made. It is shown that any robust controller must consist of two devices 1) a servocompensator and 2) a stabilizing compensator. The servocompensator is a feedback compensator with error input consisting of a number of unstable subsystems (equal to the number of outputs to be regulated) with identical dynamics which depend on the disturbances and reference inputs to the system. The sorvocompensator is a compensator in its own right, quite distinct from an observer and corresponds to a generalization of the integral controller of classical control theory. The sole purpose of the stabilizing compensator is to stabilize the resultant system obtained by applying the servocompensator to the plant. It is shown that there exists a robust controller for "almost all" systems provided that the number of independent plant inputs is not less than the number of independent plant outputs to be regulated, and that the outputs to be regulated are contained in the measurable outputs of the system; if either of these two conditions is not satisfied, there exists no robust controller for the system.
1,199 citations
TL;DR: In this article, the optimal control of linear time-invariant systems with respect to a quadratic performance criterion is discussed and an algorithm for computing FAST is presented.
Abstract: The optimal control of linear time-invariant systems with respect to a quadratic performance criterion is discussed. The problem is posed with the additional constraint that the control vector u(t) is a linear time-invariant function of the output vector y(t) (u(t) = -Fy(t)) rather than of the state vector x(t) . The performance criterion is then averaged, and algebraic necessary conditions for a minimizing F\ast are found. In addition, an algorithm for computing F\ast is presented.
906 citations
TL;DR: In this paper, a necessary and sufficient condition for the existence of local control laws with dynamic compensation to stabilize a given system is derived in terms of a new notion, called "fixed modes", which is a natural generalization of the well-known concept of uncontrollable modes and unobservable modes that occur in centralized control system problems.
Abstract: This paper considers the problem of stabilizing a linear time-invariant multivariable system by using several local feedback control laws. Each local feedback control law depends only on partial system outputs. A necessary and sufficient condition for the existence of local control laws with dynamic compensation to stabilize a given system is derived. This condition is stated in terms of a new notion, called "fixed modes," which is a natural generalization of the well-known concept of uncontrollable modes and unobservable modes that occur in centralized control system problems. A procedure that constructs a set of stabilizing feedback control laws is given.
906 citations
TL;DR: The content of main theorems is presented in a tutorial form aimed at a broad audience of engineers and applied mathematicians interested in control, estimation and optimization of dynamic systems.
892 citations
TL;DR: Equivalence relations in information and in control functions among different systems are developed and aid in the solving of many general problems by relating their solutions to those of the systems with "perfect memory".
Abstract: General dynamic team decision problems with linear information structures and quadratic payoff functions are studied. The primitive random variables are jointly Gaussian. No constraints on the information structures are imposed except causality. Equivalence relations in information and in control functions among different systems are developed. These equivalence relations aid in the solving of many general problems by relating their solutions to those of the systems with "perfect memory." The latter can be obtained by the method derived in Part I. A condition is found which enables each decision maker to infer the information available to his precedents, while at the same time the controls which will affect the information assessed can be proven optimal. When this condition fails, upper and lower bounds of the payoff function can still be obtained systematically, and suboptimal controls can be obtained.
677 citations