State feedback controller sparsification via a notion of non-fragility

Bahavarnia, MirSaleh; Somarakis, Christoforos; Motee, Nader

doi:10.1109/cdc.2017.8264278

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…wherein f K (K) and f L (L) denote Gamma PDFs for K and L, respectively. Also, we calculate the double integral bounds in (14) via Assumption 1 which is equivalent to the following inequalities:…”

Section: Probabilistic Robust Non-fragile Tuning Of a Pd Controllermentioning

confidence: 99%

“…The non-fragility concept has been utilized in state-feedback controller sparsification as well. [14][15][16] Moreover, it has been utilized in order reduction of LTI controllers. 17 Most of the existing tuning methods are deterministic.…”

Section: Introductionmentioning

confidence: 99%

“…In Reference 13, the authors have proposed a non‐fragile PID controller via an optimization‐based approach. The non‐fragility concept has been utilized in state‐feedback controller sparsification as well 14‐16 . Moreover, it has been utilized in order reduction of LTI controllers 17…”

Section: Introductionmentioning

confidence: 99%

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A probabilistic framework to achieve robust non‐fragile tuning methods: PD control of IPD‐modeled processes

Bahavarnia

Tavazoei

2021

Intl J Robust & Nonlinear

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We introduce a novel probabilistic framework to achieve robust non-fragile tuning methods in control of processes with parametric uncertainties. We consider probability distributions to model the process parameters' uncertainties.First, we propose the tuning framework in a general setting. Then, as an illustration, we apply it to PD control of IPD-modeled processes. It is noteworthy that the proposed tuning method is robust against the considered parametric uncertainties. Also, to empower the proposed robust tuning method in the viewpoint of non-fragility, we utilize a centroid approach. Selecting the form of the probabilistic framework, we empirically observe some of the popular tuning methods are special cases of the proposed novel framework. Moreover, we theoretically/empirically make a comparison among the tuning methods in the literature based on non-fragility and robustness via such a probabilistic framework.

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Section: Probabilistic Robust Non-fragile Tuning Of a Pd Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A probabilistic framework to achieve robust non‐fragile tuning methods: PD control of IPD‐modeled processes

Bahavarnia

Tavazoei

2021

Intl J Robust & Nonlinear

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“…The sparse control design in such cases must also be robust against the uncertainties. Robust designs have been reported in several recent papers such as [7]- [10] using H ∞ control, which is suitable for handling norm-bounded uncertainties in the system dynamics. In particular, [8], [9] employ both H 2 and H ∞ control, thus balancing the H 2 performance of the nominal system and robustness objective.…”

Section: Introductionmentioning

confidence: 99%

Game-Theoretic Mixed $H_2/H_{\infty}$ Control with Sparsity Constraint for Multi-agent Networked Control Systems

Lian,

Chakrabortty,

Duel-Hallen

2019

Preprint

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Multi-agent networked control systems (NCSs) are often subject to model uncertainty and are limited by large communication cost, associated with feedback of data between the system nodes. To provide robustness against model uncertainty and to reduce the communication cost, this paper investigates the mixed H2/H∞ control problem for NCS under the sparsity constraint. First, proximal alternating linearized minimization (PALM) is employed to solve the centralized social optimization where the agents have the same optimization objective. Next, we investigate a sparsity-constrained noncooperative game, which accommodates different control-performance criteria of different agents, and propose a best-response dynamics algorithm based on PALM that converges to an approximate Generalized Nash Equilibrium (GNE) of this game. A special case of this game, where the agents have the same H2 objective, produces a partially-distributed social optimization solution. We validate the proposed algorithms using a network with unstable node dynamics and demonstrate the superiority of the proposed PALM-based method to a previously investigated sparsity-constrained mixed H2/H∞ controller.

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Sparsity in Linear Dynamical Systems

Joseph,

Murthy

2024

Springer Tracts in Electrical and Electronics Engineering

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State feedback controller sparsification via a notion of non-fragility

Cited by 8 publications

References 32 publications

A probabilistic framework to achieve robust non‐fragile tuning methods: PD control of IPD‐modeled processes

A probabilistic framework to achieve robust non‐fragile tuning methods: PD control of IPD‐modeled processes

Game-Theoretic Mixed $H_2/H_{\infty}$ Control with Sparsity Constraint for Multi-agent Networked Control Systems

Sparsity in Linear Dynamical Systems

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