Distributed decoupling of linear multiagent systems with mixed matched and unmatched state-coupled nonlinear uncertainties

Rezaei, Vahid; Stefanovic, Margareta

doi:10.23919/acc.2017.7963359

Cited by 12 publications

(6 citation statements)

References 30 publications

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“…Theorem 3 (Exponential tracking behavior and guaranteed cost). Let Assumptions 1 and 2 be satisfied by the mixed-order interconnect agents (40) and (41). The structurally nonsymmetric control layers  cx and  cv in Design Procedure 3, with static weights given by  c , achieve cooperative tracking (42) with a robust exponential behavior and guaranteed bound on the associated cost function (46).…”

Section: Design Procedures 3 (Construction Of Control Layer Topologies)mentioning

confidence: 99%

“…In the first step, we propose a candidate Lyapunov function V(e) = e T Pe ≻ 0, where P ≻ 0 is the solution of ARE (52) and can be reconstructed using the closed-form solutions for sub-AREs (54) (based on the design matrices in Design Procedure 3). We let and conclude exponential first-order tracking behavior in the multi-layer MAS of mixed-order agents (40)- (41). We only need to note that the following calculation can be derived:…”

Section: Design Procedures 3 (Construction Of Control Layer Topologies)mentioning

confidence: 99%

“…In this subsection, we consider the mixed-order MAS of Subsection 3.3 with M = 2 second-order agents (40) and N − M = 3 first-order agents (41). The nonlinearities of second-order agents are the same as the first two agents in Subsection 4.2 (ie, i ∈  1 = {1, 2}), and those of first-order agents are the same as the last three agents in Subsection 4.1 (ie, i ∈ {3, 4, 5}).…”

Section: Mixed-order Interconnected Systemsmentioning

confidence: 99%

“…We also refer to the work of Tuna about a matrix‐weighted Laplacian consensus, and the work of Lombana and Bernardo regarding an analysis strategy to ensure consensus in a multiplex network of the completely known interconnected LTI agents with a priori given communication topologies. We further point out the works of Rezaei and Stefanovic and Rezaei and Stefanovic, which, based on a priori given communication topology, focused on a special graph theoretic stabilization problem for Lur'e nonlinearly interconnected MASs through the distributed decoupling of agents' dynamics. While the need for a complete knowledge about the interconnection topology was relaxed by Rezaei and Stefanovic, the method was still limited to a very special physical (dynamical) interconnection topology, there was no discussion on the performance of the closed‐loop interconnected systems, the order of agents were the same (cf the works of Liu and Liu and Feng et al), and the communication protocol was the same for all state variables of the agents (these issues will be discussed in Section 3).…”

Section: Introductionmentioning

confidence: 99%

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Multi‐layer distributed protocols for robust cooperative tracking in interconnected nonlinear multiagent systems

Rezaei

Stefanovic

2019

Intl J Robust & Nonlinear

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Summary We develop a mixed graph and optimal control theoretic formulation to design a robust cooperative control protocol for a large‐scale multiagent system with partially known interconnected first‐, second‐, or mixed first‐ and second‐order dynamics. In each case, we transform the control protocol design task to a robust communication graph design problem, which, from a cyber‐physical perspective, is interpreted as the control layer design problem for an interconnected system with unknown agent layer dynamics. According to this viewpoint, each state variable has its own control layer communication topology separate from the other state variable's communication topology and the unknown agent layer interconnection topologies. We prove that all cooperative, decentralized, and centralized tracking protocols can be treated as a single design problem and, by deriving closed‐form solutions for the robust control layer topologies, we further provide a simpler design procedure, which is only based on the matrix manipulations. Aside from the linear implementation of the protocol and the connection of the proposed formulation to the well known rules‐of‐thumb in optimal control theory, this creates a higher potential to transfer ideas to industry. Modeling uncertainties tolerable by a given control layer topology is analyzed, and a preliminary performance‐oriented analysis and design approach for large‐scale interconnected systems is discussed. We show that exactly the same steps can be followed to design appropriate control layers for both tracking and stabilization.

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Section: Design Procedures 3 (Construction Of Control Layer Topologies)mentioning

confidence: 99%

Section: Design Procedures 3 (Construction Of Control Layer Topologies)mentioning

confidence: 99%

Section: Mixed-order Interconnected Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi‐layer distributed protocols for robust cooperative tracking in interconnected nonlinear multiagent systems

Rezaei

Stefanovic

2019

Intl J Robust & Nonlinear

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“…In [10], a suboptimal consensus controller design was developed by employing a hierarchical LQ control approach for an appropriately chosen global performance index, and a similar idea for constructing a particular cost functional was employed in [11] to design a reduced order distributed controller. In [12] a distributed optimal control method was adopted to decouple a class of linear multi-agent systems with state coupled nonlinear uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Distributed Linear Quadratic Optimal Control: Compute Locally and Act Globally

Jiao

Trentelman

Camlibel

2020

IEEE Control Syst. Lett.

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In this paper we consider the distributed linear quadratic control problem for networks of agents with single integrator dynamics. We first establish a general formulation of the distributed LQ problem and show that the optimal control gain depends on global information on the network. Thus, the optimal protocol can only be computed in a centralized fashion. In order to overcome this drawback, we propose the design of protocols that are computed in a decentralized way. We will write the global cost functional as a sum of local cost functionals, each associated with one of the agents. In order to achieve 'good' performance of the controlled network, each agent then computes its own local gain, using sampled information of its neighboring agents. This decentralized computation will only lead to suboptimal global network behavior. However, we will show that the resulting network will reach consensus. A simulation example is provided to illustrate the performance of the proposed protocol.

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Distributed Decoupling of Partially-Unknown Interconnected Linear Multiagent Systems: State and Output Feedback Approaches

Rezaei

Stefanovic

2017

IFAC-PapersOnLine

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Distributed decoupling of linear multiagent systems with mixed matched and unmatched state-coupled nonlinear uncertainties

Cited by 12 publications

References 30 publications

Multi‐layer distributed protocols for robust cooperative tracking in interconnected nonlinear multiagent systems

Multi‐layer distributed protocols for robust cooperative tracking in interconnected nonlinear multiagent systems

Distributed Linear Quadratic Optimal Control: Compute Locally and Act Globally

Distributed Decoupling of Partially-Unknown Interconnected Linear Multiagent Systems: State and Output Feedback Approaches

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