arXiv subjects

Kunihisa Okano

Publications and source records attributed to Kunihisa Okano.

8 recordsLinked to original sources

arXiv2026

Distributed Event-Triggered Consensus Control of Discrete-Time Linear Multi-Agent Systems under LQ Performance Constraints

This paper proposes a distributed event-triggered control method that not only guarantees consensus of multi-agent systems but also satisfies a given LQ performance constraint. Taking the standard distributed control scheme with all-time communication as a baseline, we consider the problem of designing an event-triggered communication rule such that the resulting LQ cost satisfies a performance constraint with respect to the baseline cost while consensus is achieved. The main difficulty is that the performance requirement is global, whereas triggering decisions are made locally and asynchronously by individual agents, which cannot directly evaluate the global performance degradation. To address this issue, we decompose allowable degradation across agents and design a triggering rule that uses only locally available information to satisfy the given LQ performance constraint. For general linear agents on an undirected graph, we derive a sufficient condition that guarantees both consensus and the prescribed performance level. We also develop a tractable offline design method for the triggering parameters. Numerical examples illustrate the effectiveness of the proposed method.

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arXiv2026

Event-Based Control via Sparsity-Promoting Regularization: A Rollout Approach with Performance Guarantees

This paper presents a controller design framework aiming to balance control performance and actuation rate. Control performance is evaluated by an infinite-horizon average cost, and the number of control actions is penalized via sparsity-promoting regularization. Since the formulated optimal control problem has a combinatorial nature, we employ a rollout algorithm to obtain a tractable suboptimal solution. In the proposed scheme, actuation timings are determined through a multistage minimization procedure based on a receding-horizon approach, and the corresponding control inputs are computed online. We establish theoretical performance guarantees with respect to periodic control and prove the stability of the closed-loop system. The effectiveness of the proposed method is demonstrated through a numerical example.

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arXiv2024

Sparsity-Constrained Linear Quadratic Regulation Problem: Greedy Approach with Performance Guarantee

We study a linear quadratic regulation problem with a constraint where the control input can be nonzero only at a limited number of times. Given that this constraint leads to a combinational optimization problem, we adopt a greedy method to find a suboptimal solution. To quantify the performance of the greedy algorithm, we employ two metrics that reflect the submodularity level of the objective function: The submodularity ratio and curvature. We first present an explicit form of the optimal control input that is amenable to evaluating these metrics. Subsequently, we establish bounds on the submodularity ratio and curvature, which enable us to offer a practical performance guarantee for the greedy algorithm. The effectiveness of our guarantee is further demonstrated through numerical simulations.

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arXiv2020

Sensor placement minimizing the state estimation mean square error: Performance guarantees of greedy solutions

This paper studies selecting a subset of the system's output to minimize the state estimation mean square error (MSE). This results in the maximization problem of a set function defined on possible sensor selections subject to a cardinality constraint. We consider to solve it approximately by a greedy search. Since the MSE function is not submodular nor supermodular, the well-known performance guarantees for the greedy solutions do not hold in the present case. Thus, we use the quantities---the submodularity ratio and the curvature---to evaluate the degrees of submodularity and supermodularity of the objective function. By using the properties of the MSE function, we approximately compute these quantities and derive a performance guarantee for the greedy solutions. It is shown that the guarantee is less conservative than those in the existing results.

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arXiv2017

Stabilization of uncertain systems using quantized and lossy observations and uncertain control inputs

In this paper, we consider a stabilization problem of an uncertain system in a networked control setting. Due to the network, the measurements are quantized to finite-bit signals and may be randomly lost in the communication. We study uncertain autoregressive systems whose state and input parameters vary within given intervals. We derive conditions for making the plant output to be mean square stable, characterizing limitations on data rate, packet loss probabilities, and magnitudes of uncertainty. It is shown that a specific class of nonuniform quantizers can achieve stability with a lower data rate compared with the common uniform one.

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arXiv2017

Stabilization of systems with asynchronous sensors and controllers

We study the stabilization of networked control systems with asynchronous sensors and controllers. Offsets between the sensor and controller clocks are unknown and modeled as parametric uncertainty. First we consider multi-input linear systems and provide a sufficient condition for the existence of linear time-invariant controllers that are capable of stabilizing the closed-loop system for every clock offset in a given range of admissible values. For first-order systems, we next obtain the maximum length of the offset range for which the system can be stabilized by a single controller. Finally, this bound is compared with the offset bounds that would be allowed if we restricted our attention to static output feedback controllers.

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arXiv2014

Minimum data rate for stabilization of linear systems with parametric uncertainties

We study a stabilization problem of linear uncertain systems with parametric uncertainties via feedback control over data-rate-constrained channels. The objective is to find the limitation on the amount of information that must be conveyed through the channels for achieving stabilization and in particular how the plant uncertainties affect it. We derive a necessary condition and a sufficient condition for stabilizing the closed-loop system. These conditions provide limitations in the form of bounds on data rate and magnitude of uncertainty on plant parameters. The bounds are characterized by the product of the poles of the nominal plant and are less conservative than those known in the literature. In the course of deriving these results, a new class of nonuniform quantizers is found to be effective in reducing the required data rate. For scalar plants, these quantizers are shown to minimize the required data rate, and the obtained conditions become tight.

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arXiv2012

Data Rate Limitations for Stabilization of Uncertain Systems over Lossy Channels

This paper considers data rate limitations for mean square stabilization of uncertain discrete-time linear systems via finite data rate and lossy channels. For a plant having parametric uncertainties, a necessary condition and a sufficient condition are derived, represented by the data rate, the packet loss probability, uncertainty bounds on plant parameters, and the unstable eigenvalues of the plant. The results extend those existing in the area of networked control, and in particular, the condition is exact for the scalar plant case.

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