Consensus-based state estimation for multi-agent systems with constraint information
TL;DR: In this paper, the authors considered a distributed estimation problem for multi-agent systems under state inequality constraints and proposed a consensus-based Kalman filter (CKF) and projection on the surface of constraints.
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Abstract: This paper considers a distributed state estimation problem for multi-agent systems under state inequality constraints. We first give a distributed estimation algorithm by projecting the consensus estimate with help of the consensus-based Kalman filter (CKF) and projection on the surface of constraints. The consensus step performs not only on the state estimation but also on the error covariance obtained by each agent. Under collective observability and connective assumptions, we show that consensus of error covariance is bounded. Based on the Lyapunov method and projection, we provide and prove convergence conditions of the proposed algorithm and demonstrate its effectiveness via numerical simulations.
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Fixed-time safe tracking control of uncertain high-order nonlinear pure-feedback systems via unified transformation functions
Chaoqun Guo,Jiangping Hu,Hao Jiang,Sergej Čelikovský,Xiaoming Hu +4 more
TL;DR: Fixed-time safe tracking control of uncertain high-order nonlinear pure-feedback systems via unified transformation functions. A new unified transformation function is proposed to handle both constrained and unconstrained cases. A fixed-time dynamic surface control technique is developed to facilitate the control design. An adaptive fixed-time control strategy is proposed to guarantee the fixed-time tracking.
Distributed State Estimation under State Inequality Constraints with Random Communication over Multi-Agent Networks
TL;DR: This paper introduces two random schemes, including a random sleep scheme and an event-triggered scheme, and proposes two random distributed estimation algorithm based on Lyapunov method and projection, which is shown to be bounded with probability one when the agents randomly take the measurement or communicate with their neighbors.
Fixed-time safe tracking control of uncertain high-order nonlinear pure-feedback systems via unified transformation functions
TL;DR: In this paper , a fixed-time safe control problem is investigated for an uncertain high-order nonlinear pure-feedback system with state constraints, and a new nonlinear transformation function is firstly proposed to handle both the constrained and unconstrained cases in a unified way.
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