Distributed estimation and control of multi-agent systems in uncertain environment

2013 ◽  
Vol 43 (6) ◽  
pp. 529-540
Author(s):  
Qiang ZHANG
Keyword(s):  
Distributed Estimation ◽  
Multi Agent Systems ◽  
Uncertain Environment ◽  
Agent Systems ◽  
Multi Agent ◽  
Estimation And Control ◽  
And Control

scholarly journals Nonlinear Attitude and Formation Estimation Spacecraft And Multi-Agent Systems

2021 ◽  
Author(s):  
Michael Rososhansky
Keyword(s):  
Particle Filter ◽  
Nonlinear Filtering ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Consensus Tracking ◽  
Multi Agent ◽  
Filtering Technique ◽  
Estimation And Control ◽  
And Control

This dissertation examines the state and parameter estimation problem of monolithic spacecraft and multi-agent systems in conjunction with the control algorithms. Nonlinear filtering techniques are investigated and applied to the problems of attitude estimation and control of monolithic spacecraft, distributed flltering for attitude estimation and control of satellite formation flying (SFF), and estimation and control of a multi-agent system in consensus tracking with uncertain dynamic model. The main objective is to investigate the performance of nonlinear filtering techniques under fault-free and fault-prone scenarios. In essence, the core of this research has been placed on identifying techniques to improve the efficiency and reduce the variance of estimations in nonlinear filtering. The research is primarily dedicated to the investigation of adaptive unscented Kalman Filter (AUKF) and particle Filter (PF). A nonlinear filtering technique has been proposed for sequential joint estimation of a multi-agent system in consensus tracking with uncertain dynamic model. The new filter is called marginalized unscented particle Filter (MUPF). The proposed filter uses the Rao-Blackwellised principle to couple the particle filtering technique with unscented transform algorithm

scholarly journals Nonlinear Attitude and Formation Estimation Spacecraft And Multi-Agent Systems

2021 ◽  
Author(s):  
Michael Rososhansky
Keyword(s):  
Particle Filter ◽  
Nonlinear Filtering ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Consensus Tracking ◽  
Multi Agent ◽  
Filtering Technique ◽  
Estimation And Control ◽  
And Control

This dissertation examines the state and parameter estimation problem of monolithic spacecraft and multi-agent systems in conjunction with the control algorithms. Nonlinear filtering techniques are investigated and applied to the problems of attitude estimation and control of monolithic spacecraft, distributed flltering for attitude estimation and control of satellite formation flying (SFF), and estimation and control of a multi-agent system in consensus tracking with uncertain dynamic model. The main objective is to investigate the performance of nonlinear filtering techniques under fault-free and fault-prone scenarios. In essence, the core of this research has been placed on identifying techniques to improve the efficiency and reduce the variance of estimations in nonlinear filtering. The research is primarily dedicated to the investigation of adaptive unscented Kalman Filter (AUKF) and particle Filter (PF). A nonlinear filtering technique has been proposed for sequential joint estimation of a multi-agent system in consensus tracking with uncertain dynamic model. The new filter is called marginalized unscented particle Filter (MUPF). The proposed filter uses the Rao-Blackwellised principle to couple the particle filtering technique with unscented transform algorithm

Dynamic Generation and Control of Optimally Persistent Formation for Multi-agent Systems

2014 ◽  
Vol 39 (9) ◽  
pp. 1431-1438 ◽  
Author(s):  
Xiao-Yuan LUO ◽  
Shi-Kai SHAO ◽  
Xin-Ping GUAN ◽  
Yuan-Jie ZHAO
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Dynamic Generation ◽  
And Control

scholarly journals Impulsive Consensus Tracking of Multiagent Systems with Quantization and Input Delays Using Position-Only Information

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Zhou ◽  
Yu-Zhen Qin ◽  
Kuo Feng ◽  
Wen-Shan Hu ◽  
Zhi-Wei Liu
Keyword(s):  
Sampling Period ◽  
Second Order ◽  
Quantization Scheme ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Consensus Tracking ◽  
Sufficient And Necessary Conditions ◽  
Multi Agent ◽  
Input Delays ◽  
And Control

This paper investigates the consensus tracking problem for second-order multi-agent systems without/with input delays. Randomized quantization scheme is considered in the communication channels, and impulsive consensus tracking algorithms using position-only information are proposed for the consensus tracking of multi-agent systems. Based on the algebraic graph theory and stability theory of impulsive systems, sufficient and necessary conditions for consensus tracking are studied. It is found that consensus tracking for second-order multi-agent systems without/with input delays can be achieved by appropriately choosing the sampling period and control gains which are determined by second/third degree polynomials. Simulations are performed to validate the theoretical results.

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