Cooperative fault estimation for a class of heterogeneous multi-agents with stochastic nonlinearities based on finite impulse response filter
Yutao Wu
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aircraft, Ministry of Industry and Information Technology, Nanjing, China
Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing, China
Search for more papers by this authorCorresponding Author
Zehui Mao
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aircraft, Ministry of Industry and Information Technology, Nanjing, China
Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing, China
Correspondence Zehui Mao, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Email: [email protected]
Search for more papers by this authorXing-Gang Yan
School of Engineering, University of Kent, Canterbury, UK
Search for more papers by this authorBin Jiang
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aircraft, Ministry of Industry and Information Technology, Nanjing, China
Search for more papers by this authorYutao Wu
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aircraft, Ministry of Industry and Information Technology, Nanjing, China
Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing, China
Search for more papers by this authorCorresponding Author
Zehui Mao
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aircraft, Ministry of Industry and Information Technology, Nanjing, China
Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing, China
Correspondence Zehui Mao, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Email: [email protected]
Search for more papers by this authorXing-Gang Yan
School of Engineering, University of Kent, Canterbury, UK
Search for more papers by this authorBin Jiang
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aircraft, Ministry of Industry and Information Technology, Nanjing, China
Search for more papers by this authorFunding information: National Natural Science Foundation of China, 61922042; 62020106003; Qinglan Project of Jiangsu Province of China, Fundamental Research Funds for the Central Universities, FRF-BD-20-10A; Research Fund of State Key Laboratory of Mechanics and Control of Mechanical Structures (Nanjing University of Aeronautics and astronautics), MCMS-I-0521G05
Abstract
This article investigates the cooperative fault estimation problem for a class of heterogeneous multi-agent systems, in which the agent dynamics are governed by linear discrete time-varying systems with nonidentical dimensions subject to stochastic nonlinearities. A finite impulse response (FIR) filter based fault estimation scheme is developed via relative outputs to estimate the possible faults of the local and neighboring agents simultaneously. An analytical redundancy expressed in terms of all the states in the previous time window is originally established for deriving the fault estimation signal. The prior variance information coupled with fault estimation error in nonlinear form, is fully considered to design performance index through analysis of random matrix inequality. The optimal FIR filter gain is analytically obtained with computational efficiency by searching the minimum point of the relevant matrix trace function. Illustrative examples are finally provided to demonstrate the effectiveness and advantages of the developed results.
CONFLICT OF INTEREST
The authors declare that there are no conflicts of interest regarding the publication of this paper.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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