Simplified optimised prescribed performance control for high-order multiagent systems with privacy preservation
DOI10.1080/00207721.2023.2212652zbMath1520.93027OpenAlexW4377824394MaRDI QIDQ6115800
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Publication date: 13 July 2023
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2023.2212652
reinforcement learningprivacy protectionpower exponential functionsspeed functionoptimised backstepping
Control/observation systems governed by partial differential equations (93C20) Control/observation systems governed by ordinary differential equations (93C15) Multi-agent systems (93A16) Consensus (93D50)
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Cites Work
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- Distributed fault detection for a class of large-scale systems with multiple incomplete measurements
- Adaptive regulation of high-order lower-triangular systems: an adding a power integrator technique
- A system-theoretic framework for privacy preservation in continuous-time multiagent dynamics
- Privacy Preserving Average Consensus
- Output-feedback Stabilization for Stochastic High-order Nonlinear Systems with a Ratio of Odd Integers Power
- A continuous feedback approach to global strong stabilization of nonlinear systems
- Output Tracking of High-Order Stochastic Nonlinear Systems with Application to Benchmark Mechanical System
- A Novel Framework for Backstepping-Based Control of Discrete-Time Strict-Feedback Nonlinear Systems With Multiplicative Noises
- Robust adaptive fuzzy control for non-strict feedback switched nonlinear systems with unmodeled dynamics
- Event-triggered neural adaptive anti-disturbance control of nonlinear multi-agent systems with asymmetric constraints
- Event-triggered adaptive decentralised control for switched interconnected nonlinear systems with unmodeled dynamics and full state constraints
- Secure and Privacy-Preserving Consensus
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