Fuzzy model-based multi-objective dynamic programming with modified particle swarm optimization approach for the balance control of bicycle robot
DOI10.1049/CTH2.12199zbMATH Open1544.93437MaRDI QIDQ6595134
Zhang Chen, Yiyong Sun, Haotian Zhao, Mingguo Zhao, Xudong Zheng, Bin Liang
Publication date: 29 August 2024
Published in: IET Control Theory \& Applications (Search for Journal in Brave)
fuzzy controlnonlinear control systemsmobile robotsstability in control theoryoptimisation techniquescontrol system analysis and synthesis methodsinterpolation and function approximation (numerical analysis)mechanical variables controltransportation system control
Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59) Fuzzy control/observation systems (93C42) Automated systems (robots, etc.) in control theory (93C85) Fuzzy and other nonstochastic uncertainty mathematical programming (90C70) Dynamic programming (90C39)
Cites Work
- Title not available (Why is that?)
- Nonlinear system identification and control using state transition algorithm
- Model-free adaptive control optimization using a chaotic particle swarm approach
- PID controller design of nonlinear systems using an improved particle swarm optimization approach
- A Bicycle Can Be Self-Stable Without Gyroscopic or Caster Effects
- Particle swarm optimization in electromagnetics
- Linearized dynamics equations for the balance and steer of a bicycle: a benchmark and review
- Hands-free circular motions of a benchmark bicycle
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