A Novel Fuzzy Approach for State Estimation of Nonlinear Hybrid Systems Using Particle Filtering Method

DOI10.1002/asjc.465zbMath1287.93087OpenAlexW2107865461MaRDI QIDQ5417004

M. Foad Samadi, Karim Salahshoor

Publication date: 15 May 2014

Published in: Asian Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asjc.465

zbMATH Keywords

fuzzy logicfault detectionstate estimationhybrid systemparticle filtersfuzzy-based particle filter

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Fuzzy control/observation systems (93C42) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)

Related Items (4)

Event‐triggered PCS Based Trajectory Tracking Control of Systems with Perturbation ⋮ State estimation for discrete-time Takagi-sugeno fuzzy systems with time-varying delays ⋮ Intelligent Setting Control for Clinker Calcination Process ⋮ Particle Smoother for Nonlinear Systems With One‐Step Randomly Delayed Measurements

Cites Work

• Fault diagnosis in discrete time hybrid systems -- a case study
• Robust state estimation and fault diagnosis for uncertain hybrid nonlinear systems
• Sequential Monte Carlo Methods in Practice
• A unified framework for hybrid control: model and optimal control theory
• Hybrid filtering for linear systems with non-Gaussian disturbances
• Particle filtering-based fault detection in non-linear stochastic systems
• Moving horizon estimation for hybrid systems
• A survey of convergence results on particle filtering methods for practitioners

This page was built for publication: A Novel Fuzzy Approach for State Estimation of Nonlinear Hybrid Systems Using Particle Filtering Method