A model‐and data‐driven predictive control approach for tracking of stochastic nonlinear systems using Gaussian processes
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Publication:6194773
DOI10.1002/rnc.6853OpenAlexW4381849709MaRDI QIDQ6194773
Publication date: 12 March 2024
Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/rnc.6853
Nonlinear systems in control theory (93C10) Optimal stochastic control (93E20) Model predictive control (93B45)
Cites Work
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- Stochastic tube MPC with state estimation
- The robust binomial approach to chance-constrained optimization problems with application to stochastic partitioning of large process networks
- Explicit use of probabilistic distributions in linear predictive control
- Confidence-based reasoning in stochastic constraint programming
- An approach to output-feedback MPC of stochastic linear discrete-time systems
- CasADi: a software framework for nonlinear optimization and optimal control
- Incorporating state estimation into model predictive control and its application to network traffic control
- Adaptive tracking control for nonlinear time-varying delay systems with full state constraints and unknown control coefficients
- Hybrid Gaussian process modeling applied to economic stochastic model predictive control of batch processes
- Filtering adaptive tracking controller for multivariable nonlinear systems subject to constraints using online optimization method
- Tracking control of MIMO nonlinear systems under full state constraints: a single-parameter adaptation approach free from feasibility conditions
- The scenario approach for stochastic model predictive control with bounds on closed-loop constraint violations
- On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
- Stochastic MPC Framework for Controlling the Average Constraint Violation
- ℒ1Adaptive Control Theory
- Removing the Feasibility Conditions Imposed on Tracking Control Designs for State-Constrained Strict-Feedback Systems
- Stable adaptive neural control scheme for nonlinear systems
- Decentralized filtering adaptive constrained tracking control for interconnected nonlinear systems
- An efficient method for stochastic optimal control with joint chance constraints for nonlinear systems
- Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting
- Stochastic Tubes in Model Predictive Control With Probabilistic Constraints
- Robust Model Predictive Control via Scenario Optimization
- Stochastic tracking control of multivariable nonlinear systems subject to external disturbances
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