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Stochastic linear model predictive control with chance constraints–a review
In the past ten years many Stochastic Model Predictive Control (SMPC) algorithms have
been developed for systems subject to stochastic disturbances and model uncertainties …
been developed for systems subject to stochastic disturbances and model uncertainties …
An outlook on robust model predictive control algorithms: Reflections on performance and computational aspects
MB Saltık, L Özkan, JHA Ludlage, S Weiland… - Journal of Process …, 2018 - Elsevier
In this paper, we discuss the model predictive control algorithms that are tailored for
uncertain systems. Robustness notions with respect to both deterministic (or set based) and …
uncertain systems. Robustness notions with respect to both deterministic (or set based) and …
Chance-constrained dynamic programming with application to risk-aware robotic space exploration
Existing approaches to constrained dynamic programming are limited to formulations where
the constraints share the same additive structure of the objective function (that is, they can …
the constraints share the same additive structure of the objective function (that is, they can …
Chance-constrained optimal path planning with obstacles
Autonomous vehicles need to plan trajectories to a specified goal that avoid obstacles. For
robust execution, we must take into account uncertainty, which arises due to uncertain …
robust execution, we must take into account uncertainty, which arises due to uncertain …
Chance-constrained H∞ control for a class of time-varying systems with stochastic nonlinearities: the finite-horizon case
In this paper, a new finite-horizon H∞ control problem is considered for a class of time-
varying systems with stochastic nonlinearities, measurements degradation and chance …
varying systems with stochastic nonlinearities, measurements degradation and chance …
Non-gaussian chance-constrained trajectory planning for autonomous vehicles under agent uncertainty
Agent behavior is arguably the greatest source of uncertainty in trajectory planning for
autonomous vehicles. This problem has motivated significant amounts of work in the …
autonomous vehicles. This problem has motivated significant amounts of work in the …
Optimal covariance control for stochastic systems under chance constraints
This letter addresses the optimal covariance control problem for stochastic discrete-time
linear systems subject to chance constraints. To the best of our knowledge, covariance …
linear systems subject to chance constraints. To the best of our knowledge, covariance …
A probabilistically robust path planning algorithm for UAVs using rapidly-exploring random trees
The computationally efficient search for robust feasible paths for unmanned aerial vehicles
(UAVs) in the presence of uncertainty is a challenging and interesting area of research. In …
(UAVs) in the presence of uncertainty is a challenging and interesting area of research. In …
Stochastic model predictive control with joint chance constraints
This article investigates model predictive control (MPC) of linear systems subject to arbitrary
(possibly unbounded) stochastic disturbances. An MPC approach is presented to account …
(possibly unbounded) stochastic disturbances. An MPC approach is presented to account …
Optimal stochastic vehicle path planning using covariance steering
This letter addresses the problem of vehicle path planning in the presence of obstacles and
uncertainties, a fundamental robotics problem. While several path planning algorithms have …
uncertainties, a fundamental robotics problem. While several path planning algorithms have …