Blar i Institutt for teknisk kybernetikk på emneord "Cybernetics"
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Integral Line-of-Sight Guidance of Underwater Vehicles Without Neutral Buoyancy
(Journal article; Peer reviewed, 2016)This paper analyzes an integral line-of-sight guidance law applied to an underac-tuated underwater vehicle. The vehicle is rigorously modeled in 5 degrees of freedom usingphysical principles, and it is ... -
Nonlinear model predictive control with explicit back-offs for Gaussian process state space models
(Chapter, 2019)Nonlinear model predictive control (NMPC) is an efficient control approach for multivariate nonlinear dynamic systems with process constraints. NMPC does however require a plant model to be available. A powerful tool to ... -
Output feedback stochastic nonlinear model predictive control of a polymerization batch process
(Chapter; Peer reviewed, 2019)Nonlinear model predictive control (NMPC) is one of the few methods that can handle multivariate nonlinear control problems while accounting for process constraints. Many dynamic models are however affected by significant ... -
Path Planning for UGVs Based on Traversability Hybrid A*
(Peer reviewed; Journal article, 2021)In this letter, a new method of path planning for unmanned ground vehicles (UGVs) on terrain is developed. For UGVs moving on terrain, path traversability and collision avoidance are important factors. If traversability ... -
Sea state estimation based on vessel motion responses: Improved smoothness and robustness using Bezier surface and L1 optimization
(Peer reviewed; Journal article, 2021)Floating structures oscillate in waves, where these wave-induced motions may be critical for various marine operations. An important consideration is thereby given to the sea states at the planning and operating stages for ... -
Stochastic Nonlinear Model Predictive Control Using Gaussian Processes
(Chapter, 2018)Model predictive control is a popular control approach for multivariable systems with important process constraints. The presence of significant stochastic uncertainties can however lead to closed-loop performance and ...