Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression
نویسندگان
چکیده
منابع مشابه
Automatic Gait Optimization with Gaussian Process Regression
Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function optimization procedures that suffer from three key drawbacks. Local optimization techniques are naturally plagued by local optima, make no use of the expensive gait evaluations once a local step is taken, and do not expli...
متن کاملLocal Gaussian Process Regression for Real Time Online Model Learning
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by local learning, we propose a method to speed up standard Gaussian process regression (GPR) with local GP models (LGP). The training data is partitioned in local regions, for each an individual GP model is trained. The...
متن کاملOnline sparse Gaussian process regression using FITC and PITC approximations ?
We provide a method which allows for online updating of sparse Gaussian Process (GP) regression algorithms for any set of inducing inputs. This method is derived both for the Fully Independent Training Conditional (FITC) and the Partially Independent Training Conditional (PITC) approximation, and it allows the inclusion of a new measurement point xn+1 in O(m) time, with m denoting the size of t...
متن کامل3D Deformable Object Manipulation using Fast Online Gaussian Process Regression
In this paper, we present a general approach to automatically visual-servo control the position and shape of a deformable object whose deformation parameters are unknown. The servo-control is achieved by online learning a model mapping between the robotic end-effector’s movement and the object’s deformation measurement. The model is learned using the Gaussian Process Regression (GPR) to deal wi...
متن کاملModel Learning with Local Gaussian Process Regression
Precise models of the robot inverse dynamics allow the design of significantly more accurate, energy-efficient and more compliant robot control. However, in some cases the accuracy of rigidbody models does not suffice for sound control performance due to unmodeled nonlinearities arising from hydraulic cable dynamics, complex friction or actuator dynamics. In such cases, estimating the inverse d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Process Control
سال: 2023
ISSN: ['1873-2771', '0959-1524']
DOI: https://doi.org/10.1016/j.jprocont.2022.12.001