Likar B,Kocijan J.Predictive control of a gas–liquid separation plant based on a gaussian process model. Computers and Chemistry . 2007Likar, B.; Kocijan, J. Predictive control of a gas-liquid separation plant
This paper presents a stochastic model predictive control method for linear time﹊nvariant systems subject to stateヾependent additive uncertainties modelled by Gaussian process (GP). The new method is developed by re‐building the tube‐based model predictive control framework with chance constraints ...
内容提示: 1Cautious Model Predictive Control using GaussianProcess RegressionLukas Hewing, Melanie N. ZeilingerAbstract—Gaussian process (GP) regression has been widelyused in supervised machine learning for its f l exibility andinherent ability to describe uncertainty in the function estimation.In the ...
此研究生作品已出版并开放阅览。 版权信息 Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works. Dynamic Gaussian Process Models for Model Predictive Control of Vehicle Roll Broderick, David J. Auburn University ProQuest Dissertations & Theses, ...
1.The model used is(xed) identi(ed o)-line,which means that used control Referenceenerator r+ Optimisationlgorithm Processodel Model y u u n y + _ + ++ Fig.1.Block diagram of model predictive control system algorithm is not an adaptive one.The structure of the entire control loop is...
3、Gaussian Process for Modelling and Control of Dynamic Systems 这本书主要讲了高斯过程(GP)模型在非线性系统辨识和动态系统控制设计中的应用,这种方法在动态系统建模和工程实践中具有很大的潜力。 当然,读者可以在网站上下载所提出的一些算法的Matlab实现:Gaussian-Process-Model-based System-Identification Toolbox...
A framework for using Gaussian Process together with Model Predictive Control for optimal control.The framework has been implemented with the principles of being flexible enough to experiment with different GP methods, optimization of GP models. and using different MPC schemes and constraints. Examples ...
Firstly, an enhanced model constructed by a nominal and an additive Gaussian process (GP) model is learned on-line, where the GP model is stochastic and captures dynamic properties of actuators by using the training data. Furthermore, a stochastic model predictive control (SMPC) formulation is ...
Gaussian-Process-based-Model-Predictive-ControlBr**xx 上传13.2 MB 文件格式 zip Invalid JSONProject for the course "Statistical Learning and Stochastic Control" at University of Stuttgart 点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 PSN-Birthday-Recover:该存储库保存程序PSN Birthday Recover的源...
A framework for using Gaussian Process together with Model Predictive Control for optimal control.The framework has been implemented with the principles of being flexible enough to experiment with different GP methods, optimization of GP models. and using different MPC schemes and constraints. Examples ...