所以本文从最最基本的一个动机开始讲起。 模型预测控制(model predictive control)顾名思义有三个主要部分构成,1模型;2预测;3控制(做决策),我们只要理解这三个部分和它们之间的关系即可。 1 模型,模型可以是机理模型,也可以是一个基于数据的模型(例如用神经网络training 一个model出来) 2 预测,建立模型的目的是...
MPC basic control loop The lower part of the following picture shows in more detail the reference trajectory and the predicted plant outputs. The MPC controller uses its internal prediction model to predict the plant outputs over the prediction horizonp. The upper part of the picture shows the ...
Model Predictive Control (MPC) Borrelli, Francesco, Alberto Bemporad, and Manfred Morari. Predictive control for linear and hybrid systems. Cambridge University Press, 2017 Framework Use a dynamical model of the process to predict its future evolution (finite time horizon) and choose the "best" con...
Model predictive control (MPC) technology for advanced process control (APC) in industrial applications: blending, kilns, boilers, distillation columns
In subject area: Engineering Model Predictive Control is an advanced model-based control scheme employing an explicit system model to predict future system outputs over a pre-defined horizon. From: Fault Detection, Supervision and Safety of Technical Processes 2006, 2007 ...
You try to sense the surroundings, predict the best path in the direction of a goal, but take only one step at a time and repeat the cycle. Similarly, the MPC process is like walking into a dark room. The essence of MPC is to optimize the manipulatable inputs and the forecasts of ...
【Linear MPC入门】Model Predictive Control Algorithm, Feasibility and Stability 有限时间带约束的优化问题,叫model predict control(MPC),或者也叫receding horizon control(RHC)。
Model Predictive Control (MPC) is a set of computer control algorithms which use a process model to predict the future response of a process. From: Computer Aided Chemical Engineering, 2011 About this pageSet alert Also in subject areas: ...
Assume, we have modeled the system from first principles and identified the parameters in an experiment. We are especially unsure about the exact value of the inertia of the masses. With Multi-stage MPC, we can define different scenarios e.g.±10%for each mass and predict as well as optimi...
the results. SinceSimOptions.Modelis not empty,SimOptions.Model.Plantis converted to discrete time (using zero order hold) and used as the plant in the closed loop simulation, while the plant inmpcobj.Model.Plantis only used by the controller to predict the response over the prediction ...