Model predictive control variable Cost function

In summary, the conversation discusses a MIMO system developed in Simulink and the use of Model Predictive Control for it. The speaker is seeking help in using a manipulated variable during specific times of day, specifically with the MPC toolbox. Another participant suggests using system time and a switch on the variable, but the speaker is specifically looking for a solution using the MPC toolbox.
  • #1
waseem85
2
0
Hi all,
I have a MIMO system which I have developed in Simulink and I have also work out the Model predictive control for it. Now I have a manipulated variable which I want to be used during night and remained turned off during day. I have tried but could not figure out how to do this in simulink model predictive control tool box?

Any ideas and help will be really appreciated.

Thanks in advance.

Regards
Waseem
 
Engineering news on Phys.org
  • #2
Cant you access system time and place a switch on the variable once the time meets conditions of day and night? Does it have to be only with the MPC toolbox?
 
  • #3
Hi Viscousflow,
Thanks for your kinds reply. Mate, it has to bedone with MPC tool box, any idea how to do that?

Regards
 

What is Model Predictive Control (MPC)?

Model Predictive Control (MPC) is a control strategy used in the field of engineering and applied mathematics to optimize the performance of a system by predicting future behavior and adjusting control inputs accordingly. It uses a mathematical model of the system to calculate the optimal control actions that minimize a cost function while satisfying constraints.

What is a variable in Model Predictive Control?

A variable in Model Predictive Control refers to a quantity that can change over time and has an impact on the performance of the system. These variables can be inputs, outputs, or states of the system, and they are used in the mathematical model to predict future behavior and determine the optimal control actions.

What is a Cost Function in Model Predictive Control?

A Cost Function in Model Predictive Control is a mathematical expression that quantifies the performance of the system. It is used to calculate the optimal control actions by minimizing the cost function while satisfying constraints. The cost function typically includes terms related to the desired performance, such as setpoints, and penalties for deviations from these setpoints.

How is a Cost Function selected in Model Predictive Control?

The selection of a Cost Function in Model Predictive Control depends on the specific application and the desired performance of the system. It is usually chosen to reflect the objectives and constraints of the system and can include terms related to energy efficiency, production cost, or stability. The Cost Function is typically adjusted and refined during the design process to achieve the desired control performance.

What are the benefits of using a Cost Function in Model Predictive Control?

Using a Cost Function in Model Predictive Control allows for the optimization of the system's performance while accounting for constraints. It enables the control algorithm to consider future behavior and adjust control actions accordingly, leading to improved control performance. Additionally, the use of a Cost Function allows for the incorporation of multiple objectives, such as cost and energy efficiency, into the control strategy.

Similar threads

(Control) Derivative filter and discrete model
    • General Engineering
Replies
0
Views
702
How to model the behavior of a closed loop position system?
    • General Engineering
Replies
9
Views
2K
Adaptive PID controller implementation
    • General Engineering
Replies
5
Views
3K
What is the "observer" in PID control?
    • Electrical Engineering
Replies
12
Views
2K
How can I accurately model a digital control valve without physical testing?
    • General Engineering
Replies
3
Views
2K
Control of an inverted pendulum (or any other dynamic system in general), how to implement it?
    • General Engineering
Replies
4
Views
4K
I Statistical modeling and relationship between random variables
    • Set Theory, Logic, Probability, Statistics
Replies
7
Views
450
Motion simulator software control
    • General Engineering
Replies
3
Views
2K
I How to propagate errors through a regression & non-linear model?
    • General Math
Replies
8
Views
2K
Heat transfer from copper coil
    • General Engineering
Replies
3
Views
4K

Hot Threads

Recent Insights

Back
Top