Learn how to use MATLAB to design and test robust process control strategies for dynamic systems. Discover how to model, simulate, analyze, optimize, and validate your control systems.

MATLAB and Simulink offer various tools and libraries to help you create and modify your model, such as the Control System Toolbox, the Simscape platform, and the Model-Based Design approach.

This project deals with the implementation of a process monitoring system using Arduino and MATLAB graphical user interface (GUI). One of the major application areas in instrumentation engineering ...

The mathematical model of the crane was also derived for comparison. The intelligent control system is implemented as Fuzzy-PID controller. The physical modeling approach using MATLAB Simscape Toolbox ...

The first file aMPC_parameters.m is a Matlab script that stores all the variables needed to run the system model in the Simulink environment. The Simulink model consists of two main elements: a ...

“Control System Toolbox becomes more powerful and easier to use in R2016a,” says Paul Barnard, director – design automation, MathWorks.

Paper deals with industrial realization of feedback control of demanding applications on theirs control, control algorithms and visualization together with real time control from MATLAB/Simulink ...

Gaussian Process Model Dynamic System Identification Toolbox for Matlab - Dynamic-Systems-and-GP/GPdyn. ... Identification and Control of Dynamical Systems Using Neural Networks, IEEE Transactions on ...

“Modern Control Theory” simulation experiment comprehensive platform takes the inverted pendulum control system as the research object, relies on Matlab powerful numerical calculation and digital ...

Taking the linear inverted pendulum as the controlled object, the inverted pendulum simulation experimental platform is designed and implemented by Matlab/GUI. The platform includes six simulation ...