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Model Predictive Control (MPC) Software
Model Predictive Control (MPC) software is a type of advanced process control algorithm used to optimize process performance. It uses mathematical models and predictive algorithms to anticipate future conditions and automate how a system should respond. MPC is often used in industrial settings to adjust variables in real time, such as temperature, pressure, and flow rate. It enables manufacturers to maintain desired process operations with greater efficiency than traditional methods.
Engineering Software
Engineering software is software used by engineers to design, analyze and manufacture various products. It includes a wide range of applications such as CAD/CAE software, analysis tools, optimization tools, and programming tools. Engineering software can be used for a variety of tasks such as designing mechanical parts, analyzing structural stability, simulating system performance, and optimizing product designs. These applications enable engineers to optimize their designs for cost reduction and increased efficiency.
Advanced Process Control (APC) Systems
Advanced Process Control (APC) systems are computer-based systems that use mathematical models and algorithms to optimize the performance of industrial processes. APC systems aim to maintain a steady state operation with tight control over process variables such as temperature, pressure, flow rate, and composition. It incorporates feedback from sensors in the process to monitor performance and take corrective action when needed, in order to keep the process operating in the desired range. APC systems can help improve efficiency, reduce energy usage, increase throughput, and reduce product variability.

2 Products for "mpc" with 1 filter applied:

  • 1
    Model Predictive Control Toolbox
    Model Predictive Control Toolbox™ provides functions, an app, Simulink® blocks, and reference examples for developing model predictive control (MPC). For linear problems, the toolbox supports the design of implicit, explicit, adaptive, and gain-scheduled MPC. For nonlinear problems, you can implement single- and multi-stage nonlinear MPC. The toolbox provides deployable optimization solvers and also enables you to use a custom solver. You can evaluate controller performance in MATLAB® and Simulink by running closed-loop simulations. ...
    Starting Price: $1,180 per year
  • 2
    MPCPy

    MPCPy

    MPCPy

    MPCPy is a Python package that facilitates the testing and implementation of occupant-integrated model predictive control (MPC) for building systems. The package focuses on the use of data-driven, simplified physical or statistical models to predict building performance and optimize control. Four main modules contain object classes to import data, interact with real or emulated systems, estimate and validate data-driven models, and optimize control input.
    Starting Price: Free
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