Find and compare the best Model Predictive Control (MPC) software in 2025
Sort:
Use the comparison tool below to compare the top Model Predictive Control (MPC) software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
-
1
Model Predictive Control Toolbox
MathWorks
$1,180 per yearThe Model Predictive Control Toolbox™ offers a comprehensive suite of functions, an intuitive app, Simulink® blocks, and practical reference examples to facilitate the development of model predictive control (MPC) systems. It caters to linear challenges by enabling the creation of implicit, explicit, adaptive, and gain-scheduled MPC strategies. For more complex nonlinear scenarios, users can execute both single-stage and multi-stage nonlinear MPC. Additionally, this toolbox includes deployable optimization solvers and permits the integration of custom solvers. Users can assess the effectiveness of their controllers through closed-loop simulations in MATLAB® and Simulink environments. For applications in automated driving, the toolbox also features MISRA C®- and ISO 26262-compliant blocks and examples, allowing for a swift initiation of projects related to lane keep assist, path planning, path following, and adaptive cruise control. You have the capability to design implicit, gain-scheduled, and adaptive MPC controllers that tackle quadratic programming (QP) problems, and you can generate an explicit MPC controller derived from an implicit design. Furthermore, the toolbox supports discrete control set MPC for handling mixed-integer QP challenges, thus broadening its applicability in diverse control systems. With these extensive features, the toolbox ensures that both novice and experienced users can effectively implement advanced control strategies. -
2
MPCPy
MPCPy
FreeMPCPy is a Python library designed to support the testing and execution of occupant-integrated model predictive control (MPC) within building systems. This tool emphasizes the application of data-driven, simplified physical or statistical models to forecast building performance and enhance control strategies. It comprises four primary modules that provide object classes for data importation, interaction with real or simulated systems, data-driven model estimation and validation, and optimization of control inputs. Although MPCPy serves as a platform for integration, it depends on various free, open-source third-party software for model execution, simulation, parameter estimation techniques, and optimization solvers. This encompasses Python libraries for scripting and data manipulation, along with more specialized software solutions tailored for distinct tasks. Notably, the modeling and optimization tasks related to physical systems are currently grounded in the specifications of the Modelica language, which enhances the flexibility and capability of the package. In essence, MPCPy enables users to leverage advanced modeling techniques through a versatile and collaborative environment. -
3
INCA MPC
Inca Tools
Advanced Process Control (APC) provides a highly efficient solution for enhancing your plant's performance without requiring any hardware modifications. By implementing an APC application, you can stabilize operations while simultaneously optimizing production or energy usage, leading to a deeper insight into your production processes. This term encompasses a wide array of methods and technologies that complement fundamental process control systems, which are primarily constructed using PID controllers. Some examples of APC technologies include LQR, LQC, H_infinity, neural networks, fuzzy logic, and Model-Based Predictive Control (MPC). An APC application continually optimizes plant operations every minute, round-the-clock, seven days a week, ensuring consistent efficiency. Among these technologies, MPC stands out as the most widely adopted within the industry, as it utilizes a process model to forecast the plant's behavior for the near future, typically ranging from a few minutes to several hours ahead, thus providing a strategic advantage in operational planning. Through the continual refinement of processes, APC not only improves efficiency but also contributes to long-term sustainability goals. -
4
PlantPAx
Rockwell Automation
Producers like yourself possess the expertise required to maneuver through the intricate hurdles of remaining competitive in today’s market landscape. This is applicable across a wide range of sectors, including pharmaceuticals, consumer goods, food and beverage, mining, and chemicals. Therefore, embracing the latest technological innovations is essential for advancing your ongoing digital transformation efforts. Throughout your organization, from the control room to executive meetings, users of process systems consistently grapple with the challenge of optimizing productivity while managing budget limitations and resource availability, all while tackling shifting operational risks. By addressing these challenges head-on, you can unlock significant productivity enhancements across your facility with the PlantPAx distributed control system (DCS). The features of this system can greatly influence the lifespan of your plant operations, ensuring that integrated and scalable systems enhance productivity, boost profitability, and minimize operational risks. Ultimately, investing in such advanced systems can lead to a more resilient and efficient production environment. -
5
Emerson DeltaV
Emerson
The DeltaV S-series Electronic Marshalling utilizing CHARMs allows for flexible placement of field cabling, independent of the type of signal or control methodology employed. The DeltaV™ Distributed Control System (DCS) is designed to streamline automation processes, which reduces operational challenges and mitigates project risks effectively. This advanced collection of products and services enhances plant efficiency through intuitive control solutions that are straightforward to manage and service. Importantly, the DeltaV DCS is adaptable, easily scaling to fit your specific requirements without introducing additional complexity. Furthermore, the seamless integration capabilities of the DeltaV system encompass various functions including batch processing, advanced control, change management, engineering tools, diagnostics, and much more, ensuring a comprehensive solution for your operational needs. Ultimately, this flexibility and integration pave the way for improved productivity and reliability in industrial environments. -
6
Pavilion8
Rockwell Automation
Navigating the complexities of industrial processes presents a significant challenge for businesses striving to be both responsive to market demands and economically viable. To meet these challenges, manufacturers are required to refine their production techniques in order to offer an expanded range of higher-value items while also accommodating shorter production runs. It is essential for them to enhance output, optimize operational efficiency, and elevate product quality to the fullest extent permitted by their existing equipment. Achieving this necessitates maximizing equipment uptime and facilitating smoother transitions while minimizing waste. Furthermore, there is an increasing expectation from the public for manufacturers to lessen their environmental footprint and adhere to strict emissions regulations. Rockwell Automation Pavilion8® Model Predictive Control (MPC) technology serves as an advanced intelligence layer that integrates with automation systems, continuously steering the plant toward achieving a multitude of business goals—including cost savings, reduced emissions, consistent quality, and increased production—while operating in real time. This innovative approach not only enhances operational effectiveness but also aligns with sustainability initiatives, positioning manufacturers for success in an evolving marketplace. -
7
COLUMBO
PiControl Solutions
A closed-loop universal multivariable optimizer is designed to enhance both the performance and quality of Model Predictive Control (MPC) systems. This optimizer utilizes data from Excel files sourced from Dynamic Matrix Control (DMC) by Aspen Tech, Robust Model Predictive Control Technology (RMPCT) from Honeywell, or Predict Pro from Emerson to develop and refine accurate models for various multivariable-controller variable (MV-CV) pairs. This innovative optimization technology eliminates the need for step tests typically required by Aspen Tech and Honeywell, operating entirely within the time domain while remaining user-friendly, compact, and efficient. Given that Model Predictive Controls (MPC) can encompass tens or even hundreds of dynamic models, the possibility of incorrect models is a significant concern. The presence of inaccurate dynamic models in MPCs leads to bias, which is identified as model prediction error, manifesting as discrepancies between predicted signals and actual measurements from sensors. COLUMBO serves as a powerful tool to enhance the accuracy of Model Predictive Control (MPC) models, effectively utilizing either open-loop or fully closed-loop data to ensure optimal performance. By addressing the potential for errors in dynamic models, COLUMBO aims to significantly improve overall control system effectiveness. -
8
Pitops
PiControl Solutions
Pitops stands out as the sole software solution capable of executing genuine closed-loop system identification with PID controllers in Auto mode, or even with secondary PID controllers in Cascade mode, without the necessity of interrupting the cascade chain or undertaking additional, labor-intensive plant step tests. No other competitor tool is capable of successfully identifying transfer functions using data from PID controllers in Cascade mode, making Pitops unparalleled in this regard. Additionally, Pitops conducts transfer function identification entirely in the time domain, unlike other tools that rely on the more intricate Laplace (S) or Discrete (Z) domains. It also has the remarkable ability to manage multiple inputs and identify several transfer functions simultaneously. Utilizing a groundbreaking proprietary algorithm, Pitops facilitates multiple inputs closed-loop transfer function system identification in the time domain, significantly surpassing traditional methods like ARX/ARMAX/Box and Jenkins used by competing tools. This innovative approach not only streamlines the process but also enhances accuracy and efficiency, making Pitops the preferred choice in the industry. -
9
Aspen DMC3
Aspen Technology
Enhance precision and sustainability in advanced process control (APC) models by integrating both linear and nonlinear variables through deep learning techniques, thereby expanding their operational capabilities. Achieve improved returns on investment through swift controller implementation, ongoing model refinement, and streamlined workflows that facilitate easier adoption by engineers. Transform the process of model creation with artificial intelligence and simplify controller calibration by using guided wizards that outline both linear and nonlinear optimization goals. Boost controller availability by leveraging cloud technology to access, visualize, and analyze real-time key performance indicators (KPIs). In the dynamic landscape of the global economy, energy and chemical industries are compelled to operate with increased flexibility to respond to market shifts and optimize profit margins. Aspen DMC3 represents an innovative digital solution that aids organizations in realizing a throughput enhancement of 2-5%, a yield increase of 3%, and a 10% decrease in energy usage. Explore the benefits of next-generation advanced process control solutions to stay competitive and efficient in the industry. The integration of these technologies not only addresses immediate operational challenges but also positions companies for long-term success in an increasingly competitive market. -
10
Cybernetica CENIT
Cybernetica
Cybernetica specializes in providing Nonlinear Model Predictive Control (NMPC) utilizing mechanistic models. Our innovative software solution, Cybernetica CENIT, features a versatile architecture capable of addressing diverse industrial challenges by delivering optimal strategies. This includes advanced multivariable optimal control, predictive control mechanisms, and intelligent feed-forward strategies, along with efficient handling of constraints. Furthermore, our adaptive control capabilities leverage state and parameter estimation, incorporating feedback from indirect measurements via the process model. The use of nonlinear models allows for effective operation across extensive ranges, enhancing the management of nonlinear processes. This leads to a diminished reliance on step-response experiments and bolstered accuracy in state and parameter estimations. Additionally, we offer control solutions for both batch and semi-batch operations, efficiently managing nonlinear processes that function under fluctuating conditions. Our technology also ensures optimal grade transitions in continuous operations, safe supervision of exothermic processes, and control of unmeasured variables, including conversion rates and product quality. As a result, we contribute to reduced energy consumption and a lower carbon footprint, while also enhancing overall process efficiency. In summary, Cybernetica is committed to advancing industrial control solutions that optimize performance and sustainability. -
11
AVEVA APC
AVEVA
AVEVA APC represents an advanced model predictive control system designed to enhance the economic efficiency of your manufacturing processes. In the current economic landscape, companies encounter diminished capital budgets, soaring energy expenses, and fierce competition on a global scale. AVEVA’s comprehensive Advanced Process Control solutions tackle intricate manufacturing obstacles by utilizing cutting-edge automatic control technologies that maximize the value derived from your operations. This system not only boosts production yields and quality but also diminishes energy consumption. Moreover, it plays a crucial role in optimizing manufacturing processes, facilitating ongoing performance enhancements that significantly benefit your financial outcomes. By leveraging state-of-the-art technology, AVEVA APC provides a holistic approach to process control that ultimately leads to increased profitability through improved quality, enhanced throughput, and decreased energy expenditures. With its ability to unlock the full potential of your processes, AVEVA APC is essential for any manufacturer aiming to thrive in a competitive market. -
12
The System 800xA by ABB transcends the traditional role of a Distributed Control System (DCS) by also functioning as an Electrical Control System, a Safety system, and a platform that facilitates collaboration, thereby enhancing engineering productivity, operator effectiveness, and asset management. This integrated electrical control capability allows users to manage the entire electrical infrastructure, covering everything from high-voltage switchgear to low-voltage motor controls, making it a versatile choice whether used alongside the 800xA DCS or independently. By utilizing intelligent devices, you can minimize the amount of hardwired cabling in switchgear while maintaining compatibility with various standard protocols. Moreover, the system’s robust digital communication capabilities enhance the flow of information from devices and streamline operations by potentially eliminating the need for additional electrical measurement devices. Through these features, ABB Ability System 800xA not only optimizes control over electrical systems but also significantly simplifies the overall management process.
-
13
Apromon
PiControl Solutions
Apromon is a web-based software tool designed to evaluate the performance of PID loop controls for both primary and Advanced Process Control (APC) systems. It assesses individual loops, cascade configurations, various APC loops, and even signals that lack a controller but have a process variable (PV). One of Apromon's standout features is its ability to transform different types of controllers, including those for flow, pressure, temperature, and level, into a unified "grade" factor, akin to the scoring system used by educators for student assessments, where 100 represents optimal performance and 0 signifies the lowest. The software operates continuously, performing evaluations at specified intervals to ensure that performance metrics are consistently calculated and stored. Unlike some competing products, Apromon guarantees that it will monitor every tag without omission, making it a reliable choice for continuous performance tracking. This dedication to comprehensive monitoring helps users maintain optimal control over their processes at all times.
- Previous
- You're on page 1
- Next
Model Predictive Control (MPC) Software Overview
Model Predictive Control (MPC) is a type of advanced control software that enables engineers to optimize the performance of industrial processes. This type of software uses a mathematical model to predict future process variables and then adjusts the process parameters in real time to continuously achieve optimal performance.
The main advantage of using MPC is that it allows for more accurate, reliable and efficient control over any number of variables in an industrial process than traditional open loop controllers. MPC software can also be automated, making it possible for human operators to oversee multiple processes without having to manually adjust them.
At its heart, MPC is based on predictive models which are used to calculate and forecast future values of various factors such as load, pressure and temperature. This prediction helps determine what course of action should be taken in order to reach the desired output or set point. The model takes into account external disturbances such as changing weather conditions or changes in customer demand and then rearranges plant operations accordingly in order to keep the system within specified limits while still achieving maximum efficiency.
MPC algorithms usually include predictive models that are constructed from linear equations or non-linear functions depending on the application being used. These equations take into consideration historical information as well as current system inputs and future predictions about how all these elements interact with each other, allowing for extremely precise control over a variety of parameters.
For instance, if an unplanned disturbance occurs within the system such as a sudden increase in customer demand or changes in outside temperatures, MPC will detect this quickly and feed updated controlling strategies back into the algorithm so that operations can be modified accordingly without sacrificing performance quality or safety levels. Additionally, since MPC is constantly updating its calculations based on new data points, it ensures that plants remain optimized even when faced with dynamic external influences such as changing resource availability or increasing competition from rivals.
In conclusion, Model Predictive Control (MPC) is an incredibly versatile piece of software designed specifically for industrial applications where optimizing operation costs while maintaining product quality is essential. By taking into account both past data points and future expectations about how certain factors could affect results, it allows users to better manage their processes while simultaneously minimizing energy consumption and maximizing profitability.
What Are Some Reasons To Use Model Predictive Control (MPC) Software?
- Flexibility: Model predictive control (MPC) software is more flexible than traditional control systems, as it allows users to set multiple goals and constraints. This means that the MPC software can be tailored to meet specific goals in complex systems with multiple inputs and outputs.
- Efficiency: The ability of MPC software to predict future performance helps increase efficiency and reduce energy costs by optimizing the use of resources over time. It also enables operators to make better decisions by allowing them to analyze the impact of their decisions over longer time periods.
- Reliability: MPC software provides reliable control even under uncertain conditions or when parameters change or vary unpredictably. By incorporating facts about system dynamics, it can adjust its forecasted strategy if required and thus ensure optimal system performance in changing environments.
- Real-time Control: MPC technology allows for fast reaction times which makes it ideal for real-time applications where fast response is essential such as power plants, robotics, automotive applications and aircraft navigation systems etc. Additionally, the ability of this software to detect potential distorting effects like noise contamination provides additional benefits for controlling dynamic processes that require rapid adjustment rates.
The Importance of Model Predictive Control (MPC) Software
Model Predictive Control (MPC) software is a powerful tool that enables engineers to control complex systems with greater accuracy and reliability than ever before. MPC algorithms are able to predict the behavior of a system based on its current values, allowing for more efficient and accurate control strategies. This type of technology provides an invaluable resource for any industrial setting, as it ensures optimal performance without sacrificing safety or efficiency.
The benefits of MPC software come from its ability to model the behavior and interactions of multiple components in a system simultaneously. By taking into account all the various input and output channels in the system, MPC can accurately anticipate how a certain change will affect the overall performance of the device. The result is improved efficiency, more consistent results and reduced energy costs over time. Moreover, MPC creates opportunities for proactive maintenance practices that can identify potential problem areas before they become too serious or costly to address.
MPC also reduces risk by providing an automated means of predicting how changes will affect performance based on current conditions—i.e., compared to manual systems with hard-coded rules or "rules of thumb" that may not always provide reliable or accurate results due to lack of available data points or outdated assumptions about underlying trends in data sets over time. Thanks to predictive analytics, controllers no longer have to rely solely on their own intuition when making decisions; instead they can use precise calculations generated by sophisticated computer models that continuously update over time as new information becomes available.
Finally, because MPC algorithms are able to adjust themselves according to changing environmental conditions such as temperature or other external factors affecting production rates and quality levels—they are especially useful for companies who require up-to-date recommendations as operations take place in remote locations around the globe where human intervention is either difficult or impossible altogether due to distance/time constraints; this brings yet another layer of added convenience that helps engineers maintain operational consistency regardless of their physical location at any given point in time.
All things considered, Model Predictive Control (MPC) software has revolutionized modern industrial automation processes by allowing companies unprecedented levels of accuracy, precision and control within their day-to-day operations—ultimately delivering cost savings while minimizing risk exposure at every step along the way.
Features Provided by Model Predictive Control (MPC) Software
- Model Predictive Control (MPC) Software provides a “lookahead” feature that allows it to predict future states of the system. This helps to make better decisions based on what is expected in the next few time steps, instead of just relying on the current state.
- MPC software also has an optimization capability that can be used to identify optimal control settings for maximum efficiency or other performance goals. It can take into account any number of constraints such as desired production rates, safety parameters and dynamic conditions like ambient temperatures or wind speeds.
- In addition, MPC software has built-in tracking capabilities which enable it to adjust its parameters over time in order to maintain a steady output from the process or systems being controlled. This ability increases efficiency by reducing unnecessary use of resources and energy.
- The software is also capable of learning from past experiences, allowing for adaptive controls that respond quickly and effectively to changing conditions without having to manually adjust settings each time. This makes it easier for operators who do not need detailed technical knowledge in order to keep their processes running smoothly.
- Finally, most modern MPC packages include visualization tools which allow users to visually monitor their processes quickly and easily. These tools often include real-time display modes so changes can be tracked in near real time as well as historical visualizations so trends over time can be observed conveniently with minimal effort.
Types of Users That Can Benefit From Model Predictive Control (MPC) Software
- Engineers: MPC software gives engineers the ability to closely monitor and regulate systems with minimal energy usage and disruption, allowing them to quickly optimize processes for maximum efficiency.
- Manufacturers: By leveraging predictive modeling capabilities, manufacturers can identify trends in product performance or production issues before they become major problems, reducing costly downtime and improving overall quality assurance.
- Industrial Automation Professionals: By utilizing pre-programmed rules and functions within MPC software, automation professionals can reduce labor costs while increasing safety in production lines as well as realize higher levels of precision control over automated machinery than other traditional controllers.
- Service Providers: With the help of a comprehensive set of data-driven analytics tools built into many types of modern MPC software, service providers are able to reliably monitor and maintain complex industrial systems from remote locations without sacrificing performance accuracy or operational reliability.
- Academics & Researchers: The advanced mathematical algorithms used in model predictive control provide a powerful tool for academic researchers studying complex dynamics, as well as provide an invaluable platform for testing hypotheses about how different models interact with each other in real-world scenarios.
How Much Does Model Predictive Control (MPC) Software Cost?
The cost of model predictive control (MPC) software can vary greatly depending on the complexity of the system and the specific features needed. Generally, open source software is available for free, while commercial packages can range from hundreds to thousands of dollars, depending on the licensing options chosen. For industrial applications, packaged MPC software solutions are often more reliable and comprehensive than custom-coded solutions. Depending on application specifics and infrastructure requirements such as SCADA/DCS systems, advanced process control training may also be required to properly use these tools. In summary, the cost of implementing an MPC solution depends on both hardware/software costs as well as related personnel resources such as consulting or engineering services necessary for successful application development and long-term maintenance.
Risk Associated With Model Predictive Control (MPC) Software
- Malfunction: In the event of a malfunction of the MPC software, it could cause various unintended and unpredictable errors to occur in the system. This can lead to inaccurate outputs or undesirable results which could be potentially hazardous or damaging.
- Security risks: The MPC software is reliant on input from external sources such as sensors and other data streams. If these sources are not adequately protected, sensitive information or malicious code may be introduced into the system, leading to serious security breaches.
- Increased complexity: The complexity of an MPC system can significantly increase when additional components such as feedback loops are integrated into it. This increased complexity introduces potential points of failure which must be identified and managed effectively in order to ensure that the system continues to perform correctly.
- Human Error: While MPC systems offer some level of automation, they still require regular maintenance which must be performed by qualified personnel in order to maintain accuracy and consistency between multiple components. Any human errors during this process can have potentially devastating consequences for the performance of the system.
What Software Does Model Predictive Control (MPC) Software Integrate With?
Model Predictive Control (MPC) software is a type of software that uses predictive models to control the operation of industrial processes. It can be used in a variety of applications, including automation, robotics, process control, and more. In order to get the most out of MPC software, it is often necessary to integrate other types of software with it. Some common types of software that are compatible with MPC include data acquisition and processing systems, data communication modules, simulation packages, graphical user interfaces (GUIs), real-time toolkits, decision support systems, alarm management packages, and optimization algorithms. Additionally, some integration solutions provide access to databases or cloud-based services through which data from various sources can be shared securely between different applications. Ultimately, the combination of these various types of software allows for efficient collaboration between multiple users and helps ensure smooth operation for automated industrial processes.
What Are Some Questions To Ask When Considering Model Predictive Control (MPC) Software?
- What is the total cost of ownership (TCO) for the MPC software?
- Does the software have a user-friendly interface so that our team can easily understand it?
- Are there any existing integrations with other systems or applications that we use in our business environment?
- Does the software include features like real-time data analysis and optimization capabilities?
- How long does it typically take to set up and configure the MPC software?
- Does the vendor provide technical support services and implementation assistance if needed?
- Is there an option to expand or customize the MPC technology for our specific needs?
- Does the vendor offer any training programs or resources for users to help them get started with using the MPC software quickly?