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. For automated driving, you can also use the provided MISRA C®- and ISO 26262-compliant blocks and examples to quickly get started with lane keep assist, path planning, path following, and adaptive cruise control applications. Design implicit, gain-scheduled, and adaptive MPC controllers that solve a quadratic programming (QP) problem. Generate an explicit MPC controller from an implicit design. Use discrete control set MPC for mixed-integer QP problems.
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AVEVA APC
AVEVA APC is model predictive advanced process control that improves your process economics. In today’s economic environment, manufacturers are faced with reduced capital budgets and overhead, rising manufacturing and energy costs, and intense global competition. Comprehensive Advanced Process Control from AVEVA, helps you address complex manufacturing challenges with state-of-the-art automatic control solutions that can extract maximum value from your processes. It can improve production yield and quality and reduce energy consumption. It can help you optimize manufacturing operations and make the performance improvements you need to improve your bottom line continuously. AVEVA APC is a comprehensive model predictive advanced process control software that improves process profitability by enhancing quality, increasing throughput, and reducing energy usage. It uses modern, state-of-the-art technology to provide automatic control systems that are capable of releasing process potential.
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Cybernetica CENIT
Cybernetica delivers Nonlinear Model Predictive Control (NMPC) based on mechanistic models. Our software product, Cybernetica CENIT, offers a flexible architecture that can meet any industrial challenge with optimal solutions. Multivariable optimal control, predictive control, intelligent feed forward, optimal constraint handling. Adaptive control through state and parameter estimation, and feedback from indirect measurements through the process model. Nonlinear models are valid over larger operating ranges. Improved control of nonlinear processes. Less need for step-response experiments and improved state and parameter estimates. Control of batch and semi-batch processes, control of nonlinear processes operated under varying conditions. Optimal grade transition in continuous processes. Safe control of exothermal processes and control of unmeasured variables, such as conversion rates and product quality. Reduced energy consumption and carbon footprint.
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INCA MPC
Advanced Process Control (APC) is a very cost-effective way to optimize your plant performance without changing the hardware. An APC application stabilizes the operation and optimizes production and/or energy consumption. A very valuable side effect also results in a better understanding of your production process. Advanced process control (APC) refers to a broad range of techniques and technologies that interact with the base layer process control systems (built up with PID controls). Some APC technologies are e.g. LQR, LQC, H_infinity, Neural, fuzzy, and MPC (Model-Based Predictive Control). An APC application optimizes your plant every minute, over and over again, 24 hours per day, 7 days per week. MPC is the most popular APC technology used in the industry. The Model Predictive Control software uses a model of the process to predict the behavior of the plant in the foreseeable future. Typically a couple of minutes to even several hours ahead.
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