APMonitor

APMonitor is a software package for dynamic simulation, model predictive control, and optimization. It is designed to solve large-scale, algebraic, and differential equation systems. APMonitor employs automatic differentiation (AD) to efficiently compute derivatives required for optimization and sensitivity analysis. The software is available as a server that can be accessed through a variety of interfaces, including Python, MATLAB, and web browsers.

APMonitor's core functionality includes:

• Dynamic Simulation: Solving systems of differential and algebraic equations to predict the behavior of a process over time.
• Model Predictive Control (MPC): Implementing advanced control strategies that use a process model to predict future behavior and optimize control actions.
• Nonlinear Programming (NLP): Solving optimization problems with nonlinear objective functions and constraints.
• Mixed-Integer Programming (MIP): Solving optimization problems that involve both continuous and discrete variables.
• Moving Horizon Estimation (MHE): Estimating unknown process states and parameters based on historical measurements.
• Parameter Estimation: Determining the values of model parameters that best fit experimental data.

APMonitor is used in a variety of applications, including chemical process control, energy systems optimization, and robotics. Its ability to handle complex, nonlinear models makes it suitable for challenging optimization and control problems. The server-based architecture allows for distributed computing and integration with various software platforms.