Download APM Python Library and Example Problems
The latest APM Python libraries are attached below. Functionality has been tested with Python 2.7. Example applications that use the apm.py library are listed further down on this page.
The development roadmap for this and other libraries are detailed in the release notes. The zipped archive contains the APM Python library apm.py and a number of example problems in separate folders. Descriptions of the example problems are provided below.
Example_hs071: Nonlinear Programming with Python
Hock-Schittkowsky Test Suite #71
Example_nlc: Nonlinear Control with Python
Example_tank_mhe/nlc: Nonlinear Estimation and Control with Python
In this case study, a gravity drained tank was operated to generate data. A dynamic model of the process was derived from a material balance. This material balance is displayed below, along with a diagram of the system.
The the unknown parameters c1 and c2 need to be determined. The parameter c1 is the flow into the tank when the valve is fully open. The parameter c2 is the relationship between the volume of water in the tank and the outlet flow. This model is nonlinear because the outlet flow depends on the square root of the liquid volume. Nonlinear estimation is a technique to determine parameters based on the measurements. The script in example_tank_mhe uses the process data and the nonlinear model to determine the optimal parameters c1 and c2.
After an accurate model of the process is obtained, the model can be used in a Nonlinear Control (NLC) application. A PID controller is compared to the NLC response in the folder example_tank_nlc.