Murray at 18:23, 9 October 2022

2022-10-09T18:23:53Z

← Older revision		Revision as of 18:23, 9 October 2022
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	{{Paper		{{Paper
	\|Title=The Python Control Systems Library (python-control)		\|Title=The Python Control Systems Library (python-control)
	\|Authors=S Fuller, B Greiner, J Moore, R Murray, R van Paassen, R Yorke		\|Authors=Sawyer Fuller, Ben Greiner, Jason Moore, Richard M. Murray, Renee van Paassen, Rory Yorke
	\|Source=IEEE Conference on Decision and Control (CDC), 2021		\|Source=IEEE Conference on Decision and Control (CDC), 2021
	\|Abstract=The Python Control Systems Library (python-control) is an open source set of Python classes and functions that implement common operations for the analysis and design of feedback control systems. In addition to support for standard LTI control systems (including time and frequency response, block diagram algebra, stability and robustness analysis, and control system synthesis), the package provides support for nonlinear input/output systems, including system interconnection, simulation, and describing function analysis. A MATLAB compatibility layer provides an many of the common functions corresponding to commands available in the MATLAB Control Systems Toolbox. The library takes advantage of the Python “scientific stack” of Numpy, Matplotlib, and Jupyter Notebooks and offers easy interoperation with other category-leading software systems in data science, machine learning, and robotics that have largely been built on Python.		\|Abstract=The Python Control Systems Library (python-control) is an open source set of Python classes and functions that implement common operations for the analysis and design of feedback control systems. In addition to support for standard LTI control systems (including time and frequency response, block diagram algebra, stability and robustness analysis, and control system synthesis), the package provides support for nonlinear input/output systems, including system interconnection, simulation, and describing function analysis. A MATLAB compatibility layer provides an many of the common functions corresponding to commands available in the MATLAB Control Systems Toolbox. The library takes advantage of the Python “scientific stack” of Numpy, Matplotlib, and Jupyter Notebooks and offers easy interoperation with other category-leading software systems in data science, machine learning, and robotics that have largely been built on Python.

Murray: Created page with "{{Paper |Title=The Python Control Systems Library (python-control) |Authors=S Fuller, B Greiner, J Moore, R Murray, R van Paassen, R Yorke |Source=IEEE Conference on Decision and Control (CDC), 2021 |Abstract=The Python Control Systems Library (python-control) is an open source set of Python classes and functions that implement common operations for the analysis and design of feedback control systems. In addition to support for standard LTI control systems (including tim..."

2022-10-09T17:25:07Z

Created page with "{{Paper |Title=The Python Control Systems Library (python-control) |Authors=S Fuller, B Greiner, J Moore, R Murray, R van Paassen, R Yorke |Source=IEEE Conference on Decision and Control (CDC), 2021 |Abstract=The Python Control Systems Library (python-control) is an open source set of Python classes and functions that implement common operations for the analysis and design of feedback control systems. In addition to support for standard LTI control systems (including tim..."

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{{Paper
|Title=The Python Control Systems Library (python-control)
|Authors=S Fuller, B Greiner, J Moore, R Murray, R van Paassen, R Yorke
|Source=IEEE Conference on Decision and Control (CDC), 2021
|Abstract=The Python Control Systems Library (python-control) is an open source set of Python classes and functions that implement common operations for the analysis and design of feedback control systems. In addition to support for standard LTI control systems (including time and frequency response, block diagram algebra, stability and robustness analysis, and control system synthesis), the package provides support for nonlinear input/output systems, including system interconnection, simulation, and describing function analysis. A MATLAB compatibility layer provides an many of the common functions corresponding to commands available in the MATLAB Control Systems Toolbox. The library takes advantage of the Python “scientific stack” of Numpy, Matplotlib, and Jupyter Notebooks and offers easy interoperation with other category-leading software systems in data science, machine learning, and robotics that have largely been built on Python.
|URL=http://cds.caltech.edu/~murray/preprints/ful+21-cdc.pdf
|Type=Conference paper
|ID=2021c
|Tag=ful+21-cdc
}}

The Python Control Systems Library (python-control) - Revision history

Murray at 18:23, 9 October 2022