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Within an Industry 4.0 framework, a variety of new considerations are of increasing importance, such as securing processes against cyberattacks on the control systems or utilizing advances in image processing for image-based control. These new technologies impact relationships between process design and control. In this work, we discuss some of these potential relationships, beginning with a discussion of side channel attacks and what they suggest about ways of evaluating plant design and instrumentation selection, along with controller and security schemes, particularly as more data is collected and there is a move toward an industrial Internet of Things. Next, we highlight how the 3D computer graphics software tool set Blender can be utilized to analyze a variety of considerations related to ensuring safety of plant operation and facilitating the design of assemblies with image-based sensing.
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Virtual Test Beds for Image-Based Control Simulations Using Blender
Process systems engineering research often utilizes virtual testbeds consisting of physicsbased process models. As machine learning and image processing become more relevant sensing frameworks for control, it becomes important to address how process systems engineers can research the development of control and analysis frameworks that utilize images of physical processes. One method for achieving this is to develop experimental systems; another is to use software that integrates the visualization of systems, as well as modeling of the physics, such as three-dimensional graphics software. The prior work in our group analyzed image-based control for the small-scale example of level in a tank and hinted at some of its potential extensions, using Blender as the graphics software and programming the physics of the tank level via the Python programming interface. The present work focuses on exploring more practical applications of image-based control. Specifically, in this work, we first utilize Blender to demonstrate how a process like zinc flotation, where images of the froth can play a key role in assessing the quality of the process, can be modeled in graphics software through the integration of visualization and programming of the process physics. Then, we demonstrate the use of Blender for testing image-based controllers applied to two other processes: (1) control of the stochastic motion of a nanorod as a precursor simulation toward image-based control of colloidal self-assembly using a virtual testbed; and (2) controller updates based on environment recognition to modify the controller behavior in the presence of different levels of sunlight to reduce the impacts of environmental disturbances on the controller performance. Throughout, we discuss both the setup used in Blender for these systems, as well as some of the features when utilizing Blender for such simulations, including highlighting cases where non-physical parameters of the graphics software would need to be assumed or tuned to the needs of a given process for the testbed simulation. These studies highlight benefits and limitations of this framework as a testbed for image-based controllers and discuss how it can be used to derive insights on image-based control functionality without the development of an experimental testbed.
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- PAR ID:
- 10543789
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Processes
- Volume:
- 12
- Issue:
- 2
- ISSN:
- 2227-9717
- Page Range / eLocation ID:
- 279
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/pr12020279
