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Advances in Artificial Intelligence Methods Applications in Industrial Control Systems
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The motivation for the present reprint is to provide an overview of novel applications of AI methods to industrial control systems by means of selected best practices in highlighting how such methodologies can be used to improve the production systems self-learning capacities, their overall performance, the related process and product quality, the optimal use of resources and the industrial systems safety, and resilience to varying boundary conditions and production requests. By means of its seven scientific contributions, the present reprint illustrates the increasing added value of the introduction of AI methods for improving the performance of control solutions with reference to different control and automation problems in different industrial applications and sectors, ranging from single manipulators or small unmanned ground vehicles up to complex manufacturing. Additionally, the role of AI to improve the performance of relevant engineering methodologies and digital instruments, such as cyberphysical systems, digital twins, and human–robot collaboration, are also effectively addressed in the included contributions.
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Keywords
- adaptive optimal control
- adaptive production systems
- artificial intelligence
- continuous control
- Control systems
- cyber-physical production system
- decentralized control
- Digital twin
- History of engineering & technology
- human robot collaboration
- industrial automation
- Industry 4.0
- interoperability
- irrigation main canal pool automation
- Machine learning
- management of water resources
- manufacturing execution system
- modified SP controller design
- multi-agent
- multi-dimensional Taylor network
- n/a
- NARX-ANN-based models
- nonlinear system
- OPC UA
- policy iteration
- policy optimization
- predictive control
- predictive model
- reconfiguration
- reinforcement learning
- robotic grasping
- Robust control
- self-learning machine tools
- SUGV
- System identification
- Technology, engineering, agriculture
- Technology: general issues
- uncertain nonlinear system
Links
DOI: 10.3390/books978-3-0365-6809-6Editions