Advances in Nonlinear Dynamical Systems and Control Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".
Deadline for manuscript submissions: 10 May 2025 | Viewed by 4122
Special Issue Editor
Interests: control; e-learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Surprisingly, after several waves of innovation, which were reflected in the technological basis of automatic control, it can be stated with that the basic structure of the most used control algorithms remains essentially at the level of solutions from the first half of the 20th century. However, the explanation of the reasons themselves is even more surprising; until now, we have not really understood them. Currently, however, development in industrial automation, embedded computers, different programmable devices, or field-programmable analog arrays has created conditions that allow exceeding these traditional technologies that are commonly referred to as PID control. The search for appropriate solutions on the one hand welcomes their innovation; on the other hand, it requires a reliable design using strict mathematical procedures. These can reflect completely new ideas, but also dusting off older inventions, which, at the time of their discovery, were technologically ahead of their time. As one of the possible examples, we could mention constrained controllers with higher-order derivatives proposed using criteria to guarantee the absolute stability of nonlinear systems, but the calculation of such possibilities could be much wider. Meanwhile, the field of application has grown significantly from traditional process control, servo systems, power electronics, or robotics. Let us mention only new solutions from the field of automotive, autonomous vehicles, or renewable energy sources. There are an awful lot of incoming challenges from practice—you just have to get hold of them!
Prof. Dr. Mikulas Huba
Guest Editor
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Keywords
- PID control
- automatic reset
- predictive control
- nonlinear control
- constrained control
- adaptive control
- intelligent control
- optimal control
- filtration
- multilevel optimization
- measurement and quantization noise
- robustness and uncertainties
- set-point and disturbance rejection optimization
- time-delayed systems
- dead-time compensators
- digitalization
- Industry 4.0
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