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Advanced Mathematics and Computational Applications in Control Systems Engineering

Advanced Mathematics and Computational Applications in Control Systems Engineering

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Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering.

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Keywords

  • 3 DOF crane
  • adaptive control
  • adaptive disturbance rejection controller
  • advanced metaheuristics
  • analysis and treatment of signals
  • Bio-inspired Robots
  • Bonferroni–Dunn and Friedman’s tests
  • brushless DC electric motors
  • buck-boost converter
  • Chaos
  • convex systems
  • distillation column heating actuator
  • doubly fed induction generator
  • dynamic resistance model
  • energy savings
  • fault-tolerant control
  • FPGA
  • fractional-order control
  • friction factor
  • fuzzy observer with sliding modes
  • high observers
  • Hybrid systems
  • Intelligent control techniques
  • LCL-filter
  • minor losses
  • n/a
  • neural control
  • nonlinear optimization
  • passive damping
  • PI tuning
  • PID control and variants
  • pipe roughness
  • qLPV systems
  • resistance spot welding
  • river monitoring
  • Robust control
  • sensors and virtual instruments
  • state constraint
  • Streeter–Phelps model
  • Synchronization
  • Takagi–Sugeno model
  • Takagi–Sugeno systems
  • Technology, engineering, agriculture
  • Technology: general issues
  • turbulent flow
  • UDS
  • worm robot

Links

DOI: 10.3390/books978-3-0365-1451-2

Editions

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