Dynamic Modeling and Simulation for Control Systems, 2nd Edition

• Format: eBook
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2024
• Subjects: active power filter (APF); adaptive fuzzy control; analog control circuit; base density of the collected data; consumption; control system architecture-based EtherCAT; DC-DC buck converter; dc-dc converter; deterministic approach; diabetes mellitus (DM); double-star permanent magnet synchronous motor (DSPMSM); dynamic control of diabetic population (DCDP); fast Fourier transform (FFT); fault-detection filter; Fourier vibration spectrum; Fuzzy-CMeans (FCM); Gaussian mixture model (GMM); humanoid; H∞ norm; inflation; inside information; interval type-2 fuzzy neural network (IT2FNN); investment; iterative computation; kernel convolution; life insurance; LMI relaxations; machine learning; Markovian jump linear system; Mathematics and Science; model transformation; monitoring; multi-objective firefly algorithm (MOFA); non-dominated sorting genetic algorithm II (NSGA-II); nonhomogeneous Markov chains; OPAL-RT (OP4510); pole placement; pulse-width modulated; real-time software; Reference, Information and Interdisciplinary subjects; Research and information: general; self-feedback recursive structure; smooth super-twisting extended-state observer (SSTESO); smooth super-twisting sliding-mode control (SSTSMC); state feedback with integral control; stochastic control; stochastic Riccati equations; STSMC; support vector machine; unknown lumped disturbance; wear trend; wind turbine
• ISBN: 3725818142; 9783725818136; 3725818134; 9783725818143
• DOI: 10.3390/books978-3-7258-1814-3

This special issue contains all the articles published in the Special Issue “Dynamic Modeling and Simulation for Control Systems, Second Edition” from the MDPI Mathematics journal. This Special Issue is a follow-up to our first successful edition. It offers researchers and practitioners a platform to explore topics related to the dynamic modeling, simulation, and optimization of control systems in various engineering fields. The aim is to cover vital aspects of optimizing the dynamic behavior of physical systems using algorithms and artificial intelligence. The applications span diverse areas such as astronautics, aerospace, avionics, robotics, manufacturing systems, mechanical engineering, power energy, materials technology, and neurorehabilitation. We hope this Special Issue will make a significant contribution to the research on modeling, simulation, and optimization techniques for dynamic control systems.