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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.

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

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The Special Issue "Computational Intelligence Application in Electrical Engineering" deals with the application of computational intelligence techniques in various areas of electrical engineering. The topics of computational intelligence applications in smart power grid optimization, power distribution system protection, and electrical machine design and control optimization are presented in the Special Issue. The co-simulation approach to metaheuristic optimization methods and simulation tools for a power system analysis are also presented. The main computational intelligence techniques, evolutionary optimization, fuzzy inference system, and an artificial neural network are used in the research presented in the Special Issue. The articles published in this issue present the recent trends in computational intelligence applications in the areas of electrical engineering.

Technology: general issues --- History of engineering & technology --- active distribution network --- computational intelligence --- optimization algorithms --- optimal distribution system management --- optimal Smart Grid management --- advanced distribution system optimization --- renewable distributed generation --- Smart Grid optimization --- co-simulation --- computational intelligence techniques --- distributed generation --- optimal allocation and control --- power system protection --- overcurrent relays --- protection relays --- metaheuristic --- school-based optimizer --- electric markets --- photovoltaic generation --- Monte Carlo simulations --- power flow --- S-iteration process --- Newton–Raphson --- high order newton-like method --- computational efficiency --- line-start synchronous motor --- efficiency factor --- power factor --- optometric analysis --- transient models --- induction machine --- ant colony optimization --- predictive current control --- fuzzy logic control --- Takagi–Sugeno --- n/a --- Newton-Raphson --- Takagi-Sugeno

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Coastal ecosystems are dynamic, complex, and often fragile transition environments between land and oceans. They are exclusive habitats for a broad range of living organisms, functioning as havens for biodiversity and providing several important ecological services that link terrestrial, freshwater, and marine environments. Humans living in coastal zones have been strongly dependent on these ecosystems as a source of food, physical protection against storms and advancing sea, and a range of human activities that generate economic income. Notwithstanding, the intensification of human activities in coastal areas of the recent decades, as well as the global climatic changes and coastal erosion processes of the present, have had detrimental impacts on these environments. Maintaining the structural and functional integrity of these environments and recovering an ecological balance or mitigating disturbances in systems under the influence of such stressors are complex tasks, only possible through the implementation of monitoring programs and by assessing their environmental quality. In this book, distinct approaches to environmental quality monitoring and assessment of coastal environments are presented, focused on abiotic and biotic compartments, and using tools that range from ecological levels of organization to the sub-organismal and the ecosystem levels.

Research & information: general --- Environmental economics --- radioactive materials --- trace metals --- bioaccumulation --- marine fish --- crustaceans --- marine environmental pollution --- Bay of Bengal --- beach litter --- infrared thermography --- UAV --- UGV --- environmental monitoring --- coastal pollution --- fuzzy modelling --- marine sediment --- Takagi–Sugeno --- ordinary kriging (OK) --- inverse distance weighting (IDW) --- spatial predictions --- endocrine disruptors --- Mugil cephalus --- PFNA --- ecosystem services --- benefit transfer --- meta-analysis --- meta-regression function --- radioactive materials --- trace metals --- bioaccumulation --- marine fish --- crustaceans --- marine environmental pollution --- Bay of Bengal --- beach litter --- infrared thermography --- UAV --- UGV --- environmental monitoring --- coastal pollution --- fuzzy modelling --- marine sediment --- Takagi–Sugeno --- ordinary kriging (OK) --- inverse distance weighting (IDW) --- spatial predictions --- endocrine disruptors --- Mugil cephalus --- PFNA --- ecosystem services --- benefit transfer --- meta-analysis --- meta-regression function

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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.

Technology: general issues --- doubly fed induction generator --- PI tuning --- LCL-filter --- passive damping --- advanced metaheuristics --- Bonferroni-Dunn and Friedman's tests --- resistance spot welding --- dynamic resistance model --- adaptive control --- energy savings --- adaptive disturbance rejection controller --- hybrid systems --- state constraint --- worm robot --- bio-inspired robots --- Streeter-Phelps model --- fractional-order control --- high observers --- river monitoring --- 3 DOF crane --- convex systems --- fault-tolerant control --- robust control --- qLPV systems --- Takagi-Sugeno systems --- chaos --- synchronization --- FPGA --- UDS --- distillation column heating actuator --- Buck-Boost converter --- Takagi-Sugeno model --- fuzzy observer with sliding modes --- nonlinear optimization --- turbulent flow --- friction factor --- pipe roughness --- minor losses --- PID control and variants --- Intelligent control techniques --- neural control --- brushless DC electric motors --- sensors and virtual instruments --- analysis and treatment of signals --- doubly fed induction generator --- PI tuning --- LCL-filter --- passive damping --- advanced metaheuristics --- Bonferroni-Dunn and Friedman's tests --- resistance spot welding --- dynamic resistance model --- adaptive control --- energy savings --- adaptive disturbance rejection controller --- hybrid systems --- state constraint --- worm robot --- bio-inspired robots --- Streeter-Phelps model --- fractional-order control --- high observers --- river monitoring --- 3 DOF crane --- convex systems --- fault-tolerant control --- robust control --- qLPV systems --- Takagi-Sugeno systems --- chaos --- synchronization --- FPGA --- UDS --- distillation column heating actuator --- Buck-Boost converter --- Takagi-Sugeno model --- fuzzy observer with sliding modes --- nonlinear optimization --- turbulent flow --- friction factor --- pipe roughness --- minor losses --- PID control and variants --- Intelligent control techniques --- neural control --- brushless DC electric motors --- sensors and virtual instruments --- analysis and treatment of signals

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• Reference Manager
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The Special Issue "Computational Intelligence Application in Electrical Engineering" deals with the application of computational intelligence techniques in various areas of electrical engineering. The topics of computational intelligence applications in smart power grid optimization, power distribution system protection, and electrical machine design and control optimization are presented in the Special Issue. The co-simulation approach to metaheuristic optimization methods and simulation tools for a power system analysis are also presented. The main computational intelligence techniques, evolutionary optimization, fuzzy inference system, and an artificial neural network are used in the research presented in the Special Issue. The articles published in this issue present the recent trends in computational intelligence applications in the areas of electrical engineering.

Technology: general issues --- History of engineering & technology --- active distribution network --- computational intelligence --- optimization algorithms --- optimal distribution system management --- optimal Smart Grid management --- advanced distribution system optimization --- renewable distributed generation --- Smart Grid optimization --- co-simulation --- computational intelligence techniques --- distributed generation --- optimal allocation and control --- power system protection --- overcurrent relays --- protection relays --- metaheuristic --- school-based optimizer --- electric markets --- photovoltaic generation --- Monte Carlo simulations --- power flow --- S-iteration process --- Newton-Raphson --- high order newton-like method --- computational efficiency --- line-start synchronous motor --- efficiency factor --- power factor --- optometric analysis --- transient models --- induction machine --- ant colony optimization --- predictive current control --- fuzzy logic control --- Takagi-Sugeno --- active distribution network --- computational intelligence --- optimization algorithms --- optimal distribution system management --- optimal Smart Grid management --- advanced distribution system optimization --- renewable distributed generation --- Smart Grid optimization --- co-simulation --- computational intelligence techniques --- distributed generation --- optimal allocation and control --- power system protection --- overcurrent relays --- protection relays --- metaheuristic --- school-based optimizer --- electric markets --- photovoltaic generation --- Monte Carlo simulations --- power flow --- S-iteration process --- Newton-Raphson --- high order newton-like method --- computational efficiency --- line-start synchronous motor --- efficiency factor --- power factor --- optometric analysis --- transient models --- induction machine --- ant colony optimization --- predictive current control --- fuzzy logic control --- Takagi-Sugeno