Results 51 to 60 of about 39,689 (251)
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Interior-point methods for PDE-constrained optimization [PDF]
, 2013 In applied sciences PDEs model an extensive variety of phenomena. Typically the final goal of simulations is a system which is optimal in a certain sense. For instance optimal control problems identify a control to steer a system towards a desired state.
Huber, Johannes
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Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
Optimal Strategies for Control of COVID-19: A Mathematical Perspective [PDF]
Scientifica, 2020 A deterministic ordinary differential equation model for SARS-CoV-2 is developed and analysed, taking into account the role of exposed, mildly symptomatic, and severely symptomatic persons in the spread of the disease. It is shown that in the absence of infective immigrants, the model has a locally asymptotically stable disease-free equilibrium ...
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Optimal control and robust estimation for ocean wave energy converters [PDF]
, 2013 This thesis deals with the optimal control of wave energy converters and some associated observer design problems. The first part of the thesis will investigate model predictive control of an ocean wave energy converter to maximize extracted power.
Abraham, Edo
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Optimal Control in Linear Sobolev Type Mathematical Models
Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software", 2020 A.A. Zamyshlyaeva1, N.A. Manakova1, O.N. Tsyplenkova1 1South Ural State University, Chelyabinsk, Russian Federation E-mails: zamyshliaevaaa@susu.ru, manakovana@susu.ru, tcyplenkovaon@susu.ru. Алена Александровна Замышляева, доктор физико-математических наук, профессор, кафедра ≪Прикладная математика и программирование≫, Южно- Уральский государственный ...
Zamyshlyaeva, A.A. +2 more
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Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Optimal Control for a Mathematical Model of Nerve Impulse Spreading
Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software", 2015 Summary: The article concerns the matter of existence of an optimal control for the mathematical model set forward by R. Fitzhugh and J. M. Nagumo for modeling of nerve impulse spreading. The model belongs to the group of diffusion-reaction models simulating a wide range of processes such as chemical reactions with diffusion and nerve impulse spreading.
Manakova, N. A., Gavrilova, O. V.
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Mathematical Optimization for Machine Learning
Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete ...
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