Dumitru Baleanu, Çankaya University, Ankara, Turkey, and Institute of Space
Science, Romania, e-mail: dumitru@cankaya.edu.tr
Yeliz Karaca, University of Massachusetts Medical School, MA, USA, e-mail:
yeliz.karaca@ieee.org
Yu-Dong Zhang, University of Leicester, Leicester, UK, e-mail: yudongzhang@ieee.org
Praveen Agarwal, Anand International College of Engineering, India, e-mail:
goyal.praveen2011@gmail.com
• Symposium Pulses
Nonlinear dynamic models are characterized by intricate attributes like high dimensionality and heterogeneity, having fractional-order derivatives, and constituting fractional calculus, which brings forth a thorough comprehension and control of the related dynamics and structure. Fractional models have become relevant to dealing with phenomena with memory effects in contrast with traditional models of ordinary and partial differential equations. Compared with integer-order calculus, which constitutes the mathematical basis of most control systems, fractional calculus can provide better equipment to handle the observed time-dependent impacts and generalized memory. Analysis and control of fractional order nonlinear systems are also important, along with the observation of unknown inputs and concepts being used and derived analytically. Multiple nonlinear systems demonstrate phenomena in which fluctuations enhance synchronization and periodic behaviors of the system. Chaos synchronization in systems has the states of complete synchronization and generalized or internal synchronization.
Fractional calculus, through the investigation of fractional-order integral and derivative operators with real or complex domains have merged with the advances in the high-speed and applicable computing technologies; and hence, computational processing analyses, as a method of reasoning and the main pillar of the majority of current research, can be of aid to tackling nonlinear dynamic problems through novel strategies based on observations and complex data. To be able to provide feasible and applicable solutions within the dynamic processes of the nonlinear systems, methods related to analytical, numerical, simulation-related, and computational analyses can be employed by considering the control-theoretic aspects to that associated. Thus, this stance enables to provide a bridge between mathematics and computer science besides other wide range of sciences so that transition from integer to fractional order methods can be ensured. Fractional derivatives and fractional differential equations are used extensively in modeling diverse, dynamic processes in the physical and natural world, which provides aid for the description of dynamic and nonlinear behaviors of nature. All these aspects are important for the optimal prediction solutions, critical decision-making processes, optimization, quantification, multiplicity, controllability, observability, synchronization and stabilization of fractional, neural and computational systems amongst many others.
This sophisticated approach, with the theoretical and applied dimensions of nonlinear dynamic systems merging fractional mathematics and computing technologies to be presented to demonstrate the significance of novel approaches in the related realms have become more prominent in nonlinear dynamic systems, facilitating to achieve viable solutions, optimization processes, numerical simulations besides technical analyses and related applications in areas like mathematics, medicine, neuroscience, engineering, physics, biology, virology, chemistry, genetics, information science, information and communication technologies, informatics, space sciences, applied sciences, finance, and social sciences, to name some. Accordingly, we hope that our symposium will be a platform to pave the way for novel research, fruitful discussions and thought-provoking experiences.
The potential topics of our symposium include but are not limited to:
– Computational methods for dynamical systems of fractional order
– Fractional calculus of variations and optimal control with time-scale
– Data-driven forecasting of high-dimensional chaotic systems
– Data-driven fractional biological modeling
– Data mining with fractional calculus methods
– Synchronization of dynamic systems on time scales
– Fractional hypergeometric functions
– Fractional order observer design for nonlinear systems
– Adaptive tracking control for multiple unknown fractional-order systems
– Nonlinear control for biological diseases
– Fractional dynamic processes in medicine
– Fractional calculus with artificial intelligence applications
– Medical image/signal analyses based on soft computing
– Stabilization of nonlinear and fuzzy systems
– Nonlinear periodicity and synchronization
– Quantization optimization algorithms
– Computational medicine and fractional calculus in nonlinear systems
– Control and dynamics of multi-agent network systems
– Nonlinear integral equations within fractional calculus in nonlinear science
– Signal processing and design for scalar conservation laws
– Deterministic and stochastic fractional differential equations
– Stochastic dynamics of nonlinear dynamic systems
– Fractional calculus with uncertainties and modeling
– Fractional-calculus-based control scheme for dynamical systems with uncertainty
– Computational intelligence-based methodologies and techniques
– Neural computations with fractional calculus
– Fractional calculus with higher dimensionality
– Special functions in fractional calculus context
– Stochastic approaches for synchronization of oscillators
– Cyber-human system modeling and control with fractional-order dynamics