Lecture: Stability of a non-autonomous reaction-diffusion food chain system with feedback control and time-varying delays
Lecturer: Professor Wang Changyou
Time: 10:00-12:00, Dec. 17th, 2025
Venue: C302B, Minglilou Building
Bio.: Wang Changyou, Ph.D., is a Professor at Chengdu University of Information Technology, serving as a member of the Academic Committee and Teaching Advisory Committee, Chair of the Academic Committee at the Center for Applied Mathematics, and a graduate supervisor. He is a reviewer for Mathematical Reviews, a guest editor for the international SCI journals Mathematics and Axioms, and an expert evaluator for natural science awards and natural science fund projects in Sichuan Province, Chongqing Municipality, Guangxi Zhuang Autonomous Region, and other provincial-level administrative regions. He has published over 150 papers in core journals both home and abroad, including Applied Mathematical Modelling, Applied Mathematics Letters, Journal of Mathematical Analysis and Applications, Physica A-Statistical Mechanics and Its Applications, International Journal of Biomathematics, Advances in Continuous and Discrete Models, and Acta Mathematica Scientia, Series B. His primary research fields include delayed reaction-diffusion equations, biomathematics, fractional-order delayed neural networks, fuzzy differential dynamical systems, and image and video processing.
Abstract: This study develops a novel non-autonomous diffusion-driven food chain model incorporating time-varying delays, feedback control mechanisms, and a Michaelis-Menten functional response to address limitations in traditional ecological models. By integrating spatiotemporal dynamics with realistic biological interactions, we derive rigorous theoretical conditions for the existence and global asymptotic stability of spatially homogeneous periodic solutions using a hybrid analytical framework combining fixed point theory, Lyapunov functionals, and limit approximation methods. The model accounts for environmental fluctuations and delayed responses, revealing critical dependencies of population persistence on diffusion rates, feedback control strengths, and delay structures. Numerical simulations parameterized with empirical data validate these findings, demonstrating delay-induced oscillations, trophic cascade propagation, and feedback-mediated stabilization under environmental stochasticity. Results highlight the model's capacity to predict population resilience in changing environments, offering mechanistic insights for conservation biology, pest management, and ecosystem resilience assessment. This work bridges a gap between theoretical reaction-diffusion systems and complex ecological realities, providing a foundational framework for predicting species responses to climate change and habitat fragmentation while emphasizing the stabilizing role of adaptive feedback in maintaining ecosystem balance.
Organizer and Sponsor：
School of Sciences
Institute of Science and Technology Development
Xindu district of chengdu in sichuan province xindu road no. 8 | 
610500 | 
86-28-83032846 
