Advanced Differential Equation Modeling and Control

Research objectives：

This research initiative aims to harness advanced differential equation theory and control methodologies to address critical challenges in sustainable technology development and process innovation. By targeting high‑impact domains such as renewable energy, personalized medicine, smart manufacturing, and environmental protection, the work bridges rigorous mathematical modeling with practical industrial and societal needs. The significance lies in creating predictive, controllable frameworks that reduce resource consumption, minimize emissions, and enhance performance across chemical, biological, materials, and engineering systems. The purpose is to introduce novel techniques—supported by real‑world applications—that enable precise analysis, optimization, and robust control of complex processes, thereby accelerating the transition toward sustainable and intelligent production paradigms. Survey articles within this theme will also chart future directions, fostering interdisciplinary collaboration and inspiring next‑generation research at the interface of mathematics, engineering, and applied sciences.

Subtopics：

1. Nonlinear Dynamics and Control of Energy Conversion Processes for Renewable and LowCarbon Systems​

Focuses on differential equation models capturing the nonlinear behavior of energy generation, storage, and conversion processes (e.g., batteries, fuel cells, hydrogen production) and designs optimal control strategies for efficiency and stability.

2. Mathematical Modeling of Bioprocesses and Pharmacokinetics for Personalized Medicine and Sustainable Biomanufacturing​

Applies ODE/PDE/control theory to model cellular growth, metabolic pathways, drug delivery, and biopharmaceutical production, aiming at scalable, ecofriendly bioprocess control.

3. Intelligent Control and Process Optimization in Smart Manufacturing and Materials Engineering Using Hybrid Differential Equation Frameworks​

Integrates datadriven and physicsbased differential equation models to optimize catalysis, separation processes, particle engineering, and advanced material synthesis in automated, energyefficient manufacturing systems.

Keywords：

• Differential equations
• Control theory
• Process systems
• Renewable energy
• Smart manufacturing
• Bioprocess modeling
• Pharmacokinetics
• Environmental engineering
• Materials science
• Catalysis
• Separation processes
• Particle engineering
• Nonlinear dynamics
• Optimization
• Sustainable development

Expected Outcomes：

Academic: Peer-reviewed articles, collected papers, or monograph