A Review of Nonlinear Control Strategies for Shape and Stress in Structural Engineering

Abstract

Structural engineering plays a pivotal role in ensuring the safety, stability, and longevity of civil infrastructure. As the demand for innovative and efficient structural designs grows, the need for advanced control strategies becomes increasingly apparent. This comprehensive review examines the state-of-the-art nonlinear control strategies for shape and stress in structural engineering. Recognizing the limitations of conventional linear approaches, the chapter systematically explores diverse methodologies such as adaptive control, neural networks, fuzzy logic, and model predictive control. It analyzes their individual and integrated applications in shaping structural form and managing stress levels. The review considers the intricate interplay between shape and stress control strategies, addresses challenges, and proposes future research directions. Case studies and a comparative analysis offer practical insights into the performance and adaptability of these strategies. By emphasizing advances in materials, technologies, and sustainability, this chapter provides a holistic perspective on the evolving landscape of nonlinear control in structural engineering. This synthesis aims to guide researchers and practitioners toward innovative solutions that enhance the safety, resilience, and efficiency of structural systems.