Control Systems and Identification

Control Systems and Identification is a research topic within Control and Systems Engineering. Science Explorer counts 44k research works in it since 1950. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers advances in system identification techniques, including parameter estimation for nonlinear models, data-driven control, model-based control, feedback controllers, state estimation for multivariable systems, and the development of recursive algorithms. The papers also discuss model selection approaches and optimal experiment design for system identification.

• System Identification
• Parameter Estimation
• Nonlinear Models
• Data-Driven Control
• Model-Based Control
• Feedback Controllers
• State Estimation
• Multivariable Systems
• Recursive Algorithms
• Model Selection