N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Automatica (Journal of IFAC)
Iterative weighted least-squares identification and weighted LQG control design
Automatica (Journal of IFAC)
Identification and control—closed-loop issues
Automatica (Journal of IFAC) - Special issue on trends in system identification
Systems & Control Letters
Automatica (Journal of IFAC)
Tuning and Control Loop Performance
Tuning and Control Loop Performance
Brief Paper: On Approximate Model-Reference Control of SISO Discrete-Time Nonlinear Systems
Automatica (Journal of IFAC)
Survey Approximate linearization via feedback - an overview
Automatica (Journal of IFAC)
Correlation-based tuning of decoupling multivariable controllers
Automatica (Journal of IFAC)
Iterative minimization of H2 control performance criteria
Automatica (Journal of IFAC)
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Brief paper: Fixed-order H∞ controller design for nonparametric models by convex optimization
Automatica (Journal of IFAC)
Performing and extending aggressive maneuvers using iterative learning control
Robotics and Autonomous Systems
Short communication: Model free adaptive control with data dropouts
Expert Systems with Applications: An International Journal
Brief paper: Asymptotic statistical analysis for model-based control design strategies
Automatica (Journal of IFAC)
Brief paper: Virtual Reference Feedback Tuning for non-minimum phase plants
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
From experiment design to closed-loop control
Automatica (Journal of IFAC)
Relations between uncertainty structures in identification for robust control
Automatica (Journal of IFAC)
From model-based control to data-driven control: Survey, classification and perspective
Information Sciences: an International Journal
Optimal input design for direct data-driven tuning of model-reference controllers
Automatica (Journal of IFAC)
Hi-index | 22.17 |
This paper considers the problem of designing a controller for an unknown plant based on input/output measurements. The new design method we propose is direct (no model identification of the plant is needed) and can be applied using a single set of data generated by the plant, with no need for specific experiments nor iterations. It is shown that the method searches for the global optimum of the design criterion and that, in the case of restricted complexity controller design, the achieved controller is a good approximation of the restricted complexity global optimal controller. A simulation example shows the effectiveness of the method.