Automatic Systems Laboratory

Its main objective is to allow modeling, identification and control of processes and dynamic systems, both locally and remotely, including sensors, actuators and communication systems for control and supervision.

The laboratory is implemented for teaching purposes attending undergraduate and graduate courses. It also allows to carry out research in advanced automatic control.

• System of interconnected (conical and parallelepipedic) ponds that allows the implementation of nonlinear system identification, fuzzy and neural control experiments.
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  Motor-generator system based on direct current (DC) machines, which allows the implementation of classical linear control experiences.
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  Twin-rotor” system allows emulating helicopter dynamics, facilitating the development of adaptive control and anomaly detection experiences.
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  PLC (programmable logic controller) system.
  Delta-V” distributed control system.

• FONDECYT Project 1110070: “Risk-Sensitive Particle Filtering Framework for Failure Prognosis and uncertainty Representation in Nonlinear Systems with High-Impact/Low-Likelihood Events”. PI: Marcos Orchard (U.Ch). Faculty of Mathematics and Physical Sciences.
• Department of Electrical Engineering. University of Chile (2011-2013).
  Innova-Chile CORFO Project 11IDL1-10409: “Model-Based Probabilistic Approach for Online State-of-Health/State-of-Charge Estimation and Characterization of Lithium-Ion Battery Usage Profile” PI: Marcos Orchard (U.Ch.). Faculty of Mathematics and Physical Sciences. Department of Electrical Engineering.
• University of Chile (2012).
  “Real-time estimation and prediction module for state-of-health (SOH) and state-of-charge (SOC) of lithium-ion batteries”. PI: Marcos Orchard (U.Ch.). Lithium Innovation Center (Energy Center). Department of Electrical Engineering, Faculty of Physical and Mathematical Sciences, University of Chile (03/2012 – 09/2012).
• FONDECYT Project 11070022: “Sequential Monte Carlo Methods and Feedback Concepts Applied to Fault Diagnosis and Failure Prognosis in Nonlinear, Non-Gaussian Dynamic Systems”. PI: Marcos Orchard (U.Ch). Faculty of Mathematics and Physical Sciences. Department of Electrical Engineering. University of Chile (2007-2009).