Bernardo A. Hernández Vicente, PhD
 

Contact information

behernandez@udec.cl

Departamento de Ingeniería Mecánica
Facultad de Ingeniería
Universidad de Concepción

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About me
Currently I am an assistant professor at the Mechanical Engineering Department at the University of Concepción, Chile, where I teach modules associated to systems analysis and control systems. I hold a PhD from the Automatic Control and Systems Engineering department at the University of Sheffield, UK (2018). My Doctorate Thesis focused on the design of Model Predicve Control (MPC) based controllers for time-varying, distributed and switching systems.

From November 2019 until January 2020 I was a Research Associate at the University of Sheffield working on the Dreams 4 Cars EU H2020 project, which objective was to create a dream-like simulation suit to help train self-driving agents for ground vehicles. During 2017 I performed as a Research Assistant at the Rolls-Royce university technology centre at the Department of Automatic Control and Systems Engineering at the University of Sheffield. Prior to my PhD I obtained an MEng in Mechanical Engineering (2013) and a BEng in Aerospace Engineering (2012) from the University of Concepcion, Chile. My masters final project focused on the implementation and optimisation of an automatic control platform in a UAV.

My current research interests are in the broad field of model-based control. More particularly in the design of model-based controllers for uncertain and changing systems, where uncertainty may arise from inaccuracies inherent to the modelling process. I am also interested in ground/air vehicle modelling for the purpose of autonomous driving/flying, specially in the design of high and low level controllers for the task of path-planning and path-following.
 
 Publications[*]
  1. B. A. Hernandez Vicente, P. A. Trodden, S. R. Anderson (2023), Fast Tube Model Predictive Control for Driverless Cars Using Linear Data-Driven Models, IEEE Transactions on Control Systems Technology, 31(3), pp. 1395–1410. Link
  2. B. A. Hernandez Vicente, S. S. James, S. R. Anderson (2021), Linear system identification versus physical modeling of lateral-longitudinal vehicle dynamics, IEEE Transactions on Control Systems Technology, 29(3), pp. 1380–1387. Link
  3. B. A. Hernandez Vicente, P. A. Trodden (2019), Stabilizing predictive control with persistence of excitation for constrained linear systems, Systems & Control Letters, 126, pp. 58–66. Link
  4. B. A. Hernandez Vicente, P. A. Trodden (2019), Switching tube-based MPC: Characterization of minimum dwell-time for feasible and robustly stable switching, IEEE Transactions on Automatic Control, 64(10), pp. 4345–4352. Link
  5. P. R. Baldivieso Monasterios, B. A. Hernandez Vicente, P. A. Trodden (2017), Nested distributed MPC, IFAC-PapersOnLine, 50(1), pp. 11822–11828. Link
  6. B. A. Hernandez Vicente, P. R. Baldivieso Monasterios, P. A. Trodden (2017), Distributed MPC: Guaranteeing Global Stability from Locally Designed Tubes, IFAC-PapersOnLine, 50(1), pp. 11829–11834. Link
  7. B. A. Hernandez Vicente, P. A. Trodden (2017), Distributed model predictive control using a chain of tubes, Proceedings of the 2016 UKACC International Conference on Control, pp. 1–6. Link
  8. B. A. Hernandez Vicente, P. A. Trodden (2017), Persistently exciting tube MPC, Proceedings of the 2016 American Control Conference, pp. 948–953. Link


  • 503202/503203 - Programming Language (Python)
  • 541234 - Dynamic Systems Analysis
  • 541236 - Control Systems
  • 541411 - Industrial Electronics
  • 541721 - Continuum Mechanics (MechEng Masters)


  • FONDECYT Iniciaciõn - 2023


  1. RESEARCH AREA: AERONAUTICS AND CONTROL
    1. Topic: Multicopter control test bed design, construction and validation (various PIA and MT).
      Description: Multicopter optimal control is a challenging task due to its fast and multivariable dynamics. The project aims to build a test bed that allows for validating multivariable control techniques on multicopters, allowing for at lest 3 degrees of freedom.
    2. Topic: Variable pitch propeller control (various PIA and MT).
      Description: Variable pitch propellers allows to mainting high propeller efficiency in different stages of flight, however its dynamics are complex due to the interaction with engine. The project aims to test various control techniques both in mathematical models and a real test bed.
    3. Tema: Autonomous pursuit of vehicles (varios PIA y MT).
      Descripción: The project aims to generate and implement algorithms for live image capture of race vehicles from an unmaned aerial platform.

  2. RESEARCH AREA: VEHICLE SIMULATION AND CONTROL
    1. Topic: Design and validation of real RPA in simulation platform (PIA).
      Description: Flight simulator softwares such as X-PLANE have a huge impact in fine tunning various aircraft components. A particularly important one for RPAs is the autopilot, however not many models of RPAs are found in flight simulator data bases. The project aims to design and validate at least one such RPA in a flight simulator.
    2. Topic: Aircraft control simulation with hardware-in-the-loop and software-in-the-loop (various PIA and MT).
      Description: Aircraft optimal control is a challenging task due to its fast and multivariable dynamics. The project aims to test various control techniques making use of flight simulators, both with actual hardware (autopilots) and software (SIMULINK/Python). This will require the generation of dynamic models specific for control purposes.
    3. Topic: Ground vehicle control simulation (various PIA and MT).
      Description: Ground vehicle optimal control is a challenging task due to its fast and multivariable dynamics. The project aims to generate simulation models of vehicle dynamics for posterior testing of control techniques in simulated environment (SIMULINK/Python), for future implementation in a real testing platform.

  3. RESEARCH AREA: CONTROL THEORY
    1. Topic: Bounding prediction error in uncertain LTI systems (PIA/MT).
      Description: LTI representations are used for many control applications, however due to several reasons they are usually affected by prediction error. Conservative bounding guarantees constraint satisfaction but decreases optimality, therefore the project aims to find less conservative bounding approaches in certain specific setups.

  4. RESEARCH AREA: PROPULSION AND CONTROL
    1. No topics currently available, although I remain open for proposals.

  5. RESEARCH AREA: SPACEC AND CONTROL
    1. No topics currently available, although I remain open for proposals.

[*] Feel free to contact me for accessing these publications.


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