Design and Simulation of a Model Predictive Controller (MPC) for a Seismic Uniaxial Shake Table

Royce Val C. Malalis, Chyn Ira C. Crisostomo, Romel S. Saysay, Alexander C. Abad, Lessandro Estelito O. Garciano, Renann G. Baldovino


Shake table is one of the apparatus that aids in researches to generate techniques, structural developments, and strategies to prevent, prepare, and minimize an earthquake’s devastating effects. One important factor that should be considered in a shake table is the system dynamics due to control-structural interactions, which could either be linear or non-linear. To accurately model both has always been the challenge but becomes more plausible with the availability of faster hardware and computers and the continuous decrease in latency. Model Predictive Controller (MPC) is a type of controller extensively used in the industry that can be used on linear and non-linear systems. This study presents the design and simulation of an MPC for a uniaxial shake table intending to analyze the system’s behavior and accuracy. MATLAB Simulink was utilized to handle the simulation analysis of the controller. Different MPC parameters such as sample time, prediction horizon, control horizon, and closed-loop performance were manipulated and adjusted to observe their effects on the output of the system. A signal that mimics the actual earthquake data was inputted into the controller, and the system's behavior and outputs were measured and presented through graphical representations. To determine the accuracy of the system’s output, its relationship with the reference signal was compared. From the simulation produced, the system demonstrated high accuracy levels and could be adjusted depending on the set performance aggressiveness of the system.


predictive controller model; uniaxial shake table; MATLAB Simulink.

Full Text:



PHIVOLCS, "Introduction to Earthquake," DOST, 2019. [Online]. Available:

USGS, "Ring of Fire," 2019. [Online]. Available:

K. Hickok, "Tons of Major Quakes Have Rattled the World Recently. Does That Mean Anything?," Live Science, 2018. [Online]. Available:

PHIVOLCS, "Earthquake Information," DOST, 2019. [Online]. Available:

PHIVOLCS, "PHIVOLCS Earthquake Intensity Scale (PEIS)," DOST, 2019. [Online]. Available:

Rappler, "MAP: Strongest earthquakes in the Philippines," Rappler, 2015. [Online]. Available:

R. Baldovino and E. Dadios, "Design and Development of a Fuzzy-PLC for an Earthquake Simulator / Shake Table," 7th IEEE International Conference Humanoid, Nanotechnology, Information Technology Communication and Control, Environment and Management (HNICEM), pp. 1 - 6, 2014.

ASTM, "New Building & Construction Standards," ASTM International, 2019. [Online]. Available:

R. Langari, "Past, present and future of fuzzy control: a case for application of fuzzy logic in hierarchical control," Fuzzy Information Processing Society, 18th International Conference of the North American Source, pp. 760-765, 1999.

M. Ulusoy, "Understanding Model Predictive Control, Part 1: Why Use MPC?," MathWorks, 2019. [Online]. Available:

M. Ulusoy, "Understanding Model Predictive Control, Part 2: What Is MPC?," MathWorks, 2019. [Online]. Available:

MathWorks, "Understanding Model Predictive Control," MathWorks, Inc., [Online]. Available:

S. Brunton, "Model Predictive Control," Youtube, 2018. [Online]. Available:

M. Ulusoy, "Understanding Model Predictive Control, Part 6: How to Design an MPC Controller with Simulink and Model Predictive Control Toolbox," MathWorks, 2019. [Online]. Available:

M. Ulusoy, "Understanding Model Predictive Control, Part 3: MPC Design Parameters," MathWorks, 2019. [Online]. Available:



  • There are currently no refbacks.

Published by INSIGHT - Indonesian Society for Knowledge and Human Development