Nonlinear Model Predictive Control of Reentry Vehicles Based on Takagi-Sugeno Fuzzy Models

  • Benjamin W. L. MargolisEmail author
  • Mohammad A. Ayoubi
  • Sanjay S. Joshi


In this paper, we apply a discrete-time Takagi-Sugeno Fuzzy Model (TSFM) based model predictive controller (MPC) to a Martian aerocapture vehicle following an arbitrary trajectory. We compare two baseline controllers: a continuous-time TSFM based parallel distributed controller (PDC) and a finite-horizon linear quadratic regulator (LQR). We evaluate the change in velocity (ΔV) required to bring the orbit of the controlled exit conditions to the orbit of the reference trajectory exit conditions over a range of initial condition errors and perturbations to atmospheric density. The LQR controller was least robust but performed best in a smaller range of perturbations. The PDC controller was most robust but performed the worst. The MPC based controllers demonstrate a balance of robustness and performance.


Model predictive control Takagi-Sugeno fuzzy model Tracking control 



This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650042.

Compliance with Ethical Standards

Conflict of interests

On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© American Astronautical Society 2019

Authors and Affiliations

  1. 1.Department of Mechanical and Aerospace EngineeringUniversity of CaliforniaDavisUSA
  2. 2.Department of Mechanical EngineeringSanta Clara UniversitySanta ClaraUSA

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