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Active suspension system identification demonstration with various recursive algorithms and susbspace methods

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System Identification of Active Suspension System

This repository contains MATLAB examples to identify the model of an active suspension system using various system identification algorithms. The algorithms included are:

  • Recursive Least Squares
  • Extended Least Squares
  • Output Error Methods
  • Output Error with Filtered Observations
  • Output Error with Adaptive Filtering of the Observations
  • Output Error with Extended Prediction Model
  • Subspace Methods

About the Data

Input and output data are sourced from a physical benchmark system discussed in the following articles:

  • Landau, Silva & Airimitoaie et al. (2013) Benchmark on adaptive regulation—rejection of unknown/time-varying multiple narrow band disturbances, European Journal of Control.
  • Abraham Castellanos Silva, Ioan D. Landau & Luc Dugard et al. (2016) Modified Direct Adaptive Regulation Scheme Applied to a Benchmark Problem, European Journal of Control.
  • Xu Chen & Masayoshi Tomizuka (2013) Selective Model Inversion and Adaptive Disturbance Observer for Time-Varying Vibration Rejection on an Active-Suspension Benchmark, European Journal of Control.

Instructions

  1. Clone this repository.
  2. Run systemID_sec2_blackbox.m and sysID_subspace.m to see results.

Feel free to explore and adapt the provided examples to suit your system identification needs. To customize the methods for your specific needs, modify the data set and transfer function orders based on your unique hardware setup.

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