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Award ID contains: 2031333

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  1. ; ; ; (, International Journal of Control)
    Real-time numerical differentiation plays a crucial role in many digital control algorithms, such as PID control, which requires numerical differentiation to implement derivative action. This paper proposes an algorithm for estimating the numerical derivative of a signal from noisy sampled data measurements. The method uses adaptive input estimation with adaptive state estimation (AIE/ASE), and thus it requires only minimal prior information about the signal and noise statistics. Furthermore, since the estimates of the derivative at step k provided by AIE/ASE depend only on data available up to step k, AIE/ASE is thus implementable in real time. The accuracy of AIE/ASE is compared numerically to several conventional numerical differentiation methods. Finally, AIE/ASE is applied to simulated vehicle position data, generated in the CarSim simulator software. 
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    Free, publicly-accessible full text available December 1, 2025
  2. (, Proc. Amer. Contr. Conf.)
    Accepted Manuscript Full Text Available
  3. (, Proc. Amer. Contr. Conf.)
    Accepted Manuscript Full Text Available
  4. ; (, IEEE Transactions on Automatic Control)
    null (Ed.)
    Full Text Available