Non‐Model‐Based Estimation for Velocity and Acceleration by Adaptive Identification Method

Abstract

The design of an ideal differentiator is a difficult and a challenging task. In this paper, we propose two types of differentiators to estimate the time derivative of an output signal. To begin with, a velocity estimator is proposed on the basis of the adaptive identification method and compared with the exact differentiator proposed by Levant. Then, an acceleration estimator is proposed with the nonpassifiable adaptive schemes. Finally, the proposed differentiators are applied to the estimation of the speed and acceleration of the mass-spring system. The simulation results show that the proposed differentiators are robust to additive noises. 

CO2 Uptake Estimation of Crassulacean Acid Metabolism Using Experimental Data

“…The time derivative of Ĵk CO 2 can be estimated using the adaptive velocity estimator proposed by us [11] [12].…”

A Method for Selecting Velocity Filter Cutoff Frequency for Maximizing Impedance Width Performance in Haptic Interfaces

“…Researchers have proposed advanced velocity estimators to overcome the trade-off between time-delay and accuracy in velocity estimates, such as Kalman filters [10], Taylor's series expansion and least-square fit estimators [11], first-order adaptive windowing [9], Levant's differentiator [8], time-stamping [12], [13], position and acceleration based velocity estimation [14], and Luenberger and other nonlinear velocity observers [15], [16], [17], [18], [19], [20]. However, these advanced velocity estimation techniques suffer from constraints such as higher computation time, special hardware requirements, parameter tuning; and on many occasions, the implementation is tedious or not possi-ble within the framework of existing control hardware.…”

Experimental Validation of Adaptive Velocity and Acceleration Estimators with MEMS-Based Inertial Sensors

“…We have recently presented a time-derivative tracker whose update law consists of a signum function and applied to the velocity estimation of unicycle mobile robots [5]. In [7,9], we presented two types of adaptive differentiators to estimate the derivative of an output signal. In the case of the output signal with unknown dynamic structure, a velocity estimator was proposed based on the gradient-type adaptive update law.…”