Online parameter estimation and adaptive control with limited information in structures

Abstract

An online parameter estimation is important along with the adaptive control, that is, a time-dependent plant. This study uses both online identification and the simple adaptive control algorithm with velocity feedback. The recursive least squares method was used to identify the stiffness and damping parameters of the structure’s stories. Identification was carried out online without initial estimation and only by measuring the structural responses. The limited information regarding sensor measurements, parameter convergence, and the effects of the covariance matrix is examined. The integration of the applied online identification, the appropriate reference model selection in simple adaptive control, and adopting the proportional integral filter was used to limit the structural control response error. Some numerical examples are simulated to verify the ability of the proposed approach. Despite the limited information, the results show that the simultaneous use of online identification with the recursive least squares method and simple adaptive control algorithm improved the overall structural performance.

Adaptive Multi-Parameter Estimation of Inertial Stabilization Platform with Unknown Load

“…In Figure 3, According to Figure 3, we put forward a method to accurately capture 1 t and 2 t , which are shown in Equations ( 20) and ( 21), respectively. According to Figure 3, we put forward a method to accurately capture t 1 and t 2 , which are shown in Equations ( 20) and (21), respectively.…”

“…For the problem of online frequency domain identification of mechanical systems with variable dynamic characteristics, Nevaranta [20] proposed a closed-loop frequency domain online identification algorithm based on sliding discrete Fourier transform on selected frequency groups and the simulation and test results show that the algorithm can obtain satisfactory real-time frequency response estimation in short data using sliding windows. Amini [21] presented the simultaneous integration of online estimation of structural parameters with adaptive control to reduce structural vibrations, in which the stiffness and damping online identification were carried out by the RLS method without initial estimation and only by measuring the structural responses. To solve the problem of simultaneous state estimation and parameter identification for a class of nonlinear systems, Alvaro-Mendoza [22] designed an adaptive observer based on the sliding mode method, whose main advantages are that it combines the robustness and finite-time convergence of the sliding mode observer, as well as the simple tuning of the high-gain observer, reducing the tuning effort.…”