Joint estimation of state, parameter, and unknown input for nonlinear systems: A composite estimation scheme

Abstract

This study is concerned with the joint estimation problem for a class of nonlinear systems with the simultaneous unknown of the system state, the parameter, as well as the input signal. A composite estimation scheme is proposed where the estimator consists of both linear and nonlinear components, under which the estimation performance is improved. The analysis and synthesis issues of the developed estimation algorithm are addressed for both the continuous-time case and the discrete-time case. By utilizing the Lyapunov stability theory combined with the singular value decomposition technique, sufficient conditions are established for both continuous-time and discrete-time cases to guarantee the convergence of the estimation error, rather than the boundedness in most of the existing literature. To facilitate the algorithm implementation in practical engineering, the Newton-Raphson method is adopted to deal with the feasibility issue for the discrete-time case. Numerical simulations are provided for both the continuous-and discrete-time cases to demonstrate the effectiveness of the proposed joint estimation strategies.

Fault detection problem for discrete‐time impulsive system using mixed dissipativity approach

“…Finally, a numerical example and a mass-spring system are given to verify the effectiveness of our proposed diagnosis strategy. Moreover, future work will include studies on fault detection/estimate on handling randomly occurring faults, [33][34][35][36] networked based fault detection problem, 37,38 and data based fault detection methods. 39,40…”

An outlier‐resistant approach to observer‐based security control for interval type‐2 T‐S fuzzy systems subject to deception attacks

“…Figure 4 plots the closed‐loop system (24) with outlier‐resistant control and the closed‐loop system without outlier‐resistant observer‐based control (traditional Luenberger observer). Obviously, the outlier‐resistant observer is less volatile and more stable [45–48]. Figure 5 depicts the time instants of successful spoofing offensives with $$\bar{\sigma }=0.38$$.…”

Set membership filtering for discrete saturated time‐varying networked systems with incomplete measurements under round‐robin protocol

“…In the network environment, due to the limited communication channel bandwidth, frequent data exchange and transmission may certainly cause various network-induced phenomena, such as communication delay, signal quantization, and sensor saturation [15][16][17][18]. These network-induced phenomena lead to the system measurement with information incomplete and bring new problems for the filtering research.…”