Concurrent Learning Based Finite-Time Parameter Estimation in Adaptive Control of Uncertain Switched Nonlinear Systems

Yazdani, Mehdi; Nazari, Saeede; Sinafar, Behzad

doi:10.1007/s40313-017-0318-y

Cited by 7 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…ensures that e i converges to zero exponentially and the estimated parameterŝi converge to the true parameters i . In Equation (22), k CL ∈ R + is the gain and I n x is the identity matrix of dimension n x .…”

Section: Integral Concurrent Learning Adaptive Identificationmentioning

confidence: 99%

“…As presented in Section 4, the sampling matrix Φ i is employed as the ith integrated history stack for the identification of subsystems. For the update law (22), the control gain is k CL = 0.8 once the sampling matrix Φ i is obtained. Before that, the control gain k CL = 0 and the update law without concurrent learning term is adopted.…”

Section: F I G U R Ementioning

confidence: 99%

“…In fact, the approach still offers an offline algorithm in each segmentation and the reduction of the combinatorial complexity is limited. Meanwhile, Goldar et al 22 propose a concurrent learning based identification method for the continuous-time switched nonlinear systems. However, it is not a strictly online identification method due to the assumption that the switching signal is known.…”

Section: Introductionmentioning

confidence: 99%

“…It is worth noticing that most works for the online identification of continuous-time affine hybrid systems are realized via the concurrent learning technique. 20,22,30 The concurrent learning technique can be summarized as using the recorded and current data concurrently for adaption in the framework of model reference adaptive control. The technique is especially promising in the field of online continuous-time affine hybrid systems identification due to providing a continuous adaptation regardless of which subsystem is activated.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A novel recursive approach for online identification of continuous‐time switched nonlinear systems

Liu

Qiu

et al. 2021

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article focuses on the identification of switched nonlinear systems, which are characterized as a collection of nonlinear dynamical systems. Each nonlinear subsystem is activated by a discrete-valued variable (switching signal). Specifically, we consider the continuous-time switched nonlinear systems in the state-space form in our article. The identification of switched nonlinear systems amounts to simultaneous estimation of the switching signal and the nonlinear dynamic subsystems via all measured state-input vectors. However, the problem is challenging and generally requires a large computational complexity to be solved. In this article, we propose a novel online approach to address the identification problem of switched nonlinear systems, which is capable to handle the measured state-input vectors in sequence. In particular, the principle used for estimating the switching signal is developed based on the subspace method. Subsequently, the integral concurrent learning identifier is extended to identify the dynamics of each subsystem recursively. The effectiveness of the proposed identification approach is demonstrated via simulation results.

show abstract

Section: Integral Concurrent Learning Adaptive Identificationmentioning

confidence: 99%

Section: F I G U R Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel recursive approach for online identification of continuous‐time switched nonlinear systems

Liu

Qiu

et al. 2021

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Among these schemes, CL algorithms for time-invariant uncertain switched systems are increasingly used to guarantee that the dynamics of the state tracking error and the weight error exponentially converge to zero. For example, [35] gave a sufficient condition to solve the finite-time parameter estimation problem of uncertain switched systems with arbitrary switching signals. Switched nonlinear systems with linear uncertain parameters were studied in [36], and a class of switching signals was found to ensure the exponential convergence of the state tracking error and weight error.…”

Section: Introductionmentioning

confidence: 99%

Switched Concurrent Learning Adaptive Control of Switched Systems With Nonlinear Matched Uncertainties

Niu

et al. 2020

IEEE Access

View full text Add to dashboard Cite

This paper investigates the model reference adaptive control (MRAC) problem of switched systems with nonlinear matched uncertainties based on mode-dependent average dwell time method. A novel switched MRAC scheme is proposed, which simultaneously uses both current and recorded data from the switched system, to study the convergence of the state tracking error and the weight error without depending on the persistency of excitation. It is critical to establish the relationship among the nonlinear matched uncertainties, the switched concurrent learning(CL) algorithm, the average dwell time of each subsystem, and the convergence domains of the state tracking error and the weight error. First, we find a class of switching signals characterized by mode-dependent average dwell time conditions such that the switched reference model is bounded-input bounded-state stable. Second, in the case of time-invariant nonlinear uncertainties, we design a switched CL adaptive law that ensures that the tracking error converges to zero, and the adaptive weights exponentially converge to their ideal values. Subsequently, in the case of nonlinear time-varying uncertainties, we estimate the convergence rates of the state tracking error and the weight error of each subsystem outside a ball, and thus obtain sufficient conditions that ensure the convergence of the trajectories of the state tracking error and the weight error to a ball centered at the origin with a given radius. Finally, the proposed approach is applied to an electro-hydraulic system, and its effectiveness is demonstrated. INDEX TERMS Switched systems, concurrent learning, mode-dependent average dwell time, model reference adaptive control.

show abstract

Ultimate Boundedness Control for Uncertain Nonlinear Impulsive Switched Systems: A Fuzzy Approach Based on a Complete Takagi–Sugeno Structure

Ghalehnoie

2019

J Control Autom Electr Syst

View full text Add to dashboard Cite

Concurrent Learning Based Finite-Time Parameter Estimation in Adaptive Control of Uncertain Switched Nonlinear Systems

Cited by 7 publications

References 22 publications

A novel recursive approach for online identification of continuous‐time switched nonlinear systems

A novel recursive approach for online identification of continuous‐time switched nonlinear systems

Switched Concurrent Learning Adaptive Control of Switched Systems With Nonlinear Matched Uncertainties

Ultimate Boundedness Control for Uncertain Nonlinear Impulsive Switched Systems: A Fuzzy Approach Based on a Complete Takagi–Sugeno Structure

Contact Info

Product

Resources

About