Robust control for nonlinear systems with uncertain time-varying parameters coupled with non-triangular terms

Oh, Sang-Young; Choi, Ho‐Lim

doi:10.1080/00207721.2020.1716277

Cited by 8 publications

(12 citation statements)

References 20 publications

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“…The unknown input‐delay actually exists due to the processing and transport of information, computation, physical limitations of sensors, etc 1,2,22 When c is known in Assumption 3, the condition () reduces to the same linear growth condition as in References 14,15. Moreover, if the upper bound of

| φ_{i} (t, x, u) |

is free of | u | and c is known, then the condition () reduces to the same one in Reference 5.…”

Section: Problem Statementmentioning

confidence: 99%

“…Remark The considered system () has the some generalized features over the existing results in the following sense: Assumption 1 implies that uncertain parameters

θ_{i} (t)

are bounded and

θ_{i} (t)

can be arbitrarily fast‐varying unlike 16,17,19 because there is no restriction on the time‐varying rates of

θ_{i} (t)

. Note that in practice, uncertain time‐varying parameters often exist such as the time‐varying mass of electromagnetic levitation system 15 due to the movement of passengers, loading of luggage, etc. Assumption 2 means that unknown delay

τ (t)

is only required to be finite and its bound is not known unlike 2,5,6,24 . Moreover,

τ (t)

can be fast‐varying without any restriction on time‐varying rate of the delay such as

\dot{τ} (t) < 1

considered in 8,24,25 .…”

Section: Problem Statementmentioning

confidence: 99%

“…Also, since there are some system parameter uncertainties in the actual system, the perturbed nonlinearity has the unknown growth rate c . From system formulation viewpoint, when

θ_{i} (t) = 1 + θ_{i}

τ (t) = 0

, and c is a known constant, the system () reduces to one in Reference 14. If

τ (t) = 0

and c is a known constant, the system () reduces to one in Reference 15. When

θ_{i} (t) = 1

and

τ (t) = 0

, the system () reduces to one in Reference 23.…”

Section: Problem Statementmentioning

confidence: 99%

“…Meanwhile, uncertain parameters are often encountered in many real systems 12‐16 and they can affect the stability/performance of the controlled systems. In this regard, various control methods for nonlinear systems with uncertain constant parameters have been studied 3,12,14 .…”

Section: Introductionmentioning

confidence: 99%

“…In Reference 3, the problem of global state regulation for time‐delay nonlinear systems with bounded constant parameters is studied. However, uncertain parameters are often time‐varying in practice, for example, the flight aircraft system parameters are time‐varying, 13 the mass of electromagnetic levitation is time‐varying due to the movement of passengers, 15 and the sprung mass of vehicle suspension is slowly varying 16 . Hence, the results of References 3,12,14 are not applicable to nonlinear systems with uncertain time‐varying parameters.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive control of feedforward nonlinear systems with uncertain time‐varying parameters and an unknown time‐varying delay in the input

Choi

2020

Adaptive Control & Signal

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Summary In this paper, we consider a global regulation problem for a class of feedforward nonlinear systems. The key features of our considered system are identified by the presence of uncertain time‐varying parameters associated with main diagonal states and input and an unknown time‐varying delay in the input. Moreover, the growth rates of nonlinearity and the input‐delay are only known to be finite. To solve our considered problem, we give a process to obtain a compact set that contains the allowed time‐varying parameters. Then, we propose an adaptive controller which handles both unknown growth rate of nonlinearity and input‐delay for system regulation. We carry out the rigorous system analysis and show the effectiveness of our proposed control scheme via an application example.

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| φ_{i} (t, x, u) |

is free of | u | and c is known, then the condition () reduces to the same one in Reference 5.…”

Section: Problem Statementmentioning

confidence: 99%

“…Remark The considered system () has the some generalized features over the existing results in the following sense: Assumption 1 implies that uncertain parameters

θ_{i} (t)

are bounded and

θ_{i} (t)

can be arbitrarily fast‐varying unlike 16,17,19 because there is no restriction on the time‐varying rates of

θ_{i} (t)

τ (t)

is only required to be finite and its bound is not known unlike 2,5,6,24 . Moreover,

τ (t)

can be fast‐varying without any restriction on time‐varying rate of the delay such as

\dot{τ} (t) < 1

considered in 8,24,25 .…”

Section: Problem Statementmentioning

confidence: 99%

“…Also, since there are some system parameter uncertainties in the actual system, the perturbed nonlinearity has the unknown growth rate c . From system formulation viewpoint, when

θ_{i} (t) = 1 + θ_{i}

τ (t) = 0

, and c is a known constant, the system () reduces to one in Reference 14. If

τ (t) = 0

and c is a known constant, the system () reduces to one in Reference 15. When

θ_{i} (t) = 1

and

τ (t) = 0

, the system () reduces to one in Reference 23.…”

Section: Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive control of feedforward nonlinear systems with uncertain time‐varying parameters and an unknown time‐varying delay in the input

Choi

2020

Adaptive Control & Signal

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Adaptive event‐triggered control for strict‐feedback systems With time‐varying parameters

Tan,

Wu,

Liu

2023

Intl J Robust & Nonlinear

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In this article, we develop a new adaptive event‐triggered asymptotic control scheme for strict‐feedback systems with fast time‐varying parameters. To deal with time‐varying parameters with unknown variation boundaries in the feedback path and the input path, we construct three adaptive laws for parameter estimation, two for the uncertain parameters in the feedback path and one for the uncertain parameters in the input path. In particular, two sets of tuning functions are introduced to avoid over‐parametrization. Additionally, an event‐triggering mechanism is embedded in this adaptive control framework to reduce the data transmission from the controller to the actuator. We also introduce a soft sign function to handle the perturbations caused by sampling errors to achieve asymptotic stability and avoid the so‐called parameter drift. The stability analysis shows that the closed‐loop system is globally uniformly asymptotically stable and the Zeno behavior can be excluded. Simulation results verify the effectiveness and performance of the proposed adaptive scheme.

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Improved Controller Design with Two Gain-scaling Factors for Global Asymptotic Stabilization of Nonlinear Systems via Matrix Inequality Approach

Choi

2021

Int. J. Control Autom. Syst.

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Robust control for nonlinear systems with uncertain time-varying parameters coupled with non-triangular terms

Cited by 8 publications

References 20 publications

Adaptive control of feedforward nonlinear systems with uncertain time‐varying parameters and an unknown time‐varying delay in the input

Adaptive control of feedforward nonlinear systems with uncertain time‐varying parameters and an unknown time‐varying delay in the input

Adaptive event‐triggered control for strict‐feedback systems With time‐varying parameters

Improved Controller Design with Two Gain-scaling Factors for Global Asymptotic Stabilization of Nonlinear Systems via Matrix Inequality Approach

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