Performance Improvement in Adaptive Control of Linearly Parameterized Nonlinear Systems $ $

Adetola, Veronica; Guay, Martin

doi:10.1109/tac.2010.2052149

Cited by 80 publications

(106 citation statements)

References 13 publications

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“…In this paper, Lemma 2 provides a numerically feasible and intuitive way to online verify the required condition for the convergence, that is, by calculating the minimum eigenvalue of matrix M to test for λ min (M ) > σ > 0. A standard method to fulfil this condition is to add appropriate dither noises into the system [21][22][23][24]. However, a trade-off between the excitation level and the convergence performance should be considered, that is, the noises should fulfil the PE condition but cannot be too large.…”

Section: Remarkmentioning

confidence: 99%

“…This can be achieved by introducing appropriate dither signals into the system (e.g. regressor vector φ) as [16,21,23]. With this regard, Lemma 2 provides a numerically method to facilitate the design of dither signals, that is, by calculating the minimum eigenvalue of matrix M to test if the condition λ min (M ) > 0 is true.…”

Section: Implementations and Comparisonsmentioning

confidence: 99%

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Adaptive estimation of road gradient and vehicle parameters for vehicular systems

Yang

Guo

2015

IET Control Theory & Applications

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To improve the vehicle driving performance, adaptive parameter estimation is studied to simultaneously estimate the road gradient, vehicle mass and other vehicle parameters, which requires the vehicle longitudinal velocity and driving force only. Different to conventional gradient and recursive least square methods, the parameter estimation error is obtained to drive the adaptive laws for estimating unknown parameters, where exponential convergence can be guaranteed under the classical persistently excitation condition. Moreover, finite-time parameter estimation is achieved by incorporating the sliding mode technique into the adaptive laws. The robustness of the proposed adaptations against bounded disturbances is studied. Simulation results illustrate that the presented methods can obtain faster transient and better steady-state performance than some available methods.

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Section: Remarkmentioning

confidence: 99%

Section: Implementations and Comparisonsmentioning

confidence: 99%

Adaptive estimation of road gradient and vehicle parameters for vehicular systems

Yang

Guo

2015

IET Control Theory & Applications

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“…Recently, an alternative adaptive scheme has been proposed to address the parameter estimation problem, where the information of parameter error (the error between the unknown parameters and its estimated values) is explicated obtained and used to drive the adaptive laws [6]. In particular, in our previous work [7][8][9], several novel direct estimation schemes are proposed by introducing novel filter operations, so that the unstable integrator and the online calculation of a matrix inverse in [6] are all avoided.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, in our previous work [7][8][9], several novel direct estimation schemes are proposed by introducing novel filter operations, so that the unstable integrator and the online calculation of a matrix inverse in [6] are all avoided. Moreover, exponential and/or finite-time error convergence are retained under a verify excitation condition.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Control for Robotic Systems with Guaranteed Parameter Estimation

Jing

Gao

et al. 2015

Lecture Notes in Electrical Engineering

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Abstract. In most adaptive control systems with unknown parameters, the adaptive laws are usually designed based on the predictor/observer error or control error. In this paper, we propose a novel adaptive control scheme for nonlinear robotic systems by incorporating the parameter error into the adaptive law, which leads to guaranteed estimation performance. By carrying out filter operations, the robotic system can be linearly parameterized without using the measurements of acceleration. Then a new adaptive algorithm is introduced to guarantee that the parameter error and control error exponentially converge to zero. In particular, we provide an intuitive method to online verify the standard PE condition used for the parameter estimation. The robustness against disturbances is also studied and appropriate comparisons to several adaptive laws are provided. Simulations with a realistic robot arm are presented to validate the improved performance.

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“…This paper treats the problem of constrained control of nonlinear systems subject to parametric uncertainties. The approach proposed combines the adaptive compensator design presented in [1], an uncertain set estimation recently proposed in [2] (as well as in [3] in the context of model predictive control) and a constrained control approach [5]. The adaptive controller with compensator provides exponential convergence of the parameter estimation error when a sufficiently rich tracking signal is considered.…”

Section: Introductionmentioning

confidence: 99%

Adaptive control of state constrained nonlinear systems in strict feedback form

Guay

Bürger

2012

2012 American Control Conference (ACC)

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In this paper, we propose a systematic approach for the constructive design of adaptive control systems for nonlinear uncertain systems subject to state constraints. The analysis is restricted to a class of nonlinear systems in strict feedback form with respect to the state constraints. A novel adaptive estimation routine is employed to estimate both the unknown parameters and an approximate uncertainty sets, which is decreasing over time. The approximate uncertainty set is utilized to define a sequence of robustly controlled invariant sets which are strictly contained in the feasible set.

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Performance Improvement in Adaptive Control of Linearly Parameterized Nonlinear Systems $ $

Cited by 80 publications

References 13 publications

Adaptive estimation of road gradient and vehicle parameters for vehicular systems

Adaptive estimation of road gradient and vehicle parameters for vehicular systems

Robust Adaptive Control for Robotic Systems with Guaranteed Parameter Estimation

Adaptive control of state constrained nonlinear systems in strict feedback form

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