Proceedings Article10.1109/IFUZZY.2015.7391900
Composite learning from model reference adaptive fuzzy control
Yongping Pan,Meng Joo Er,Lin Pan,Haoyong Yu +3 more
- 01 Nov 2015
- pp 91-96
9
TL;DR: The proposed model reference composite learning fuzzy control strategy can guarantee accurate function approximation under greatly reduced computational cost and has been verified by applying it to an control problem of aircraft wing rock.
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Abstract: Function approximation accuracy and computational cost are two major issues in approximation-based adaptive fuzzy control. In this paper, a model reference composite learning fuzzy control (MRCLFC) strategy is proposed for a class of affine nonlinear systems with functional uncertainties. In the MRCLFC, a modified modelling error that utilizes data recorded online is defined as the prediction error, a linear filter is applied to estimate the derivatives of plant states, and both the tracking error and the prediction error are exploited to update parametric estimates. It is proven that the closed-loop system achieves semiglobal practical exponential stability by an interval-excitation condition which is much weaker than a persistent-excitation condition. The proposed strategy can guarantee accurate function approximation under greatly reduced computational cost. The effectiveness of the proposed MRCLFC strategy has been verified by applying it to an control problem of aircraft wing rock.
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Citations
Composite Learning From Adaptive Dynamic Surface Control
Yongping Pan,Haoyong Yu +1 more
TL;DR: A novel technique coined composite learning is developed to guarantee parameter convergence without the PE condition, where online recorded data together with instantaneous data are applied to generate prediction errors, and both tracking errors and prediction errors are utilized to update parametric estimates.
273
Model reference composite learning control without persistency of excitation
TL;DR: In this article, a model reference composite learning control strategy was proposed to guarantee parameter convergence without the PE condition, where an integral at a moving-time window is applied to construct a prediction error, an integral transformation is derived for avoiding the time derivation of plant states in the calculation of the prediction error and both the tracking error and the prediction errors are applied to update parametric estimates.
49
Modelling and Experimental Study on Active Energy-Regenerative Suspension Structure with Variable Universe Fuzzy PD Control
TL;DR: In this article, an electromagnetic active suspension with an energy-regenerative structure is proposed to solve the suspension's control consumption problem, and the results demonstrate that the variable universe fuzzy control can recycle more than 18 percent vibration energy and provide over 11 percent power for the control demand.
19
Composite Learning Fuzzy Control of Uncertain Nonlinear Systems
TL;DR: A model reference composite learning fuzzy control strategy is proposed for a class of affine nonlinear systems with functional uncertainties and it is proven that the closed-loop system achieves semiglobal practical exponential stability by an interval-excitation condition which is much weaker than a persistent-excitement condition.
16
Robustness analysis of composite adaptive robot control
Yongping Pan,Tairen Sun,Lin Pan,Haoyong Yu +3 more
- 28 May 2016
TL;DR: In this paper, robustness analysis of CAC for a class of arm-type robots formulated by Euler-Lagrange systems has been conducted and it is shown that CAC is still not robust against bounded perturbations without robust modifications.
9
References
Robust adaptive control
Petros Ioannou,Jing Sun +1 more
- 15 Oct 1995
TL;DR: In this article, the authors present a model for dynamic control systems based on Adaptive Control System Design Steps (ACDS) with Adaptive Observers and Parameter Identifiers.
5.9K
Command Filtered Adaptive Backstepping
TL;DR: This paper proposes a command filtered adaptive backstepping design method, in which analytic calculation of partial derivatives is not required and the control law and the update law become succinct.
760
Composite adaptive control of robot manipulators
Jean-Jacques E. Slotine,W. Li +1 more
TL;DR: A new class of adaptive robot controllers is proposed, the parameter adaptation of which is driven by both tracking error and prediction error, and a detailed analysis of these “composite” adaptive controllers is provided.
652
Adaptive Optimal Control of Unknown Constrained-Input Systems Using Policy Iteration and Neural Networks
TL;DR: This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems where two neural networks are tuned online and simultaneously to generate the optimal bounded control policy.
460
Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation
TL;DR: A new fuzzy controller with the composite parameters adaptive laws are developed and it is proved that all the signals of the closed-loop system are bounded and the system output can follow the given bounded reference signal.
453