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In this paper, we address the tracking control problems of a robotic system with uncertain dynamics. To cope with the problem of the unknown nonlinear function terms in the system and improve the robustness, adaptive fuzzy logic control is proposed for an approximation of uncertain parameters to achieve the control objectives. Furthermore, both non-constraint and output constraint are considered in...
In this paper, a novel robust nonlinear sliding mode controller for a class of nonlinear system with parameter uncertainty and disturbance is proposed. The controller is designed in a backstepping manner, proportional-integral-derivative(PID) stabilizing signal of the virtual error is introduced in the design procedure. First, according to the backstepping approach, series Lyapunov functions are constructed...
In this paper, a model-free intelligent controller is proposed to control the piezoelectrically actuated system. This control strategy employs the Haar wavelet functional approximation technique (FAT) to establish the unknown function for releasing the model-based requirement of the sliding mode control. In addition, an adaptive fuzzy scheme with online learning ability is introduced to compensate...
Incorporating Nussbaum function gain into adaptive backstepping, this paper develops an adaptive nonlinear robust control scheme for a class of nonlinear strict-feedback systems with completely unknown control coefficient and unknown bounded disturbance. The proposed design method does not require any a priori knowledge of the signs of the unknown control coefficient. A leakage term based on σ-modification...
This paper addresses the design of adaptive controllers for a networked large-scale system subjected to parametric uncertainties. The system in question is assumed to be an interconnection of several subsystems, coupled through physical interconnections and communication networks introduced for the purpose of cooperation. The system-model is assumed to be a large linear time-invariant system with...
The performances of brushless DC motors (BLDCM) will directly restrict the performances of electro-mechanical actuator (EMA). To improve the performances of the BLDCM, a dynamic mathematical model with taking into the problem of parameter variation and nonlinear dynamic friction compensation has been established, a recurrent neural network (RNN) based adaptive back stepping control (RNABC) for BLDCM...
In this paper, an observer-based robust adaptive fuzzy controller is proposed to deal with the output tracking control problem for a class of uncertain single-input single-output (SISO) nonlinear systems with output delay and unmatched uncertainties.Within this scheme, the state observer is applied for estimating all states which are not available for measurement in the system, and then fuzzy logic...
Multiple model adaptive control (MMAC) is a well-established approach for implementing adaptive systems with fast transient response. This paper considers a recently developed MMAC method based on adaptive nonlinear backstepping control where the parameter estimate may be discontinuously reset based on a criterion that requires a negative jump in the associated control Lyapunov function. Particular...
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