Neuro-fuzzy-based direct adaptive controller design for a class of uncertain multivariable nonlinear systems

Author(s):  
Wei-Song Lin ◽  
Chun-Sheng Chen
2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Huanqing Wang ◽  
Xiaoping Liu ◽  
Qi Zhou ◽  
Hamid Reza Karimi

The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.


2012 ◽  
Vol 182-183 ◽  
pp. 1260-1264
Author(s):  
Xiao Chun Lou

In this paper, we have discussed the adaptive controller problem for a class of nonlinear discrete systems. Firstly, the general nonlinear discrete-time system is transformed into a new form which is more suitable for adaptive controller design. Based on the new model, the observer is proposed to estimate the unavailable states. The adaptive controller is designed to track the desired trajectory.


Author(s):  
W. X. Deng ◽  
J. Y. Yao

In this paper, a robust adaptive controller is proposed for a class of uncertain nonlinear systems subject to time-varying input delay, parametric uncertainties and additive bounded disturbances. The desired trajectory based adaptive feedforward technique and a predictor-like robust delay compensating term are integrated via backstepping in the controller design. The proposed controller theoretically ensures semi-global uniformly ultimately bounded tracking performance based on Lyapunov stability analysis by employing Lyapunov-Krasovskii (LK) functionals. Simulation results are obtained to illustrate the effectiveness of the proposed control strategy.


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