in industrial robotic manipulator, due to the presence of quite nonlinear dynamic and structural and nonstructural uncertainties, a precise model is not easily obtained. as a result, designing a controller with a suitable function based on system model is a challenging issue. sliding mode control is a robust control with numerous applications which can overcome the aforementioned uncertainties....

Based on the similarity between prevalent fuzzy logic controllers (FLC) and the conventional robust controller, i.e., the variable structure controller, control theoretic analysis of a fuzzy control system is presented in the sense of Lyapunov. As well as the robustness of the fuzzy control system against uncertainties of a controlled process, this analysis gives an account of the relationship ...

This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimat...

In this paper, a new approach is presented to fit arobust fuzzy regression model based on some fuzzy quantities. Inthis approach, we first introduce a new distance between two fuzzynumbers using the kernel function, and then, based on the leastsquares method, the parameters of fuzzy regression model isestimated. The proposed approach has a suitable performance to<b...

Abstract: In this paper hybrid fuzzy model based predictive control (HFMBPC) is addressed, proposed and tested. The proposed hybrid fuzzy convolution model consists of a steady-state fuzzy model and a gain independent impulse response model. The proposed model is tested in model based predictive control of the concentration control in the chemical reactor, manipulating its flow rate. The paper ...