Mahdi Aliyari Shoorehdeli

TL;DR: Simulation results show that the proposed sliding adaptive fuzzy control method is appropriate to chaos control and it is robust with respect to changes of parameters and the performance is better than the performance of sliding mode controller.

TL;DR: In this article , an intelligent fault detection system using machine learning algorithms for a typical EDF, 72.5 kV, SF6 HVCB with a spring drive mechanism is presented.

TL;DR: A relationship between phase structure of a class of patterns and their moments after and before filtering have been considered and a general formula between the phase structure and moments of the images is obtained.

TL;DR: In this paper, fault detection and isolation (FDI) is shown as a pattern classification problem which can be solved using clustering techniques Gath-Geva clustering (GGC) is exploited as optimal form by a performance assessment rule for fault detection, while multistage Gath Geva (GGG) clustering is employed for the intent of fault isolation Furthermore since Visbreaker unit is a large scale process, a novel hybrid method on the basis of principle component analysis and genetic algorithm optimization was also proposed in order to cope with the curse of dimensionality and complexity

TL;DR: A new combination of nonlinear backstepping scheme with fuzzy system is presented for controlling a rotary inverted pendulum system to achieve better performance in nonlinear controller approach.