Interval type-2 fuzzy system block diagram. حسب Seung-Min Ryu (21463891)

الموضوعات:

Fuzzy rules of interval type-2. حسب Seung-Min Ryu (21463891)

الموضوعات:

Region of interest and light segmentation in the image. حسب Seung-Min Ryu (21463891)

الموضوعات:

Detailed view of Fig 1(c). حسب Seung-Min Ryu (21463891)

الموضوعات:

Interval type-2 membership function for speed. حسب Seung-Min Ryu (21463891)

الموضوعات:

The five layers of the adaptive neuro–fuzzy inference system. حسب Seung-Min Ryu (21463891)

الموضوعات:

Output of the vehicle system: a) speed measurement, b) distance measurement. حسب Seung-Min Ryu (21463891)

الموضوعات:

Vehicle system with disturbances. حسب Seung-Min Ryu (21463891)

الموضوعات:

Image values by distance. حسب Seung-Min Ryu (21463891)

الموضوعات:

Type-1 membership function for distance. حسب Seung-Min Ryu (21463891)

الموضوعات:

Interval type-2 membership function for distance. حسب Seung-Min Ryu (21463891)

الموضوعات:

Membership functions for distance generated by the adaptive neuro–fuzzy inference system. حسب Seung-Min Ryu (21463891)

الموضوعات:

Output of the vehicle system for the 41–43 m section: a) speed measurement, b) distance measurement. حسب Seung-Min Ryu (21463891)

الموضوعات:

Type-1 membership function for speed. حسب Seung-Min Ryu (21463891)

الموضوعات:

Vehicle dynamics model parameters. حسب Seung-Min Ryu (21463891)

الموضوعات:

Membership functions for speed generated by the adaptive neuro–fuzzy inference system. حسب Seung-Min Ryu (21463891)

الموضوعات:

Overall system block diagram. حسب Seung-Min Ryu (21463891)

الموضوعات:

Longitudinal dynamics model of the vehicle. حسب Seung-Min Ryu (21463891)

الموضوعات:

Membership functions for speed and distance in the 47–49 m section. حسب Seung-Min Ryu (21463891)

الموضوعات:

Proposed PI controller for sensorless BLDC motor. حسب Fizza Shafique (19996292)

"…BLDC motor is a complex system having nonlinearity in its dynamic responses which makes primary controllers in efficient. Therefore, this paper implements metaheuristic optimization techniques such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Accelerated Particle Swarm Optimization (APSO), Levy Flight Trajectory-Based Whale Optimization Algorithm (LFWOA); moreover, a chaotic map and weight factor are also being applied to modify LFWOA (i.e., CMLFWOA) for optimizing the PI controller to control the speed of BLDC motor. …"