One of the most important challenges in nonlinear, multi-input multi-output (MIMO) and time variant systems (e.g., robot manipulator) is designing a controller with acceptable performance. This paper focused on design a new artificial non linear controller with on line tunable gain applied in the robot manipulator. The sliding mode fuzzy controller (SMFC) was designed as 7 rules Mamdani’s infer...

One of the most important challenges in nonlinear, multi-input multi-output (MIMO) and time variant systems (e.g., robot manipulator) is designing a controller with acceptable performance. This paper focused on design a new artificial non linear controller with on line tunable gain applied in the robot manipulator. The sliding mode fuzzy controller (SMFC) was designed as 7 rules Mamdani’s infer...

Conventional (type-1) fuzzy logic controllers have been commonly used in various power converter applications. Generally, in these controllers, the experience and knowledge of human experts are needed to decide parameters associated with the rule base and membership functions. The rule base and the membership function parameters may often mean different things to different experts. This may cau...

ress as: , Alexa and hosti 013.11.0 Abstract The interval type-2 fuzzy logic controller (IT2-FLC) is able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of a fuzzy logic system (FLS). This paper proposes an interval type-2 fuzzy PD (IT2F-PD) controller for nonlinear inverted pendulum. The proposed controller uses the Mamdani interval type...

Robots are highly nonlinear and chaotic in position control. The present paper mainly presents the position control of PUMA-560 Robot manipulator. Computed torque controller (CTC) is one of the solutions for position control of robot manipulators. The main drawback of controller is that it fails to operate under different dynamic operating conditions. To overcome this difficulty, intelligent co...

We designed a neuro fuzzy control strategy for control of cyclical leg movements of paraplegic subjects. The cyclical leg movements were specified by three ‘swing phase objectives’, characteristic of natural human gait. The neuro fuzzy controller is a combination of a fuzzy logic controller and a neural network, which makes the controller self tuning and adaptive. Two experiments have been perf...

In our day to day life, increasing the number of vehicles like motorcycle, car, bus, van and truck etc. very rapidly. As a result outcome of traffic blocking and enormous problems in metro cities. Due to traffic jamming problem some large issues are found such as pollution, wastage of time, fuel, and accidents. Traffic jamming arises terribly often time switch in the contemporary world that has...

In this paper, a fuzzy adaptive neural-network model-following speed controller for permanent-magnet synchronous motor (PMSM) drives is proposed. The fuzzy neuralnetwork model-following controller (FNNMFC) consist of a proportional plus integral (PI) like-fuzzy controller in addition to an on-line trained neural-network model-following controller (NNMFC). This controller, FNNMFC, combines the m...

A neuro-fuzzy controller was designed and implemented using LabVIEW over a mobile robotic platform. The controller is based on fuzzy clusters, neural networks, and search techniques. Also, wireless communication with Bluetooth protocol was used to communicate the robot with the controller running in LabVIEW, allowing a simple collaborative task that consisted in pick and place objects, through ...

This paper introduces a new friction compensation strategy which utilizes a rule-based fuzzy logic controller whose parameters are self-tuned according to the previous performance of the controller and a friction model in the lowvelocity range. The proposed controller as well as a conventional fuzzy logic controller and a PID controller were simulated and implemented on a 3-axis milling machine...