Fuzzy adaptive sliding mode control method is a good way to resolve the control problem when the system mathematic model is unknown. However, reaching condition must be satisfied in this method. In this paper, a kind of fuzzy adaptive variable structure control method is presented in which sliding mode doesn’t exist in closed-loop system. Dynamic fuzzy logical system (DFLS) is introduced to for...

An innovative adaptive control method for speed control of induction motor based on field oriented control is presented in this paper. The fusion of sliding-mode and type-2 neuro fuzzy systems is used to control this system. An online learning algorithm based on sliding-mode training algorithm, and type-2 fuzzy systems is employed to deal with parametric uncertainties and disturbances, by adjus...

Due to computational burden and dynamic uncertainty, the classical model-based control approaches are hard to be implemented in the multivariable robotic systems. In this paper, a model-free fuzzy sliding mode control based on neural network is proposed. In classical sliding mode controllers, system dynamics and system parameters are required to compute the equivalent control. In Radial Basis F...

The main purpose of this paper is to integrate fuzzy logic control and sliding mode control techniques based on backstepping approach to develop a robust fuzzy backstepping sliding mode controller (RFBSMC) for an under-actuated quadrotor UAV system under external disturbances and parameter uncertainties. First, a robust backstepping sliding mode control for quadrotor is introduced briefly. More...

A method of sliding mode control based on a fuzzy model identified through input output data is presented. In this approach the advantages of the sliding mode control technique are maintained, however parametric uncertainty and unmatched disturbance are acknowledged as limiting factors of controller performance and their effects are sought to be minirnised. Controller performance is compared wi...

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...

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

In this paper a systematic fuzzy sliding mode controller is presented for permanent magnet synchronous motor (PMSM) sensorless drives. The fuzzy sliding mode controller is designed based on input–output feedback linearization control technique. The extended Kalman filter is used to estimate the speed, position and load torque. The PMSM is fed from indirect power electronics converter. This indi...

controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. interval type-2 fuzzy logic systems (it2fls) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. in contrast, adaptive sliding modecontrol (asmc) provides...