In this paper, we will propose a cooperative control approach that is based on the hybrid grey-neural network with sliding mode control (HGNS) methodology. The main purpose is to eliminate the chattering phenomenon such that the two-link robotic manipulator has a superior tracking response. Moreover, the system performance obtained via the method of the HGNS can be improved. In the present appr...

The motion control problem for the finger of a humanoid robot hand is investigated. First, the index finger of the human hand is dynamically modelled as a kinematic chain of cylindrical links. During construction of the model, special attention is given to determining bone dimensions and masses that are similar to the real human hand. After the kinematic and dynamic analysis of the model, in or...

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...

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...