The purpose of designing the active suspension systems is providing comfort riding and good handling in different road disturbances. In this paper a novel control method based on adaptive neuro fuzzy system in active suspension system is proposed. Choosing the proper data base to train the ANFIS has an important role in increasing the suspension system’s performance. The data base which is used...

in this paper, an optimal adaptive fuzzy integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet dc motor. in the proposed control, sliding surface of the sliding mode control is defined according to the information of position tracking error, derivatives, and error integral. in order to estimate bounds ...

this paper presents a gaussian radial basis function neural network based on sliding mode control for trajectory tracking and vibration control of a flexible joint manipulator. to study the effectiveness of the controllers, designed controller is developed for tip angular position control of a flexible joint manipulator. the adaptation laws of designed controller are obtained based on sliding m...

Two robust nonlinear controllers along with a nonlinear observer have been developed in this study to control a 1D nonlinear flexible spacecraft. The first controller is based on dynamic inversion, while the second one is composed of dynamic inversion and µ-synthesis controllers. The extension of dynamic inversion approach to flexible spacecraft is impeded by the non-minimum phase characteristi...

This article proposes a procedure for upgrading linear proportional controller to sliding mode one preventing degradation of control quality. Two nonlinear algorithms are studied in this context: Unit and Homogeneous Sliding Mode Controllers (SMCs). The parameters the controllers defined using gains (already well-tuned) controller. main idea is split state-space into two regions, region control...

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...

In this paper, we develop a new control method that brings together the advantages of fuzzy logic and sliding mode control. First, we introduce a non-chattering robust sliding mode control. Then, in order to improve the performance of the controller a fuzzy logic algorithm is integrated with the sliding mode controller. This algorithm decides the slope of the sliding surface of the sliding mode...

A systematic way to combine adaptive control and sliding mode control (SMC) for trajectory tracking of robot manipulators in the presence of parametric uncertainties and uncertain nonlinearities is developed. Continuous sliding mode controllers without reaching transients and chattering problems are rst developed by using a dynamic sliding mode. Transient performance is guaranteed and globally ...

The stability and trajectory control of a quadrotor carrying a suspended load with a fixed known mass has been extensively studied in recent years. However, the load mass is not always known beforehand in practical applications. This mass uncertainty brings uncertain disturbances to the quadrotor system, causing existing controllers to have a worse performance or to be collapsed. To improve the...