Sliding mode control is introduced into classical model free fuzzy logic control for discrete time nonlinear systems with uncertainty to the design of a novel fuzzy sliding mode control to meet the requirement of necessary and sufficient reaching conditions of sliding mode control. The simulation results show that the proposed controller outperforms the original fuzzy sliding mode controller an...

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 recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...

This article presents a fuzzy sliding-mode control scheme for a class of Takagi-Sugeno (T-S) fuzzy which are subject to norm-bounded uncertainties in each subsystem. The proposed stabilization method can be adopted to explore T-S uncertain fuzzy systems (TSUFS) with various local control inputs. Firstly, a new design is proposed to transform TSUFS into sliding-mode dynamic systems.In addi...

This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct...

In this paper, a novel adaptive fuzzy sliding mode control method is proposed for the robust tracking control of robotic manipulators. The proposed controller possesses the advantages of adaptive control, fuzzy control, and sliding mode control. First, system stability and robustness are guaranteed based on the sliding mode control. Further, fuzzy rules are developed incorporating with adaptati...

The purpose of this paper is to apply adaptive fuzzy sliding mode control for structurally controlling buildings with sliding bearing isolation. Combining fuzzy control and robust control such as sliding mode control, reduces fuzzy rule bases complexity and ensures stability and robustness. We use Lyapunov theory to develop a self-tuning law. Stiffness uncertainty and time delay is used to demo...

This paper presents the development and performance analysis of intelligent control techniques such as Sliding Mode controller and Fuzzy logic Controller for Brushless DC (BLDC)motor drives. Today, strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance. One of the best nonlinear robust controller which can be used i...

This paper focuses on the development of a robust fuzzy sliding-mode scheme for controlling a vehicle motion system by continuously adjusting the brake torque, Fuzzy logic known for its properties of universal approximator and sliding mode control for its robustness in the presence of parameter variations and the disturbances are employed to control the wheel slip rate in emergency braking mane...

This paper addresses the problems caused by an inappropriate selection of sliding surface parameters in fuzzy sliding mode controllers via an optimization approach. In particular, the proposed method employs the parallel distributed compensator scheme to design the state feedback based control law. The controller gains are determined in offline mode via a linear quadratic regular. The particle ...