In this paper, we describe a method of stability analysis for a GA-Based reference adaptive fuzzy sliding model controller for the handling of these problems for a nonlinear system. Firstly, an uncertain and nonlinear plant for the tracking of a reference trajectory is well approximated and described via a fuzzy model involving fuzzy logic control rules. Then, the initial values of the conseque...

There are several techniques to control of an uncertain nonlinear system. A typical approach is sliding mode control technique [14]. In the sliding mode technique, the proper transformation of tracking errors to generalize errors is introduced, so that n order tracking problem can be transformed into an equivalent first order stabilization problem [16]. The sliding-mode control employs a discon...

The objective of this work is to provide a simple and effective nonlinear controller. Our strategy involves switching the underlying strategies in order to maintain a robust control. If a disturbance moves the system outside the region of stability or the domain of attraction, it will be guided back onto the desired course by the application of a different control strategy. In the context of sw...

This paper focuses on a second order sliding mode based direct power controller (SOSM-DPC) of a three-phase grid-connected voltage source converter (VSC). The proposed control scheme combined with fuzzy logic aims at regulating the DC-link voltage of the converter and precisely tracking arbitrary power references, in order to easily control the system’s power factor. Therefore measures are prop...

This chapter develops a sliding mode and fuzzy logic-based speed controller, which is named adaptive fuzzy sliding-mode controller (AFSMC) for an indirect fieldoriented control (IFOC) of an induction motor (IM) drive. Essentially, the boundary layer approach is the most popular method to reduce the chattering phenomena, which leads to trade-off between control performances, and chattering elimi...

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...

The hydraulic servo control system, which is the important component of parallel robot, is a high order, nonlinear, dynamic asymmetry, parameter uncertain system, which seriously affect dynamic performance of robot, so it is very difficult to gain good performance with traditional control. Based on sliding mode variable structure control method combined with fuzzy control and adaptive control, ...

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 chapter, three methods for synchronizing of two chaotic gyros in the presence of uncertainties, external disturbances and dead-zone nonlinearity are studied. In the first method, there is dead-zone nonlinearity in the control input, which limits the performance of accurate control methods. The effects of this nonlinearity will be attenuated using a fuzzy parameter approximator integrate...