A hybrid model is designed by combining the genetic algorithm (GA), radial basis function neural network (RBF-NN) and Sugeno fuzzy logic to determine the optimal parameters of a proportional-integralderivative (PID) controller. Our approach used the rule base of the Sugeno fuzzy system and fuzzy PID controller of the automatic voltage regulator (AVR) to improve the system sensitive response. Th...

This paper proposes a new robust fuzzy gain scheduling of RST controller for a Wind Energy Conversion System (WECS) based on a doubly fed induction generator (DFIG). First, a designed fuzzy gain scheduling of RST controller is investigated, in which fuzzy rules are utilized on-line to adapt the RST controller parameters based on the error and its first time derivative. The aim of the work is to...

In this paper we propose a parallel structure of I-P-D (Integral minus Proportional minus Derivative) type fuzzy controller based on the conventional PID control theory, used to control the speed of DC motor. The conventional PID controller exhibit poor performance when applied to DC motor, it fails to perform satisfactory under parameter variation or load changes. The parallel I-P-D type fuzzy...

This paper considers the fuzzy modeling and robust fuzzy variable control for quadrotor in uncertain environment. The nonlinear system of quadrotor is firstly analyzed in this paper by utilizing laws of motion and force. Then, a Takagi-Sugeno (T-S) fuzzy model is achieved to approximate the system. LMI method is used to acquire an improved sliding surface. On this basis, a fuzzy variable struct...

This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural ...

Permanent Magnet (PM) stepper motors are widely used in precise systems which are affected by external disturbances, parameters uncertainty and saturated control. Also, an appropriate nonlinear controller is required when the problem is to track reference signal. This paper presents a robust adaptive controller to control rotor angular position in stepper motors. The main idea to make a robust ...

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...

The power system dynamic instability is occurred by loosing balance relation between electrical generation and a varying load demand that justifies the necessity of using Power System Stabilizer (PSS). Moreover, the PSS must have the capability of producing appropriate stabilizing signals with limited practical amplitude and it should be robust against a wide range of operating conditions and d...

In this paper, an output based adaptive iterative learning controller using an output recurrent fuzzy neural network is proposed for a class of uncertain nonaffine nonlinear systems. It is assumed that the states are not measurable. Without state observer, a sliding window of measurement is introduced to design the iterative learning controller. The main structure of this controller is construc...

This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various ref...