Embedded two level direct adaptive fuzzy controller for DC motor speed control

AbstractThis paper presents a proposed approach based on an adaptive fuzzy logic controller for precise control of the DC motor speed. In this concern, the proposed Direct Adaptive Fuzzy Logic Controller (DAFLC) is estimated from two levels, where the lower level uses a Mamdani fuzzy controller and the upper level is an inverse model based on a Takagi–Sugeno (T–S) method in which its output is used to adapt the parameters of the fuzzy controller in the lower level. The proposed controller is implemented using an Arduino DUE kit. From the practical results, it is proved that the proposed adaptive controller improves, successfully both the performance response and the disturbance due to the load in the speed control of the DC motor

Practical Implementation for the interval type-2 fuzzy PID controller using a low cost microcontroller

AbstractIn this study, we propose an embedded real-time interval type-2 fuzzy proportional – integral – derivative (IT2F-PID) controller which is a parallel combination of the interval type-2 fuzzy proportional – integral (IT2F-PI) controller and the interval type-2 fuzzy proportional – derivative (IT2F-PD) controller. The proposed IT2F-PID controller is able to handle the effect of the system uncertainties due to the structure of the interval type-2 fuzzy logic controller. The proposed IT2F-PID controller is implemented practically using a low cost PIC microcontroller for controlling the uncertain nonlinear inverted pendulum to minimize the effect of the system uncertainties due to the uncertainty in the mass of the pendulum, the measurement error in the rotation angle of the pendulum and the structural uncertainty. The test is carried out using the hardware-in-the-loop (HIL) simulation. The experimental results show that the performance of the IT2F-PID controller improves significantly the performance over a wide range of system uncertainties

Intelligent control for nonlinear inverted pendulum based on interval type-2 fuzzy PD controller

The interval type-2 fuzzy logic controller (IT2-FLC) is able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of a fuzzy logic system (FLS). This paper proposes an interval type-2 fuzzy PD (IT2F-PD) controller for nonlinear inverted pendulum. The proposed controller uses the Mamdani interval type-2 fuzzy rule based, interval type-2 fuzzy sets (IT2-FSs) with triangular membership function, and the Wu–Mendel uncertainty bound method to approximate the type-reduced set. The proposed controller is able to minimize the effect of the structure uncertainties and the external disturbances for the inverted pendulum. The results of the proposed controller are compared with the type-1 fuzzy PD (T1F-PD) controller in order to investigate the effectiveness and the robustness of the proposed controller. The simulation results show that the performance of the proposed controller is significantly improved compared with the T1F-PD controller. Also, the results show good performance over a wide range of the structure uncertainties and the effect of the external disturbances

Embedded two level direct adaptive fuzzy controller for DC motor speed control

This paper presents a proposed approach based on an adaptive fuzzy logic controller for precise control of the DC motor speed. In this concern, the proposed Direct Adaptive Fuzzy Logic Controller (DAFLC) is estimated from two levels, where the lower level uses a Mamdani fuzzy controller and the upper level is an inverse model based on a Takagi–Sugeno (T–S) method in which its output is used to adapt the parameters of the fuzzy controller in the lower level. The proposed controller is implemented using an Arduino DUE kit. From the practical results, it is proved that the proposed adaptive controller improves, successfully both the performance response and the disturbance due to the load in the speed control of the DC motor

Embedded system based on a real time fuzzy motor speed controller

This paper describes an implementation of a fuzzy logic control (FLC) system and a/the conventional proportional-integral (PI) controller for speed control of DC motor, based on field programmable gate array (FPGA) circuit. The proposed scheme is aimed to improve the tracking performance and to eliminate the load disturbance in the speed control of DC motors. The proposed fuzzy system has been applied to a permanent magnet DC motor, via a configuration of H-bridge. The fuzzy control algorithm is designed and verified with a nonlinear model, using the MATLAB® tools. Both FLC and conventional PI controller hardware are synthesized, functionally verified and implemented using Xilinx Integrated Software Environment (ISE) Version 11.1i. The real time implementation of these controllers is made on Spartan-3E FPGA starter kit (XC3S500E). The practical results showed that the proposed FLC scheme has better tracking performance than the conventional PI controller for the speed control of DC motors