In this study, a modified quantum-behaved particle swarm optimization (MQPSO) approach is proposed to design an optimal fuzzy PID controller for asymptotical stabilization of a pendubot system. In the fuzzy PID controller, parameters are determined by using MQPSO algorithm. The MQPSO method and other PSO methods are then applied to design an optimal fuzzy PID controller in a pendubot system. Co...

In this paper, we present a backstepping based fuzzy logic (FL) scheme for the active control of vehicle suspension systems using the two-degrees of freedom or 1/4 car model. The full dynamics of a novel hydraulic strut are considered. The servo-valve dynamics are also included. A fuzzy logic system is used to estimate the nonlinear hydraulic strut dynamics. The backstepping fuzzy logic scheme ...

Fuzzy PID controllers provide a promising approach for industrial applications with many desirable features. However, the large number of parameters and rule bases make self-tuning fuzzy PID controller optimization a complex task. In this paper, a novel tuning method based on the development of the standard particle swarm optimization (PSO) is proposed for optimum design of fuzzy PID controller...

Abstract This work develops a mathematical model of quarter car suspension system with two degrees freedom and suggests fuzzy adaptive PID controller by assessing the drawbacks conventional control methods. The three parameters are automatically modified control, adjusted in real time. Matlab/Simulink platform is used to create relevant simulation model. results demonstrate superiority suggeste...

This paper deals with the design of a novel fuzzy proportional–integral–derivative (PID) controller for automatic generation control (AGC) of a two unequal area interconnected thermal system. For the first time teaching–learning based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed fuzzy-PID controller. The design problem is formulated as an optimi...

This paper presents an adaptive neuro-fuzzy controller ANFIS (Adaptive Neuro-Fuzzy Inference System) for a bilateral teleoperation system based on FPGA (Field Programmable Gate Array). The proposed controller combines the learning capabilities of neural networks with the inference capabilities of fuzzy logic, to adapt with dynamic variations in master and slave robots and to guarantee good prac...

The main objective of Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. T...

Today, DC motors is still being used globally due to their easy speed controllability. In this article, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed for DC motors. The main purpose of performing such task is to reduce the DC motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...