Abstract This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education....

A proportional integral derivative (PID) controller is the most commonly used controller in controlling industrial loops due to its simple structure, robust nature and easy implementation. Tuning a PID controller is an important task. The conventional methods for tuning a PID controller have certain limitations. These limitations can be taken care by tuning the PID controller using intelligent ...

An adaptive approach to control a cooling coil chilled water valve operation, called adaptive fuzzy logic control (AFLC), is developed and validated in this study. The AFLC calculates the error between the supply air temperature and supply air temperature set point for air in an air handling unit (AHU) of a heating, ventilating, and air conditioning (HVAC) system and determines optimal fuzzy lo...

Aiming at the uncertainty of model parameters and dominate time delay of the controlled object in feed water system of boiler, combined with improved Smith predictor control method and fuzzy immune PID control method, improved Smith predicting controller based on fuzzy immune is designed. Fuzzy Immune PID controller can self-tune parameters, and has adaptive capacity to the diversification of c...

Due to nonlinear P-V characteristics of photovoltaic generator, a maximum power point tracking(MPPT) algorithm is needed to optimize the performance of photovoltaic (PV) system.In this paper, an adaptive fuzzy proportional integral derivative (AFPID) control based maximum power point tracking strategy for photovoltaic system is proposed. The proposed adaptive fuzzy PID method integrates two lev...

This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consist...

The modelling, numerical simulation and intelligent control of an expert HVAC (heating, ventilating and air-conditioning) system having two different zones with variable flow-rate were performed by considering the ambient temperature in this study. The sub-models of the system were obtained by deriving heat transfer equations of heat loss of two zones by conduction and convection, cooling unit ...

The objective of this study is to present an offline control of highly non-linear inverted pendulum system moving on a plane inclined at an angle of 10° from horizontal. The stabilisation was achieved using three different soft-computing control techniques i.e. Proportional-integral-derivative (PID), Fuzzy logic and Adaptive neuro fuzzy inference system (ANFIS). A Matlab-Simulink model of the p...

We designed a neuro fuzzy control strategy for control of cyclical leg movements of paraplegic subjects. The cyclical leg movements were specified by three ‘swing phase objectives’, characteristic of natural human gait. The neuro fuzzy controller is a combination of a fuzzy logic controller and a neural network, which makes the controller self tuning and adaptive. Two experiments have been perf...

In this paper, a heating, ventilating and air-conditioning (HVAC) system was designed and two different damper gap rates (actuators position) of the HVAC system were controlled by a conventional PID (proportional–integral–derivative) controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the...