The rocket is the only vehicle that launches the spacecraft in the space. The orientation of the spacecraft in precise position is so crucial. But, the motion of the rocket can be influenced by internal and external disturbances. Furthermore, the rocket is a multi-input and multi-output nonlinear system whose dynamics are unstable and poorly understood. Hence, attitude control of the rocket is ...

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains compared to proportional-integral-derivative (PID) controllers. This research paper proposes a design procedure and a tuning procedure that carries tuning rules from the PID domain over to fuzzy single-loop controllers. The idea is to start with a tuned, conventional PID controller, replace it with an equiva...

Function and its partial derivative approximation based upon a set of discrete dataset are important issues in soft computing. Several function approximators have been presented most of them fits a model to the dataset so that the Mean Squared Error is minimized. In this paper, we propose to calculate the derivative of the Neuro-Fuzzy function approximator directly according to the parametric s...

The objective of this paper is to design a nonlinear robust controller for the multimachine power system. We present in this study a sliding mode control method without the reaching phase by modifying the terms of the output tracking error combined with the fuzzy Proportional Integral Derivative based on Power System Stabilizer (FPID-PSS). The Mamdani fuzzy inference is used in this study to fi...

Perceptions about function changes are represented by rules like “If X is SMALL then Y is QUICKLY INCREASING.” The consequent part of a rule describes a granule of directions of the function change when X is increasing on the fuzzy interval given in the antecedent part of the rule. Each rule defines a granular differential and a rule base defines a granular derivative. A reconstruction of a fuz...

The classical proportional-derivative (PD) control is relatively easy to design, but useful for fast response controllers by combining proportional control and derivative control in parallel. However, as PD control is linear, it is not able to be used to deal with non-linear plants. An answer to this problem is fuzzy-logic control, which is also a model-free control scheme and can be applied to...

This paper deals with the development of a neuro-fuzzy controller for a wind-diesel system composed of a stall regulated wind turbine with an induction generator connected to an ac busbar in parallel with a diesel-generator set having a synchronous generator. A gasifier is capable of converting tons of wood chips per day into a gaseous fuel that is fed into a diesel engine. The controller input...

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 ...

Fuzzy relation equations (FRE) are associated with the composition of binary fuzzy relations. In the present work FRE are used as a tool for studying the process of learning a new subject matter by a student class. A classroom application and other suitable examples connected to the student learning of the derivative are also presented illustrating our results and useful conclusions are obtained.