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In this study, the aim is to track the desired pitch and yaw axis trajectories of a 2-DOF helicopter system. For this purpose, neuro-fuzzy system with parameterized conjunctors is used and its performance is compared with a conventional control approach, namely a PID controller. In neuro-fuzzy methods, in order to obtain an optimal fuzzy model, the most commonly used approach is to tune the parameters...
Model-free approaches such as Artificial Neural Networks and Fuzzy Controllers are widely used in the control of Antilock Braking System (ABS) due to its strongly nonlinear structure and uncertainties involved. In this paper the design of a Spiking Neural Network (SNN) controller is considered for the regulation of the wheel slip value at its optimum value. For the training of the network a gradient...
In this study, two fuzzy algorithms, type-1 fuzzy algorithm with parameterized conjunctors and a novel approach interval type-2 fuzzy algorithm with parameterized conjunctors are used in the modeling application for nonlinear functions. The aim of using parameterized conjunctors as fuzzy operators in these algorithms is not to lose or distort the expert knowledge about the system during the optimization...
In conventional fuzzy modeling and control, to obtain an optimal fuzzy system, a commonly used approach is to tune the parameters of the membership functions. However, if the membership functions carry significant expert knowledge about the system, this may be lost or distorted during the optimization process. In order to prevent such a loss of valuable information, parameterized conjunction operators...
A type-2 Takagi-Sugeno-Kang fuzzy neural system is proposed and its parameter update rules are derived using fuzzy clustering and gradient learning algorithms. The proposed type-2 fuzzy neural system is used for the control and the identification of a real-time servo system. Fuzzy c-means clustering algorithm is used to determine the initial places of the membership functions to ensure that the gradient...
Control of nonlinear systems is a challenging task in control engineering and the use of type-2 fuzzy logic controllers (FLCs) has been proposed as a promising approach, as they can perform adequately in dynamically unstructured environments that include large amount of uncertainties. In this paper, an Anti-Lock Braking System (ABS) is controlled by an interval type-2 fuzzy logic controller. The control...
A type-2 fuzzy neural system (T2FNS) is proposed in this paper for process control. The structure of the system is presented and the rules for updating its parameters are derived using the gradient algorithm. The effectiveness of the proposed approach is evaluated on a laboratory setup that regulates the speed of a DC motor and the experimental results are compared with those obtained with the use...
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