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This paper presented a genetic - fuzzy logic based Proportional-Integral-Derivative controller (GFPID) for automatic generation control of two area thermal-thermal power system. Genetic algorithm has been applied to simultaneously tune PID gains, membership functions and control rules of FPID controller to minimize the frequency deviations of the system against the load disturbances. An objective...
Shape memory alloy (SMA) composites offer a great potential as actuators because of its excellent power to weight ratio, smooth motion and silent actuation. However, SMA actuated robotic manipulator systems have severe hysteresis, system nonlinearities, model and parametric uncertainties those are often responsible for position inaccuracy in a regulation or tracking system. A simple and upstanding...
In this paper a simple adaptive predictive fuzzy logic controller is developed for the attitude control of a micro-satellite; its performance is compared with a PID controller. PID controller is the most widely used among the conventional controllers. The gain of proportional, integral and derivative control has to be tuned and fixed throughout the control simulation. APFLC is introduced in order...
This paper proposed a new neural network algorithm with fuzzy iterative learning controller and applied to a certain turbofan engine rotor speed control system. A dynamic neural network was used to identify the plant on-line. The control signal was then calculated iteratively according to the responses of a reference model and the output of identified plant. A fuzzy logic block with four very simple...
A novel design method of boundary controller for certain aircraft based on fuzzy logic control is proposed in this paper. The method integrates optimization of fuzzy control function and on-line self-tuning of domain in fuzzy control system, which can largely improve qualities and adaptabilities of control system. A least squares algorithm of proportional gain ?? can optimize fuzzy logic rules. Self-tuning...
In this paper, we describe the design of an intelligent pedestrian crossing and vehicle controller based on fuzzy logic technology. This paper is part of our work in which we attempt to use genetic algorithm and fuzzy logic in traffic light control and pedestrian crossing. In our approach, we use two sensors, the first one calculates the vehicle density and the other calculates the pedestrian density...
In this paper a fuzzy sliding mode control (FSMC) for spacecraft attitude tracking in terms of quaternion is designed. For this purpose, at first, the spacecraft dynamic and kinematic equations based on quaternion are described. Then, the design procedure of related variable structure controller is presented. To prove the system stability in sliding mode and also to guarantee the convergence of quaternion...
In this paper, a chattering free sliding mode control (SMC) for a robot manipulator including PID part with a fuzzy tunable gain is designed. The main idea is that the robustness property of SMC and good response characteristics of PID are combined with fuzzy tuning gain approach to achieve more acceptable performance. For this purpose, in the first stage, a PID sliding surface is considered such...
In order to realization electronic parts product appearance quality detection control, one kind of processor based on the intelligent knowledge automatic extraction and system intelligence modeling was presented. In the processor, wavelet-fuzzy technique and neural network technique are combined. Uses the fuzzy wavelet extraction image feature, and wavelet function is used as fuzzy membership function...
Analysis of nonlinear dynamics of one-dimensional fuzzy control system is achieved indirectly. The fuzzy control law is decomposed into a linear control law and a superimposed nonlinearity. The linear part is treated as variable-level bang-bang control and analyzed by applying Lyapunov stability theorem. Superimposed nonlinearity can then be categorized according to its effects on the stability and...
Methods are investigated in which controllers (simple memoryless nonlinear functions of the output of the plant) are directly estimated from input-output data without a model of the plant. A procedure is proposed which first selects good data sequences according to some control objective and then estimates the controller parameters directly from the selected sequences. Connections are drawn with other...
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