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In the field of modern national defense and civilian technology, we often need to precisely adjust a bearing platform. The platform with certain equipment to the horizontal position improves the system performance. Short time, high speed, high precision and well stability is required in the leveling system. However, the leveling system is a nonlinear time-varying system. “involvement coupling” problem...
In this paper, because the induction machines (IM) are described as the plants of highly nonlinear and parameters time-varying, to obtain excellent control performances of IM and overcome the shortcomings of the fast modified variable metric optimal learning algorithm (MDFP) and back propagation (BP) learning algorithm of neural network, such as requiring derivation in the process of learning and...
A fuzzy sliding mode controller based on radial basis function neural network (RBFNN) for permanent magnet synchronous machine (PMSM) is investigated in this paper, in which direct torque control (DTC) concept, variable structure control and space vector modulation (SVM) are integrated to achieve high performance. Fuzzy logic is used to adjust the gain of the corrective control of the sliding mode...
A intelligent monitor and control system on multi-factor of aquaculture environment based on wireless sensor networks is designed adopting BP neural networks. The system uses wireless sensor nodes to detect a variety of water quality parameters transmitted to the on-site monitoring host computer through sink node wirelessly. The control module consists of fuzzy controller and decoupling neural network...
General fuzzy controller in the control rules to determine the need, after adjustment, time-consuming and laborious; with a correction factor of fuzzy controller to change the correction factor, the entire control of the table almost affected, would make some point to meet the control requirement has led to some point does not meet the requirements. To solve these problems, proposed a new type of...
Distributed control was a important development direction of Aeroengine in 21 century. For network time-delay question of aeroengine, a method of neural network Smith predictive compensable fuzzy PID control was brought forward. The method integrated neural network and fuzzy logic system into traditional Smith predictive controller and traditional PID controller. Neural network Smith predictive compensable...
In this study, a robust path tracking control scheme is constructed for a nonholonomic mobile robot via a dynamic Petri recurrent-fuzzy-neural-network (DPRFNN). In the DPRFNN, the concept of a Petri net (PN) and the recurrent frame of internal feedback loops are incorporated into a traditional fuzzy neural network (FNN) to alleviate the computation burden of parameter learning and to enhance the dynamic...
A multi-variable dynamic model of the glutamic acid fermentation process based on neural network is established. Combining the off-line Optimal control method and the on-line adaptive fuzzy neural network control method, the hybrid fuzzy adaptive fermentation process control model is designed. The off-line optimization track is the main control model, while the adaptive fuzzy neural network based...
As genetic algorithm can't maintain the diversity of groups and is prone to prematurity, in this paper one introduce niche technology and fuzzy control theory to improve the simple genetic algorithm. The niche technology preserve the variety of the population and fuzzy control can make sure GA gets the optimal solutions in the global search by controlling the crossover- probability and mutation-probability...
The coupling relations of all variables during fermentation process with fermentation are discussed. Since the parameters are always changing as time-varying, nonlinearity and randomicity during biology fermentation control process. the scheme for biology fermentation control process using feed forward decoupling intelligent algorithm for multivariable based on FNN is presented. Fuzzy-Neural controller...
This paper introduces the basic components and key techniques of the steel rolling heating furnace control system's development. Immense amounts of information provided by the steel rolling heating furnace control system has the vital significance for standardize procedures of furnace control system. It proposed a new hybrid fuzzy control formula for combustion automatic control system for reheating...
A method of intelligent PID control was proved and it's based on RBF neural network and fuzzy theory, which constructs RBF neural network identifier online and identifies a controlled object online by means of adopting the receding horizon optimization methods, and adjusts parameters of PID controller online and realizes decoupling control of multivariable, nonlinear and time variation system. The...
In this brief, it presents the implementation of control of an inverted pendulum system by using the Adaptive Neural- Fuzzy. The inverted pendulum system has been built in the educational kit whose purpose is to educate control engineers in the college students. The inverted pendulum system is known as a nonlinear system whose goal is to maintain the balance of the pendulum while tracking a desired...
With the modification of laser sub-marker controlling system, the intelligent harmony close-loop position servo system is designed in this article, which meets the requirement of high performance in position servo system. It bears the advantage of fuzzy controlling and nerve network controlling technology, and it weakens the influence on the system from non-linear factors. Thus the design improves...
The water turbine generator set has the characters of non-linearity, parameter time-variability and non-minimum phase. It is found that PID controller has the problem of integral saturation and poor robustness and the traditional fuzzy controller has a subjective subordinate degree. To improve the running state, a fuzzy neural network based on T-S model is designed by imitating the structure of the...
Radial Basis Function(RBF) is used to identify the model of mine ventilator, frequency control system is introduced to control the speed of ventilator, and traditional control strategy used PID is replaced by FNN. The MATLAB simulation results show that the ventilator modeling by RBF neural network can better reflect its nonlinear characteristic, the speed of ventilator controlled by FNN changed with...
In this paper, a wind velocity control system of low-speed wind tunnel has been built in Inner Mongolia Agricultural University. Due to the difficulties of establishing mathematical model, the complicated nonlinear characteristics and the change of parameters, the wind velocity system is not easy to control in classical PID algorithm. Fuzzy logic was used for the adaptation of the learning algorithm...
This paper discussed and researched the structure and algorithm of fuzzy neural network controller based on the character of fuzzy logic and neural network theory. For the nonlinear system characteristics of uncertainty, high order and hysteresis, this paper used the fuzzy neural network technology to control nonlinear system and improved the control quality obviously. Take the single inverted pendulum...
This paper demonstrates the Maximum Power Point Tracking (MPPT) controller that uses a DC/DC Boost converter with a Fuzzy Neural Network (FNN) system. It simplifies the topology of the DC/DC boost converter model to state equations, which is easy to simulate with Matlab. Additionally, the FNN system uses an integrated Fuzzy and Neural Network (NN), which advantages include uncertainty information...
This paper presents an dSPACE implementation of three-phase squirrel-cage induction motor control using direct torque control (DTFC) technique with the help of intelligent techniques. A fuzzy PI controller is used in the speed control loop. The classical lookup table is replaced by a neural network selector providing switching state to the inverter. The rotor speed is estimated by a simple open loop...
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