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The heat exchange of distilled water unit is a very complex process.The main steam pressure and temperature are tightly coupled with the pressure of raw water, temperature and flow in the circuit, and show non-linear relationship. There are two important parameters need to be controlled in water production process: conductivity and temperature of distilled water at the exit. This is a typical double...
In order to improve tracking accuracy of the servo system, an adaptive inverse controller with PID feedforward is designed. It is based on the time-delay characteristic of the adaptive inverse control when training. The controller can realize accurately tracking of the servo, so as to meet the working need of the system. Finally, the tracking simulation is carried out on the digital servo experimental...
This paper presents an adaptive prediction-regret driven negotiation strategy for bilateral bargaining without modeling opponents, which combines the prediction idea in heuristic method and the regret principle in psychology. Experimental results show that agents that employ this strategy outperform agents that use other strategies previously proposed in the literature.
Regression-type algorithms are widely used for system modeling and characterization. There are applications where such characterizations are to be performed “on-line” to support control mechanisms and other decisions. In embedded autonomous systems robustness considerations ask for techniques, which, in addition to reflecting the actual state of the system and its environment, can continuously provide...
Software development methods aim at solving the software crisis. Many presented methods gain reputations under special application environments. There are so many kinds of methods that developers are troubled when choosing the most suitable one. This article presents a pervasive software development method aiming at helping developers deal with the trouble. The pervasive method advocates logicality,...
Nonparametric diffusion mixing estimator (DME) based blind signal separation (BSS) algorithm is proposed under the framework of natural gradient optimization method. In order to improve the performance of signal separation by BSS, the probability distributions of source signals must be described as accurately as possible. In this paper, we use the new data-driven bandwidth selection method based MDE...
Hybrid computational method was used on the basis of available experimental data and production- nutrient ratios were obtained to suggest best nutrient combinations for getting more profitable production of Isabgol. Nutrient combinations could be computed for the choice of farmer. However nutrient combination N 54.435 + P2O5 12.097 + K2O 4.839 Kgha-1 could be detected as best solution for farmers...
A new algorithm for speed observer based on Model Reference Adaptive System (MRAS) is proposed for high performance induction motor drive. It uses stator current error based MRAS speed observer. The reference model of the stator current error based MRAS is the measured stator current components and the adaptive model is neuro-fuzzy based stator current observer. The adaptive model also needs the use...
In this paper a comparison is carried out in order between fuzzy logic controller and adaptive neuro-fuzzy controller. We make use of these two control systems to regulate the temperature of the water bath system. We see that the Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set...
The paper proposes a new hybrid forecasting model using auto regressive moving average (ARMA) as basic architecture and particle swarm optimization (PSO) as learning algorithm. These two combinations have yielded an efficient prediction model for retail sales volumes. To facilitate comparison ARMA, functional link artificial neural network (FLANN) and MLP models are also simulated. The performance...
This paper presents Adaptive Neuro-Fuzzy Inference System (ANFIS) based intelligent control of vector controlled induction motor drive. The proposed intelligent control scheme consists of sensorless adaptive neuro-fuzzy speed controller with speed estimation based on adaptive neuro-fuzzy inverse model. The proposed neuro-fuzzy speed controller incorporates fuzzy logic algorithm with a five-layer artificial...
An optimal adaptive controller for multidimensional disturbed systems is concerned in this paper. The system parameters, especially the first parameters of the controller, are unknown a prior. The one-step-ahead adaptive controller is designed based on the input matching technique and the extended least-squares (ELS) algorithm. It is shown that the system identification is consistent and the adaptive...
When a linear model is used for controlling nonlinear systems solely, it can't satisfy accuracy requirement. Whereas, although a neural network can deal with the accuracy problem, it may lead to instability. In this paper, an adaptive controller is proposed for nonlinear dynamical systems based on linear model and quasi-ARX neural network model. A switching algorithm is designed between the linear...
This work mainly focuses on developing a concept towards building an object-centric thermal mapping (OCT Map) environment based on the use of wireless sensor networks. The sensor network is represented through infrastructural sensors of any functional space like the cool-room or a food-store. These sensors facilitate initial values for the calculation of the temperature at a given location within...
Fuzzy neural network can handle non-linear, complex data, but the structure of model determination is an important and difficult issues identified. More complete results can be made in a short period of time by the optimization network model. To address this issue, this paper presents the fusion of a quantum clustering algorithm and fuzzy c-means clustering algorithm, the fuzzy neural network structure...
A time-series prediction model using a Bilinear Recurrent Neural Network (BRNN) is proposed in this paper. The BRNN model used in this paper is the Multiresolution architecture with an adaptive training mode. The Multiresolution Bilinear Recurrent Neural Network (MBRNN) is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The proposed MBRNN-based...
This paper is concerned with high performance control of three-phase UPS system. The basic requirements of a UPS control system are mentioned. Different control techniques are classified and their performance is briefly described. A hybrid learning-adaptive controller is proposed based on the performance of existing methods. For the learning part, a Repetitive Controller (RC) is used and a Model Reference...
This paper presents a new speed-sensorless vector control drive system for induction motor. In order to produce low harmonics in output voltage and current, reduce the torque fluctuation, and avoid the high voltage jump in switching time, the system utilizes three-level inverter to supply power for the induction motor and a SVPWM scheme with neutral point voltage balance strategy is applied for the...
Maglev train is a new vehicle without support wheel and its movement speed is gained through a special measure equipment. The paper proposes a neural network arithmetic for the maglev train speed estimator which combines characteristics of its traction linear induction motor. The result of a dynamic simulation experiment shows that real speed measure is near to theory calculation. This proves that...
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