[PDF] Top 20 Improved CMAC neural network control scheme
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Improved CMAC neural network control scheme
... Introduction: The cerebellar model articulation controller (CMAC) was proposcd by Albus [l]. This neural network is capable of learning noclinear functions extremely qui[r] ... See full document
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Practical stability issues in CMAC neural network control systems
... [3], [4] (in continuous-time format) and has raised much interests in applying it to various control problems. This scheme does not evolve from traditional control theory, but rath[r] ... See full document
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High-order MS_CMAC neural network
... of neural networks. In their work, the network structure is always a three-layer tree ...structure CMAC (MS_CMAC) neural network in structural ...trapezium scheme is ... See full document
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MS_CMAC neural network learning model in structural engineering
... Applying neural network computing toward structural engineering problems has received increasing interest, with particular emphasis placed on supervised neural ...vised neural network ... See full document
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Improved MS_CMAC neural networks by integrating a simplified UFN model
... variational CMAC neural network that is designed for modeling smooth functional ...structure network that is composed of one-dimensional CMAC ...an improved model by integrating ... See full document
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Temperature control with a neural fuzzy inference network
... target-switching scheme is proposed to serve as a front-end processor of the fuzzy active controller and to deal with the local trapping and wandering cycle problem in the navigation of a behavior-based mobile ... See full document
12
Wavelet Neural Network Control for Linear Ultrasonic Motor Drive
... proposed control scheme, the WNN control system is implemented in a PC-based computer control system, and the LUSM is driven by a voltage source inverter using LLCC resonant ... See full document
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Water bath temperature control with a neural fuzzy inference network
... trained network is con gured as a network controller to the plant as shown in ...perfect control. To achieve perfect control performance, on-line training is usually ...trained network ... See full document
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A functional-link-based fuzzy neural network for temperature control
... The second set of simulations is performed to elucidate the noise-rejection ability of the five controllers when some unknown impulse noise is imposed on the process. One impulse noise value −5 ° C is added to the plant ... See full document
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Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management
... Step 1: Create training data by case simulations The procedure generates data from case simulations performed by using ISOQUAD. ISOQUAD is a groundwater flow and contaminants transport simulation model for a confined ... See full document
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Supervisory recurrent fuzzy neural network control for long-term ecological systems
... the neural network-based controllers have been developed to compensate the effects of nonlinearities and system uncertainties, so that the stability, convergence and robustness of the control system ... See full document
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Recurrent-neural-network-based adaptive-backstepping control for induction servomotors
... at the seventh second. Fig. 3(b) shows that when parameter variation occurs, degenerate tracking responses always result. For comparison, the proposed RNABC scheme is applied for an induction-servomotor ... See full document
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Application of neural fuzzy network to pyrometer correction and temperature control in rapid thermal processing
... different control structures, where the nonuniformity is given by the difference of the two controlled temperatures measured at the center and the margin of the ...based scheme can keep better temperature ... See full document
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Direct adaptive iterative learning control of nonlinear systems using an output-recurrent fuzzy neural network
... fuzzy neural net- work (ORFNN) is presented for a class of repeatable nonlinear sys- tems with unknown nonlinearities and variable initial resetting er- ...auxiliary control components are applied to ... See full document
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The Robust Neural Network Control Theorem Apply to Manipulator Tracking 黃睿祥、陳昭雄
... adaptive control technique, an adaptive law is presented for tuning all parameters of the neural network system, including the output weights, the widths and the centers, thereby reducing the ... See full document
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An artificial neural network-based scheme for fragile watermarking
... FRAGILE WATERMARKING PROCEDURES At first, the host image is transformed by the discrete wavelet transform (DWT) to transfer image information from the spatial domain t[r] ... See full document
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FUZZY ADAPTIVE LEARNING CONTROL NETWORK WITH ONLINE NEURAL LEARNING
... Given the supervised training data, the proposed learning algorithm first decides whether or not to perform the structure learning based on the fuzzy similarity measure o[r] ... See full document
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Optimal control algorithm and neural network for dynamic groundwater management
... Researchers have found that obtaining optimal solutions for groundwater resource-planning problems, while simultaneously considering time-varying pumping rates, is a challenging task. This study integrates an artificial ... See full document
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Counterpropagation fuzzy-neural network for city flood control system
... The neural networks and fuzzy systems are either used as competing alternatives to the traditional hydrological models or work in synergy with the traditional models to pro- duce better modeling ...a neural ... See full document
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Neural-network connection-admission control for ATM networks
... ATM network node and estimates its equivalent band- width C,. The network resource manager calculates the bandwidth currently available for allocation, denoted by C,, [r] ... See full document
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