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Anti-windup saturation compensation schemes in two-link flexible arms are studied. The singular perturbation approach is used to decompose the nonlinear system into a rigid subsystem and a fast subsystem, which allows a composite control design for the original system. A neural network is designed to compensate the saturation nonlinear in rigid subsystem, and a robust controller is employed to attenuate...
In this paper, a new iterative algorithm for determination of direction cosine matrix (DCM) is presented, it can be expressed as two forms, matrix exponential and six scalar differential equations respectively, corresponding to each form, related algorithms used for the orthonormalization are derived, although the simulations and algorithm analysis are omitted here, the Van test results verified its...
A three-degree-of-freedom nonlinear dynamic model of the highline cable of Underway Replenishment System(UNREP) was developed, which considered the influence of the incline angle, the motion of the support point and the geometrical of the highline cable. The partial differential equations of the two half of the highline cable were discretized to system of ordinary differential equations (ODE) by Galerkin...
The importance of symbolic analysis in the neural network approach to analog circuit fault diagnosis is discussed in this paper. Theoretical explanations and two explicative examples are presented, by taking into account the k-fault hypothesis.
The simulation of large-scale analog circuits is very expensive. Instead of the circuit complex model, reduction of the computing effort implies using a macromodel capable to capture the behaviors of the original circuit while preserving its essential properties. Building such a model is based on a simplified and unitary description of the circuit, by establishing a simple relationship between the...
On the basis of controlled nuclear fusion equipment HT-7 superconductive tokamak's detection data, this paper reports on an approach of nuclear fusion magneto hydrodynamics(MHD) pattern recognition by using artificial neural network and back-propagation(BP) neural network with delta-bar-delta rules which can monitor the system characteristics and recognize the MHD pattern precisely. The HT-7 nuclear...
Premature convergence is the main obstacle to the application of genetic algorithm. This paper makes improvement on traditional genetic algorithm by linear scale transformation of fitness function, using self-adaptive crossover and mutation probability and adopting close relative breeding avoidance method. Simulation results show that the improved algorithm outperforms traditional genetic algorithm...
A novel algorithm of Electromagnetic Environment (EME) is proposed in this paper. Assessment indices are established based on analysis of factors influenced electromagnetic environment complex. Index weights are acquired by fuzzy comprehensive evaluation method. The grade of complexity is computed based on complex evaluation values according to the grade standard of complexity. Experimental result...
This paper contributes a novel Particle Swarm Optimization (PSO) method. The particle is updated not only by the best position in history (pbest) and the best position among all the particles in the swarm (gbest), but also using the position that is nearest neighbor of pbest. Additionally, we introduce a modified PSO algorithm based on the fuzzy clustering of particles to communication with the nearest...
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...
Least-squares design of digital filters is generally achieved by solving a system of linear equations. The matrices involved in the set of linear equations can be formulated as a Toeplitz-plus-Hankel form such that a matrix inversion is avoided with effectiveness. In this paper, some trigonometric properties are further exploited to obtain the closed-form expressions required for the system associated...
A general model of oil consumption is investigated in this study. This model should be applicable to different countries even with different characteristics. Conventional model that works very well for Malaysia is tested with seven developing Asian countries: China, India, Indonesia, Malaysia, Pakistan, Philippines, and Thailand. The results have shown that this model can not produce a good fit to...
In present work we aimed to develop a NN based approach to translate the design parameter from a submicron technology to a long channel one. The proposed approach is able to find the superseded design parameters in 1.2 mum technology using the input information, which are design parameters of Gain, Phase Margin, Unity Gain Bandwidth and Power in TCMS 0.18 mum. The training data are obtained by various...
With the interface from words to graphic, the quality of application program is more and more depend on the degree which the graphic interface feat the taste of the users. So if we can predict the users' taste of the style of application program, our work must be more popular. Now with the help of BP-neural network we can do it because of its strong capacity of prediction.
The stability of equilibrium point of neural network for the large-scale dynamic system is extremely important. This article has studied the stability of equilibrium point of vector differential equation of the asymmetrical internet, proposed to utilize approximate linear equation to study the stability problem of equilibrium point of neural network. This method is simple and effective to examine...
Due to multivariable, highly nonlinear, strong coupling, time-varying dynamics and unavailability of measurements, induction motor control is still a difficult and complex engineering problem. Vector control has replaced traditional control method using the ratio of voltage and frequency as a constant, which improve greatly dynamic control efficiency of motor. However, under the circumstances of changing...
In this paper, a speed estimation and control strategy for induction motor drive based on an indirect field-oriented control is presented. The rotor speed estimator based on a RBF neural network utilizes stator voltage and current measured values to calculate the rotor speed, and the control approach based on a sliding-mode controller with an integral sliding surface is proposed in order to regulate...
A dynamic decoupling control approach based on neural network inverse system theory is developed for the AC-DC 3 degrees of freedom hybrid magnetic bearing (AC-DC 3-DOF HMB), which is a multivariable, nonlinear, strong coupled system. The configuration of AC-DC 3-DOF HMB is introduced briefly. The mathematics equations of radial and axial suspension forces are deduced. The analytical inverse system...
A recurrent wavelet neural network (RWNN) controller is proposed in this study to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive to track periodic reference trajectories. First, the dynamic model of the PMLSM drive system is derived. Next, an RWNN controller is proposed to control the PMLSM. Moreover, the connective weights, translations and dilations of the RWNN...
The Selective Harmonic Elimination (SHE) PWM technique has become a significant PWM method for less switching loss for three-level neutral-point-clamped (NPC) inverter. This paper introduces an online optimization approach to the SHEPWM technology based on genetic algorithm and BP neural network. The method doesnpsilat need to preset the initial values and to predict the trend of these values over...
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