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In this research, we examined an adaptive control method to suppress overshooting in a precise positioning device with a damper composed of a visco-elastic material and a constrained plate. A two-degrees-of-freedom control system was adopted with conditions, to shape the response characteristics of the desired response using feedforward controller. Moreover, by using a feedback controller to inhibit...
Modelling and control of gas turbines (GTs) have always been a controversial issue because of the complex dynamics of these kinds of equipment. Considerable research activities have been carried out so far in this field in order to disclose the secrets behind the nonlinear behaviour of these systems. Although the results of the research in this area have been satisfactory so far, it seems that there...
In this paper, two methods of control for high-voltage Full Bridge Series-Parallel Resonant (FBSPR) DC-DC converter are proposed and the results are compared. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. The way of obtaining small-signal model of FBSPR converter...
In this paper, a novel direct adaptive NN control algorithm is proposed for a class of ship course autopilot with input saturation. Neural networks (NNs) are used to tackle unknown nonlinear function, and then an adaptive NN controller is constructed by combining Lyapunov function and the backstepping technique. By utilizing a special property of the affine term, the developed scheme avoids the controller...
Aimed at complex multi-motor composed of three motors, difficulty of control by traditional methods such as PID are obvious. An improved control method for three-motor synchronous system which is taken as the research object based on RBF NN inverse is put forward. and the three-motor system can be linearized in series with NN inverse. Here, the inverse can be constructed by combining the RBF NN with...
In this paper, two methods of control for high-voltage Full Bridge Series-Parallel Resonant (FBSPR) DC-DC converter are proposed and the results are compared. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. The way of obtaining small-signal model of FBSPR converter...
Multi-motor drive is a multi-input multi-output (MIMO), nonlinear and strong-coupling system. Its high precision coordinated control performance can meet the requirements of many drive applications, such as urban rail transit, paper making, electric vehicle drive, and steel rolling. To decouple the velocity and the tension of the three-motor drive system, a new control strategy is proposed by incorporating...
To deal with the defects of BP neural networks used in balance control of inverted pendulum, such as longer train time and converging in partial minimum, this article reaLizes the control of double inverted pendulum with improved BP algorithm of artificial neural networks(ANN), builds up a training model of test simulation and the BP network is 6-10-1 structure. Tansig function is used in hidden layer...
In this paper self adaptive RBF neutral network PID controller for linear elevator is presented. RBFNN is widely used in many fields to solve computational problems that are difficult to solve by conventional method. Nowadays with the rapid development of permanent magnet linear synchronous motor (PMLSM) application in elevators, the design of PID controllers of these systems are very important. This...
The maximum power point tracking (MPPT) aims to increase the efficiency of Photovoltaic (PV) systems by operating their PV panels at the optimum power point. Many strategies have been introduced to achieve this objective. However, these strategies vary in their tracking performance, computational complexity and cost. The rapid changes in environmental conditions and the nonlinearity in the current-voltage...
In this paper, we propose an intelligent approach to power system stabilization using a system-centric controller. This architecture uses a control algorithm based on a supervisory loop concept implemented with a system centric controller combining both a Dual Heuristic Programming (DHP) and Model Reference Adaptive Controller (MRAC) controller. The controller performance is tested on a Single Machine...
From the dynamic model of robot arm, a new fuzzy neural network controller is proposed to control the robot arm's trail in this paper. System simulation analysis is given by fuzzy controller and fuzzy neural network controller respectively. Results show that fuzzy neural network control methods has better trail track than the fuzzy control method.
There are many kinds of indexes in desulfurization technology selection of thermo-electricity project, between which complicated nonlinear relation is presented. It is difficult to calculate and lack of effective evaluation methods. In this paper, a comprehensive evaluation index system of desulfurization technology selection has been built, the BP neural network evaluation method is applied to desulfurization...
In this paper, two methods of control for high-voltage Full Bridge Series-Parallel Resonant (FBSPR) DC-DC converter are proposed and the results are compared. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. The way of obtaining small-signal model of FBSPR converter...
By merging the feed forward neural network, the competitive learning algorithm and the fuzzy control, the neural network-based adaptive fuzzy control algorithm is proposed. This system can produce more reasonable fuzzy rules by the competitive (clustering) algorithm, and control the object by the optimized fuzzy rules. The analysis of the system, the experimental result and considerations are given.
Along with the social requirements of power quality improvement, power quality problems are becoming the higher demands of social, reactive power compensation increasingly become the research focus. Based on neural network, non-linear mapping characteristics, puts forward a suitable for direct current control of static VAR generator detecting reactive and harmonic current method, established the neural...
Artificial neural network is a class of biologically-inspired systems that offer solutions to various real-life problems. In this talk, we will present recent advances on neural systems at anatomical and system levels. Recent researches on C. elegans disclose the complete wire diagram of the synaptic connections and morphology of C. elegans associated with functionalities. This enables not only the...
This paper presents the results of Internal Model Control (IMC) for InnoSAT attitude control based on Neural Network (NN). IMC is composed of an inverse model connected in series with the plant and a forward model connected in parallel with the plant. The controller is achieved by estimating the plant and then finding its inverse model of the InnoSAT plant using the NN. The control signal error is...
In consideration of the common sensor failures in aero-engine control system, a new approach is proposed using dual redundant predictors based on neutral network in this paper. The neutral network temporal redundant predictor and spatial redundant predictor are created over the time series redundant information of single sensor and the space redundant information of multi-sensor respectively. The...
The paper deals with an application of non-traditional type of neural network, concretely an orthogonal neural network, for adaptive control. It was provided for real control system, i.e. compressed-air aggregate. The paper includes a description of the method of adaptive inverse control, a description of the orthogonal neural network's structure for this real control system and evaluating of the...
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