PID control is the most common used method in industrial control because its structure is simple and it is easy to implement. PID controller has good control effect, now it has been widely used. However, PID method has a few limitations. The overshoot of the PID controller is very big. The adjustment time is long. When the parameters of controlled plant are changing over time, the parameters of controller could hardly change automatically to adjust to changing environment. Thus, it can’t meet the demand of control quality in the process of controlling piezoelectric ceramic. In order to effectively control the piezoelectric ceramic and improve the control accuracy, this paper replaced the learning algorithm of the BP with the mutation particle swarm optimization algorithm(MPSO) on the process of the parameters setting of BP-PID. That designed a better self-adaptive controller which is combing the BP neural network based on mutation particle swarm optimization with the conventional PID control theory. This combination is called the MPSO-BP-PID. In the mechanism of the MPSO, the mutation operation is carried out with the fitness variance and the global best fitness value as the standard. That can overcome the precocious of the PSO and strengthen its global search ability. As a result, the MPSO-BP-PID can complete controlling the controlled plant with higher speed and accuracy. Therefore, the MPSO-BP-PID is applied to the piezoelectric ceramic. It can effectively overcome the hysteresis, nonlinearity of the piezoelectric ceramic. In the experiment, compared with BP-PID and PSO-BP-PID, it proved that MPSO is effective and the MPSO-BP-PID has stronger adaptability and robustness.
KEYWORDS: Optimization (mathematics), Systems modeling, Signal attenuation, Time-frequency analysis, Signal processing, Head, Error analysis, Control systems, Computing systems, Nonlinear optics
The accuracy lives of a measurement system and its components are generally different and it will lead to a waste of resources. In order to make full use of the system’s resources and improve its accuracy life, a novel design method based on uniform accuracy life for measurement systems is proposed in this paper. According to the theory of error decomposition and tracing, Hilbert-Huang transform (HHT) method is employed to decompose the total errors of an error test system for a dial gauge and then the accuracy loss functions for the total system and some error parameters are obtained. Based on the analysis of the transfer function for the accuracy loss between the different parts of the measurement system, a constraint model consisting with the uniform accuracy life principle is set up. Taking the maximum life of the measurement system as the objective function, the uniform design model has been solved by means of the optimization methods. The uniform design method can be used to promote the accuracy life of the measurement system.
A signal processing method for reflective fiber optic displacement sensor is presented by means of a differential evolution optimized extreme learning machine (DE-ELM). The sensing head of the sensor is a combination of an illuminating fiber bundle transmitting incoming light beam and two receiving fiber bundles employed to collect the reflected beam from the reflector. Three fiber bundles with same type are put together and arranged side by side, but the two receiving fiber bundles enfaces have different distances from the reflector surface. The DE-ELM is used for extending the measuring the range of reflective fiber optic displacement sensor. A simulation experiment has been illustrated. The experimental results show that the measuring range can be extended to the whole response characteristics of the fiber optic displacement sensor and a high measuring accuracy can be obtained by the proposed method.
Along with the progress of rating and signal processing technology, because of its advantages and wide application, grating measuring technology has become a research hotspot in the precision measuring field. Nanometer measuring has become urgently to solve problem with the need of industrial development and scientific research from sub micrometer to nanometer precision measurement. This paper systematically discusses its research status, existing problems, developing trends and other issues about grating nanometer measuring technology. It provides references to grating nanometer measuring technology researches and its development.
Main error source, error characteristics and its correction method have a detailed analysis of the grating interference displacement measuring system in this paper. Through the error separation and compensation method, its system error is modified. Random error is separated through frequency spectrum analysis method. Experimental results show that, the system accuracy can be improved from micron or submicron magnitude to nanometer level by these error correction methods. This system can realize nanometer level measurement.
This paper carries out the research of the weights of the dynamic accuracy loss and weight functions. It uses the theory
of grey correlation analysis to obtain the weight functions of accuracy loss of each main structural unit. From the
magnitude of each weight, it can get the accuracy loss of the whole system from the accuracy loss of each structural unit.
Then, it uses this theory to analyze the accuracy loss of a practical measurement system, and obtains the weights of
accuracy loss of each structural unit. The theory of weight function of accuracy loss makes a foundation for further
design of equal accuracy measurement systems.
Study of the dynamic characteristics and accuracy theory about measuring system must build its mathematic model. Aim
at the limitations of traditional modeling methods, studying the whole-system dynamic error modeling theory, this
modeling method and theory consider sufficiently the information about insider buildup units of measurement system, so
the built model can reflect the change of the transfer behaviors of system's inside structural units to influence the actual
measuring system along with time. The modeling theory can be applied widespread; using this modeling theory can build
all system's whole-error modeling. The whole-error modeling of the hundredth meter is built using this theory.
This paper addresses a new and efficient behavioral modeling method of digital I/O ports for EMC and signal integrity
simulations. The proposed modeling methodology is based on the fuzzy logic system from port voltage and current
transient waveforms. The obtained models can be implemented as SPICE subcircuit conveniently and their accuracy and
efficiency are verified by applying to the approach to the characterization of transistor -level models of actual devices.
KEYWORDS: Dynamical systems, Sensors, Time metrology, Data processing, Precision measurement, Control systems, Iron, Inductance, Signal attenuation, Sensing systems
The law of precision loss about dynamic measurement system is studied in this paper. Its total loss accuracy can be
obtained by transformation law of its errors in different measuring phases of a certain measuring period. Based on the
total precision loss and its structural characteristic, WNN is used to decompose systemic total precision loss and trace to
its inside structural units, and build precision loss function model of structural units. So precision loss disciplinarian with
all units and infection of different unit to total precision loss is definitude, the principal infection unit to systemic total
precision can be distinguished. In the end of the paper an application examples have been introduced.
A least squares support vector machine (LS-SVM) based signal processing approach of reflective fiber optic displacement sensor is presented. The example for extending measuring range of the sensor using LS-SVM has been illustrated. From the experimental results, it can be clearly seen that not only the measuring range can be extended to the whole response characteristics of the fiber optics displacement sensor effectively, but also a desired linear relationship between the actual displacement and the LS-SVM predicted output can be obtained. This means the method proposed is very effective for the signal processing of the sensor.
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