HSIC Algorithm of Process Control

2013 ◽  
Vol 336-338 ◽  
pp. 847-851 ◽  
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Xiao Peng Zhang
Keyword(s):  
Mathematical Model ◽  
Process Control ◽  
Intelligent Control ◽  
Practical Application ◽  
Mode Control ◽  
Complicated Model ◽  
Thinking Mode ◽  
Human Simulation

Process control objects mathematical model is difficult to establish. Based on humans thinking mode, control experience, action and intuitional reasoning, Human simulation intelligent control (HSIC) avoids all kinds of difficult problems that we are faced with as seeking the answer of complicated model or establishing brain model, and so there are some advantages for HSIC on process control. In this paper, a detailed algorithm is described for process control by using the method of HSIC. Finally, the results of practical application have proved that HSIC is feasible and effect for process control.

A Real-Time Mathematical Model for Three-Dimensional Tidal Flow and Water Quality

1991 ◽  
Vol 24 (6) ◽  
pp. 171-177 ◽  
Author(s):  
Zeng Fantang ◽  
Xu Zhencheng ◽  
Chen Xiancheng
Keyword(s):  
Mathematical Model ◽  
Water Quality ◽  
Real Time ◽  
Control Volume ◽  
Tidal Flow ◽  
Three Dimensional ◽  
River Estuary ◽  
Pearl River Estuary ◽  
Practical Application ◽  
The Pearl River

A real-time mathematical model for three-dimensional tidal flow and water quality is presented in this paper. A control-volume-based difference method and a “power interpolation distribution” advocated by Patankar (1984) have been employed, and a concept of “separating the top-layer water” has been developed to solve the movable boundary problem. The model is unconditionally stable and convergent. Practical application of the model is illustrated by an example for the Pearl River Estuary.

Design of Intelligent Controller for Ship Motion with Input Saturation Based on Optimized Radial Basis Function Neural Network

2020 ◽  
Vol 13 ◽  
Author(s):  
Renqiang Wang ◽  
Qinrong Li ◽  
Shengze Miao ◽  
Keyin Miao ◽  
Hua Deng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Sliding Mode Control ◽  
Intelligent Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Input Saturation ◽  
Ship Motion ◽  
Mode Control

Abstract: The purpose of this paper was to design an intelligent controller of ship motion based on sliding mode control with a Radial Basis Function (RBF) neural network optimized by the genetic algorithm and expansion observer. First, the improved genetic algorithm based on the distributed genetic algorithm with adaptive fitness and adaptive mutation was used to automatically optimize the RBF neural network. Then, with the compensation designed by the RBF neural network, anti-saturation control was realized. Additionally, the intelligent control algorithm was introduced by Sliding Mode Control (SMC) with the stability theory. A comparative study of sliding mode control integrated with the RBF neural network and proportional–integral–derivative control combined with the fuzzy optimization model showed that the stabilization time of the intelligent control system was 43.75% faster and the average overshoot was reduced by 52% compared with the previous two attempts. Background: It was known that the Proportional-Integral-Derivative (PID) control and self-adaptation control cannot really solve the problems of frequent disturbance from external wind and waves, as well as the problems with ship nonlinearity and input saturation. So, the previous ship motion controller should be transformed by advanced intelligent technology, on the basis of referring to the latest relevant patent design methods. Objective: An intelligent controller of ship motion was designed based on optimized Radial Basis Function Neural Network (RBFNN) in the presence of non-linearity, uncertainty, and limited input. Methods: The previous ship motion controller was remodeled based on Sliding Mode Control (SMC) with RBFNN optimized by improved genetic algorithm and expansion observer. The intelligent control algorithm integrated with genetic neural network solved the problem of system model uncertainty, limited control input, and external interference. Distributed genetic with adaptive fitness and adaptive mutation method guaranteed the adequacy of search and the global optimal convergence results, which enhanced the approximation ability of RBFNN. With the compensation designed by the optimized RBFNN, it was realized anti-saturation control. The chattering caused by external disturbance in SMC controller was reduced by the expansion observer. Results: A comparative study with RBFNN-SMC control and fuzzy-PID control, the stabilization time of the intelligent control system was 43.75% faster, the average overshoot was reduced by 52%, compared to the previous two attempts. Conclusion: The intelligent control algorithm succeed in dealing with the problems of nonlinearity, uncertainty, input saturation, and external interference. The intelligent control algorithm can be applied into research and development ship steering system, which would be created a new patent.

Application of Magnetoelastic Effect of Ferromagnetic Material in Stress Measurement

2012 ◽  
Vol 496 ◽  
pp. 306-309 ◽  
Author(s):  
Yan Ping Shi ◽  
Shu Hua Fan
Keyword(s):  
Mathematical Model ◽  
Stress Measurement ◽  
Ferromagnetic Material ◽  
Induced Voltage ◽  
Practical Application ◽  
Magnetic Pole ◽  
Magnetoelastic Effect ◽  
Voltage Output ◽  
Contact Sensor ◽  
Test Result

A new non-contact sensor with three magnetic pole based on magnetoelastic effect was designed, and its operation principle and mathematical model of induced voltage output were given. The output characteristic of the sensor affected by field current intensity, frequency, and the gap between the probe of the sensor and the surface of the material tested was analyzed by testing. The calculation result based on the output model found by the paper accord basically with the test result. The results of the test have showed that the measuring precision and sensitivity of the sensor can meet the demands of the general practical application.

An Efficient Approach to Define the Input Stimuli to Suppress Epileptic Seizures Described by the Epileptor Model

2020 ◽  
Vol 30 (11) ◽  
pp. 2050062
Author(s):  
João Angelo Ferres Brogin ◽  
Jean Faber ◽  
Douglas Domingues Bueno
Keyword(s):  
Nonlinear Dynamics ◽  
Mathematical Model ◽  
Exact Solution ◽  
Feedback Control ◽  
Epileptic Seizures ◽  
Neural Dynamics ◽  
Practical Application ◽  
Control Gain ◽  
The World ◽  
The Mathematical Model

Epilepsy affects about 70 million people in the world. Every year, approximately 2.4 million people are diagnosed with epilepsy, two-thirds of them will not know the etiology of their disease, and 1% of these individuals will decease as a consequence of it. Due to the inherent complexity of predicting and explaining it, the mathematical model Epileptor was recently developed to reproduce seizure-like events, also providing insights to improve the understanding of the neural dynamics in the interictal and ictal periods, although the physics behind each parameter and variable of the model is not fully established in the literature. This paper introduces an approach to design a feedback-based controller for suppressing epileptic seizures described by Epileptor. Our work establishes how the nonlinear dynamics of this disorder can be written in terms of a combination of linear sub-models employing an exact solution. Additionally, we show how a feedback control gain can be computed to suppress seizures, as well as how specific shapes applied as input stimuli for this purpose can be obtained. The practical application of the approach is discussed and the results show that the proposed technique is promising for developing controllers in this field.

scholarly journals Modeling and Optimization of Bidirectional Clamping Forces in Drilling of Stacked Aluminum Alloy Plates

Materials ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 2866
Author(s):  
Jintong Liu ◽  
Anan Zhao ◽  
Piao Wan ◽  
Huiyue Dong ◽  
Yunbo Bi
Keyword(s):  
Mathematical Model ◽  
Finite Element ◽  
Aluminum Alloy ◽  
Clamping Force ◽  
Practical Application ◽  
Element Simulation ◽  
Theory Of Plates ◽  
Plates And Shells ◽  
The Mathematical Model ◽  
The Relationship

Interlayer burrs formation during drilling of stacked plates is a common problem in the field of aircraft assembly. Burrs elimination requires extra deburring operations which is time-consuming and costly. An effective way to inhibit interlayer burrs is to reduce the interlayer gap by preloading clamping force. In this paper, based on the theory of plates and shells, a mathematical model of interlayer gap with bidirectional clamping forces was established. The relationship between the upper and lower clamping forces was investigated when the interlayer gap reaches zero. The optimization of the bidirectional clamping forces was performed to reduce the degree and non-uniformity of the deflections of the stacked plates. Then, the finite element simulation was conducted to verify the mathematical model. Finally, drilling experiments were carried out on 2024-T3 aluminum alloy stacked plates based on the dual-machine-based automatic drilling and riveting system. The experimental results show that the optimized bidirectional clamping forces can significantly reduce the burr heights. The work in this paper enables us to understand the effect of bidirectional clamping forces on the interlayer gap and paves the way for the practical application.

Sliding Mode Control of the Human Vestibular System

2012 ◽  
Author(s):  
Rachael McCarty ◽  
S. Nima Mahmoodi ◽  
Keith Williams
Keyword(s):  
Mathematical Model ◽  
Sliding Mode Control ◽  
Vestibular System ◽  
Head Movement ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Control Parameters ◽  
Mode Control ◽  
The Mathematical Model ◽  
The Brain

An original sliding mode controller is designed, based on an existing mathematical model for response control of the human vestibular system. The human vestibular system is located in the inner ear and significantly contributes to the functions of detecting head motion, maintaining balance and posture, and realizing gaze stabilization. The vestibular system sends signals to the brain to tell it how the head and body are moving, and the brain reacts by changing eye position accordingly. The nonlinearities of the vestibular system are not completely understood. The biggest nonlinearity is the nystagmus, a bouncing of the eyes to compensate for quick head movement. Another nonlinearity is that the quick phase does not start until head movement reaches a certain frequency. Considering these nonlinearities as well as the uncertainties of the system, sliding mode control a good choice for controlling the system. Several mathematical models of the human vestibular system are considered for use in the control design. The best model of those considered is chosen based on the models’ consideration of nonlinearities and their levels of complexity. The mathematical model used in this paper is a nonlinear transfer function. The output is controlled with a robust sliding mode controller. Results demonstrate the need to increase control parameters as frequency of the sinusoidal input increases to minimize overshoot error. However, since the human head cannot tolerate an infinitely large frequency input, control parameters also will necessarily be limited. Therefore, results show that the designed sliding mode robust controller is an effective mechanism for controlling the mathematical model of the human vestibular system.

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