A novel single-neuron smith-predictive AGC system

The thickness of the steel strip is an important indicator of the overall strip quality. Deviations in thickness are primarily controlled using the automatic gauge control (AGC) system of each rolling stand. At the last stand, the monitoring AGC system is usually used, where the deviations in thickness can be directly measured by the X-ray thickness gauge device and used as the input to the AGC system. However, due to the physical distance between the thickness detection device and the rolling stand, time delay is unavoidably present in the thickness control loop, which can affect control performance and lead to system oscillations. Furthermore, the parameters of the system can change due to perturbations from external disturbances. Therefore, this paper proposes an identification and control scheme for monitoring AGC system that can handle time delay and parameter uncertainty. The cross-correlation function is used to estimate the time delay of the system, while the system parameters are identified using a recursive least squares method. The time delay and parameter estimates are then further refined using the Levenberg-Marquardt algorithm, so as to provide the most accurate parameter estimates for the complete system. Simulation results show that, compared with the standard Proportion Integration Differentiation (PID) controller approach, the proposed approach is not affected by changes in the time delay and parameter uncertainties.

Abstract-Because the request to the quality of cold rolling sheet strips is higher and higher, the hydraulic AGC (Automatic Gauge Control) has been a requisite means for improving the quality of cold rolling strips' finished products. But the PID control strategy, being comprehensively used in the locale, is difficult to satisfy the request of improving the control precision of cold rolling mill, because robustness is not very strong. The dynamic matrix control, brought forward by Cutler, is one of predictive control theories. It adopts the non-parameter model based the step response of the controlled object, and adopts strategies of multi-step prediction, receding-horizon optimization and feedback correction, which has the good tracking characteristic. The dynamic matrix control has succeeded to be applied in the industry field, so it is indispensable and feasible to explore its application in the hydraulic AGC system of the cold rolling mill. But the step response of the whole hydraulic AGC can't be gained easily in the practical project, so it restricts the application of the dynamic matrix control in the hydraulic AGC. In this article, using for reference the thought of the cascade control, the predictive control is combined in the cascade structure. In the thickness loop of the hydraulic AGC, it adopts PID control. And in the inner loop of the screw-down servo system, it adopts the dynamic matrix control. The cascade predictive control in this article solves the problem of gaining the step response of the whole hydraulic AGC difficultly. When adopting the dynamic matrix control, the state observer is constructed, which makes the control system have the state feedback form with the observer, strengthens robustness of the system by correcting the predictive model, and makes the system have the intelligence. It synthesizes merits of PID control, which possesses of the easy algorithm and adjusting the parameter conveniently, the characteristic of the dynamic matrix control including of good tracking characteristic and strong robustness. The result of the experiment shows that the adopted control strategy makes the dynamic quality of the system improved largely. The response time and the control precision of the screw-down servo system are improved. And the thickness precision of the strip is improved too.

The dead-zone input and hydraulic cylinder friction of the pump-controlled automatic gauge control (AGC) system introduce significant challenges to the high-precision rolling of lithium battery pole pieces. To address these nonlinearities, this paper establishes the friction and dead-zone model of the pump-controlled AGC system, and a slide-mode observer is designed to estimate the friction state z in the LuGre model. Furthermore, an adaptive compensation method is adopted to identify the unknown parameters of the input dead-zone and friction models. Meanwhile, combined with the framework of backstepping control design, both matched and mismatched disturbances are effectively compensated. Stability analysis guarantees the convergence of the estimation errors and closed-loop signal boundedness. Finally, experimental results validate the effectiveness and robustness of the proposed control strategy.

In order to fully understand dynamic behavior of the thickness variation and conduct off-line process tuning, a dynamic simulator for the feedforward Automatic Gauge Control (AGC) for a hot strip finishing mill in China Steel Corporation is developed. One of the major factors influencing on deviation of delivery thickness of the steel strip is the temperature variation caused by cyclic contact between the steel strip and beams, which transfer the strip in the hot rolling process. This temperature difference brings about hardness variation along the strip, which is known as skid marks. Simulation results and system analysis verify that the feedforward AGC system is capable of overcoming the high frequency thickness variation disturbed by the cyclic temperature difference, which usually cannot be effectively compensated by regular gaugemeter AGC feedback loop. A strategy to locate the optimal feedforward gain is also proposed.

Hot strips are presently being rolled out with considerable thickness accuracy. This has been made possible due to superordinated control system comprising of adaptive setup model, monitor thickness control, automatic gauge control, tension and looper control, hydraulic gap control etc. The present work is, however, confined to modeling and simulation studies of hydraulic gap control system in the last stand of the finishig mill of a typical hot strip mill (HSM). The simulation results based on the model show that the system operates effectively to provide high thickness accuracy and good response behavior.

Strip rolling is a very complicated nonlinear process, and characterized by couple between automatic shape control (ASC) and automatic gauge control (AGC), the coupling relationship between ASC and AGC heavily affects the improvement of combined controlling quality. This paper presents a kind of multivariable combination control system based on CMAC-PID. The perfect simulation results indicate that the ASC-AGC control system has good performances in adaptively tracking target and excellent anti-interference function. At the same time, the cross coupling between ASC and AGC is reduced.

To meet the high thickness accuracy requirements in cold-rolling processes, a roll eccentricity signal extraction method based on modified particle swarm optimization and wavelet threshold denoising (MPSO-WTD) with intrinsic time-scale decomposition (ITD) is proposed. The strong denoising ability of the wavelet is combined with the decomposition and recognition attributes of ITD for non-stationary signals. Periodic disturbances in strip thickness caused by roll eccentricity are actively compensated. First, the wavelet is used to denoise the signal and the MPSO algorithm is applied to determine a rational threshold and improve the calculation efficiency. Then, the denoised signal is decomposed into proper rotational components (PRCs) using the ITD method, and an appropriate PRC component representing the eccentricity signal is extracted. Finally, the eccentricity compensation signal is applied in the automatic gauge control (AGC) system of the cold rolling mill. During the rolling process, the rolling speed is not constant and will directly affect the frequency of the roll eccentricity signal. To solve this problem, an encoder is installed at the end of the roll and the compensation frequency of the roller eccentricity signal is determined in the roller eccentricity compensation system according to the pulse number output. The results of simulations and experiments show that roll eccentricity signals extracted using the proposed method can effectively remove the influence of interference signals. An average improvement of 62.3% in the roll eccentricity compensation effect was achieved under the stable rolling condition in the finishing rolling stage.

This work deals with the simulation model of multi-machines system as cold rolling mill is considered as application. Drivers of rolling system are a set of DC motors, which have extend applications in factories as aluminum rolling. Interconnection of multi DC motors in such a way that they are synchronized in their rotational speed. In cold rolling, the accuracy of the strip exit thickness is a very important factors. To realize accuracy in the strip exit thickness, Automatic Gauge Control system is used. In this paper MATLAB/SIMULINK models are proposed and implemented for the entire structures. Simulation results were presented to verify proposed model of cold rolling mill

To reduce longitudinal gauge deviations of the head sections at the hot strip mill rolling it is reasonable to profile band of variable thickness due to the length provided by the linear motion of the screw-down arrangements under load. The paper considers the structure of the automatic gauge control system (ACGS) of the indirect type. It estimates the accuracy of screw-down arrangement position control in the single-loop automatic position control system. It also justifies the use of automatic position combined control system. The introduction of the additional channel of control due to the first derivative of the reference input signal was proved to provide the required accuracy values of the strip gauge control. The paper presents data of the pilot study of the developed system at OJSC Magnitogorsk Iron and Steel Works' mill 2,000; they confirm its efficiency.

Distributed generators based on wind and solar energy will give prominent momentum in near future [1]. A microgrid consists of group of loads and distributed generators that operate as a single controllable system. The microgrid concept introduces hybrid AC/DC microgrid which reduces multiple reverse conversions in an individual AC or DC grid. This project aims at providing a reliable control system for integrating small renewable power generating units with main grid. The control system designed in this work consist of inner current loop and outer voltage control loop collectively known as Multiloop current voltage PI control system. In this work the performance of the hybrid AC/DC microgrid is analysed by using this control system along with d-q Transformation. This method is implemented for the converters to properly co-ordinate the AC sub-grid and DC sub-grid. The circuits with the proposed method are modeled and simulated by using the MATLAB/ SIMULINK. The results show that with this technique, phase and frequency of the converters are synchronised with that of the utility grid. Hence the reactive power in the transmission line is reduced‥ As the reactive power is reduced, we obtain a stabilized output power which is transmitted to the loads and utility grid by using the above proposed method.

In strip rolling, hydraulic automatic gauge control (HAGC) system is the key element to guarantee the precision of strip gauge. The stability of the kernel pressure closed loop (PCL) in the HAGC system plays an essential role in guaranteeing the rolling process with high performance. Nevertheless, there is some difficulty in exploring the instability mechanism of the HAGC system due to the fact that the PCL is a representative nonlinear closed‐loop control system. In this work, for each component of the HAGC system, the mathematical model was established. And on the basis of the linking relation of various elements, we derived the incremental transfer model of the PCL system. Furthermore, in accordance with the deduced information transfer relation, the transfer block diagram of disturbing variable of the PCL system was obtained. Moreover, for the purpose of deriving the instability condition of the PCL system, the Popov frequency criterion was employed. The instability conditions of the HAGC system were obtained under PCL control. Furthermore, the derived instability conditions of the HAGC system were experimentally verified under various working conditions. The research results provide a fundamental foundation for studying the instability mechanism of the HAGC system.

Time delays are ubiquitous in control systems. They usually enter because of the sensors and actuators used in them. Traditionally, time delays have been thought to have a deleterious effect on both the stability and the performance of controlled systems, and much research has been done in attempting to eliminate them, compensate for them, or nullify their presence. In this paper we take a different view. We investigate whether purposefully injected time delays can be used to improve both the system's stability and performance. Our analytical, numerical, and experimental investigation shows that this can indeed be done. Analytical results of the effects of time delays on collocated and non‐collocated control of classically damped and non‐classically damped systems are given. Experimental and numerical results confirm the theoretical expectations. Issues of system uncertainties and robustness of time delayed control are addressed. The results are of practical value in improving the performance and stability of controllers because these characteristics (performance and stability) improve dramatically with the intentional injection of small time delays in the control system. The introduction of such time delays constitutes a ‘minimal change’ to a controller already installed in a structural system for active control. Hence, from a practical standpoint, time delays can be implemented in a nearly costless and highly reliable manner to improve control performance and stability, an aspect that cannot be ignored when dealing with the economics and safety of large structural systems subjected to strong earthquake ground shaking. Copyright © 2003 John Wiley & Sons, Ltd.

The paper introduces the principle of traditional PID algorithm, analyzes its advantages and disadvantages, and proposes a new control scheme — variable structure fuzzy neural network for such a nonlinear and complex system of automatic Gauge control (AGC). Variable structure fuzzy neural network combines the advantages of neural network and fuzzy control, and also adds a genetic algorithm to optimize various parameters. According to the experimental conditions, the second-order model of the cold-rolling thickness control is selected as the experimental object, and the MATLAB simulation is carried out: compared with the traditional PID control results, we can see that the variable structure fuzzy neural network optimized by clonal algorithm is superior to the other side, whether it is dynamic performance or static performance, and further validates the feasibility and practicability of fuzzy neural network.

Integrated Active Front Steering and Semiactive Rear Differential Control in Rear Wheel Drive Vehicles

The automation control system to plate production line is developed independently. The whole system is divided into several levels and control functions are put into effect by the basic automation system, process automation system and human-machine-interface (HMI) system. Plate production thickness accuracy depends on the Automatic Gauge Control (AGC) function in the basic automation system for the plate mill area. With date communication module, process tracking module, data management module, and model calculation module, the core process model setup function is implemented by process automation system. Process monitoring and operation are implemented by HMI system. This automation control system proposed here has been applied successfully to several plate production lines in China with a good effect.