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Zhang W.,Yanshan University | Zhang W.,China Institute of Technology | Niu P.,Yanshan University | Niu P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | And 4 more authors.
Knowledge-Based Systems | Year: 2013

Accurate heat rate forecasting is very important in ensuring the economic, efficient, and safe operation of a steam turbine unit. The support vector machine (SVM) is a novel tool from the artificial intelligence field that has been successfully applied to heat rate forecasting. The least squares SVM (LS-SVM) is an improved algorithm based on the SVM. LS-SVM has minimal computational complexity and fast calculation. However, traditional LS-SVM, which was established by using offline data samples, can no longer accurately describe the actual system working condition, thereby resulting in problems when directly used in heat rate prediction. In this paper, a heat rate forecasting method based on online LS-SVM, which possesses dynamic prediction functions, is proposed. To avoid blindness and inaccuracy in parameter selection, the gravitational search algorithm (GSA) is used to optimize the regularization parameter γ and the kernel parameter σ2 of the online LS-SVM modeling. The results confirm the efficiency of the proposed method. © 2012 Elsevier B.V. All rights reserved.


Li G.,Yanshan University | Li G.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Niu P.,Yanshan University | Niu P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | And 3 more authors.
Applied Soft Computing Journal | Year: 2012

In this paper, we propose a new combination modeling method whose structure consists of three components: extreme learning machine (ELM), adaptive neuro-fuzzy inference system (ANFIS) and PS-ABC which is a modified hybrid artificial bee colony algorithm. The combination modeling method has been proposed in an attempt to obtain good approximations and generalization performances. In the whole model, ELM is used to build a global model, and ANFIS is applied to compensate the output errors of ELM model to improve the overall performance. In order to obtain a better generalization ability and stability model, PS-ABC is adopted to optimize input weights and biases of ELM. For stating the proposed model validity, it is applied to set up the mapping relation between the boiler efficiency and operational conditions of a 300 WM coal-fired boiler. Compared with other combination models, the proposed model shows better approximations and generalization performances. © 2012 Elsevier B.V.


Li G.,Yanshan University | Li G.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Niu P.,Yanshan University | Niu P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | And 3 more authors.
Knowledge-Based Systems | Year: 2012

In this paper, we present a new method based on echo state network (ESN) to control discrete chaotic systems. ESN could achieve very high precision in chaotic time series prediction and overcome most issues encountered in using traditional artificial neural networks, especially local minima and overfitting. In order to achieve good control effect when there is noise in chaotic systems, an adaptive noise canceler is introduced to eliminate the effect of the noise and perturbation. The support vector machine (SVM) is adopted to identify inverse model of the controlled plant as the adaptive noise canceler. Simulation results show that the proposed method could achieve very good control effect, possess a good stability and completely reduce the adverse effect. © 2012 Elsevier B.V. All rights reserved.


Tang Y.,Yanshan University | Tang Y.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Cui M.,Yanshan University | Hua C.,Yanshan University | And 4 more authors.
Expert Systems with Applications | Year: 2012

Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using chaotic ant swarm (CAS) optimization method. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. CAS algorithm, a newly developed evolutionary algorithm inspired by the chaotic behavior of individual ant and the self-organization of ant swarm, is used as the optimizer to search the best parameters of FOPID controller. The designed CAS-FOPID controller is applied to an automatic regulator voltage (AVR) system. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the CAS-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties. © 2011 Elsevier Ltd. All rights reserved.


Yang L.P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Yu B.Q.,Yanshan University
Applied Mechanics and Materials | Year: 2013

In the process of measuring the shape of the cold rolling strip, by combining proportion compensation with slope compensation, the signal error of edge shape should be compensated reasonably. In addition, corresponding solutions are proposed to solve the channel signal loss or the discontinuous transverse shape value which takes place occasionally in the shape measuring roller. These solutions could improve the stability of shape measuring signal, avoid serious accidents of controlling mill caused by abnormal shape signals and achieve reliable shape control without worries. © (2013)Trans Tech Publications,Switzerland.


Li G.,Yanshan University | Niu P.,Yanshan University | Niu P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Ma Y.,Yanshan University | And 2 more authors.
Knowledge-Based Systems | Year: 2014

In this paper, a novel optimization technique based on artificial bee colony algorithm (ABC), which is called as PS-ABCII, is presented. In PS-ABCII, there are three major differences from other ABC-based techniques: (1) the opposition-based learning is applied to the population initialization; (2) the greedy selection mechanism is not adopted; (3) the mode that employed bees become scouts is modified. In order to illustrate the superiority of the proposed modified technique over other ABC-based techniques, ten classical benchmark functions are employed to test. In addition, a hybrid model called PS-ABCII-ELM is also proposed in this paper, which is combined of the PS-ABCII and Extreme Learning Machine (ELM). In PS-ABCII-ELM, the PS-ABCII is applied to tune input weights and biases of ELM in order to improve the generalization performance of ELM. And then it is applied to model and optimize the thermal efficiency of a 300 MW coal-fired boiler. The experimental results show that the proposed model is very convenient, direct and accurate, and it can give a general and suitable way to predict and improve the boiler efficiency of a coal-fired boiler under various operating conditions. © 2014 Elsevier B.V. All rights reserved.


Li G.,Yanshan University | Li G.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Niu P.,Yanshan University | Niu P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling
Neural Computing and Applications | Year: 2013

The extreme learning machine (ELM) is a novel single hidden layer feedforward neural network, which has the superiority in many aspects, especially in the training speed; however, there are still some shortages that restrict the further development of ELM, such as the perturbation and multicollinearity in the linear model. To the adverse effects caused by the perturbation or the multicollinearity, this paper proposes an enhanced ELM based on ridge regression (RR-ELM) for regression, which replaces the least square method to calculate output weights. With an additional adjustment of ridge regression, all the characteristics become even better. Simulative results show that the RR-ELM, compared with ELM, has better stability and generalization performance. © 2011 Springer-Verlag London Limited.


Li J.-X.,Yanshan University | Fang Y.-M.,Yanshan University | Fang Y.-M.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Shi S.-L.,Yanshan University
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | Year: 2012

A robust output-feedback control algorithm with unknown input observer is presented for the hydraulic servo-position system in a cold-strip rolling mill with uncertain parameters, immeasurable states and unknown external load forces. The disturbance term containing the unknown external load forces is regarded as an unknown input, for which we build an observer. A robust output-feedback controller is then designed with this observer. Theoretical analysis shows that the resulting closed-loop system is uniformly bounded stable, and has robust H-infinity performance. A simulation is carried out on the hydraulic servo position system of a 650mm reversing cold-strip mill, results show the validity of the proposed algorithm.


Ma Y.,Yanshan University | Ma Y.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Niu P.,Yanshan University | Niu P.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling
Advances in Information Sciences and Service Sciences | Year: 2012

Over the decade, due to the fact that the global energy resources are in deadly shortage, much emphasis is put on the energy consumption in thermal power throughout the world. Following developed is Circulating Fluidized Bed Boiler (CFBB) in recent years, a kind of combustion boiler that can clean and desulfurize the coal efficiently in the combustion process. Circulating Fluidized Bed Boiler (CFBB) is a control object with features of time varying parameters, large delay, and multivariable control tightly coupled. Noticeably, many factors influence the combustion process. This paper designs a three level ART2-BP-BP of data fusion--fusion cluster control system based on methods of multi-sensor information fusion and cluster analysis. It completes data fusion from the data level, the feature level to the decision level. Especially, the concept of Situation Threat Space aiming at the potential threats in CFBB is presented. Results of simulation show that the control system in this paper is feasible and effective, in particular, the control system still has more satisfactory control effect in the case of a variety of sensor failures.


Li J.-X.,Yanshan University | Fang Y.-M.,Yanshan University | Fang Y.-M.,National Engineering Research Center for Equipment and Technology of Cold Strip Rolling | Shi S.-L.,Yanshan University
Kongzhi yu Juece/Control and Decision | Year: 2013

An anti-windup-based robust dynamic output feedback control algorithm is presented for hydraulic servo position system with unmeasurable states, uncertain parameters and input saturation in a rolling mill. Firstly, a sufficient condition of stability can be transformed into a linear matrix inequality(LMI) condition by using Finsler's lemma, and the controller parameter matrices are obtained by solving LMIs; Secondly, by compromising the disturbance attenuation and stability region, the anti-windup matrix is obtained by solving a convex optimization problem. It can be proved that the proposed method can guarantee the closed-loop system is uniformly bounded stable and possesses robust H∞ performance. Finally, a simulation is carried out on the hydraulic servo position system of 650mm reversing cold-strip rolling mill, the simulation results show the validity of the proposed algorithm.

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