International Journal of System Control and Information Processing (9 papers in press)
Enhanced Process Monitoring via Time Space Coordinated-Locality Preserving Projection
by Jian Yang, Hongbo Shi
Abstract: In this paper, a novel dimensionality reduction method, time space coordinated-locality preserving projections (TSCLPP) is proposed based on locality preserving projection (LPP). In practical process, except the data correlation in spatial scale, there exists data correlation in time scale as well for the short sampling interval. To considering the correlation of sampling points in time and spatial scale simultaneously, TSCLPP constructs the adjacency graph by selecting adjacent points in time-sequence and Euclidean distance respectively. Furthermore, the importance of the time-sequential neighbors is measured by the computed weight based on time distance. A dual objective function with a weight index coordinating the relationship between time and space is constructed to compute the transformation matrix. Hotellings T2 and squared prediction error (SPE) are established for process monitoring. A numerical case and the Tennessee-Eastman Process (TEP) are employed for the experimental verification.
Keywords: Dimensionality reduction; Locality preserving projection; Time sequence; Euclidean distance; process monitoring.
An improved K-means algorithm based recognition method for working condition of flotation process
by Yongheng Zhao, Tao Peng
Abstract: In this paper, a recognition method based on an improved k-means algorithm with the priori knowledge of process is proposed for the recognition of flotation working conditions. The proposed method consists of two major stages. In the offline classification stage, the bubble feature of images under different bubble status is first extracted to obtain the dataset. Then the obtained dataset is clustered by the improved k-means algorithm with the priori knowledge. At last, the working condition is classified and their root causes under different bubble status and ore grade are analyzed. In the online recognition stage, the current bubble status is first determined. Then the current working condition is recognized by the classification algorithm with the current ore grade. Finally, the proposed method is verified by the real data from a antimony flotation processes.
Keywords: Froth Flotation; Machine Learning; K-means.
Fuzzy-PI based automatic generation control of two-area interconnected nonlinear power system
by Lal Bahadur Prasad, Barjeev Tyagi, Hari Om Gupta
Abstract: This paper presents the modelling, simulation and performance analysis of automatic generation control (AGC) of two-area interconnected nonlinear power system using fuzzy logic system. Fuzzy control, one of the intelligent control techniques, uses the human expert knowledge to make control decisions. Mamdani fuzzy inference system has been used to tune proportional-integral controller for automatic generation control of two-area interconnected nonlinear power system. To compare the results the conventional integral control is also presented. The simulation of control schemes has been carried by developing MATLAB-SIMULINK models. The simulation results and analysis justify the comparative advantages of fuzzy control method.
Keywords: AGC; area control error; fuzzy control; integral control; nonlinear power system; two-area.
Finite-Time Stability of Discrete-Time Switched Singular Systems with All Unstable Modes
by Yijing Wang, Yanchao Zou, Zhiqiang Zuo
Abstract: The finite-time stability problem of discrete-time switched singular systems consisting of all unstable modes is investigated in this paper. By means of dynamic decomposition technique, the original singular system is converted to a reduced-order normal discrete-time switched system. Following the idea of getting into each unstable\r\nmode, its internal behavior is analyzed in detail. Two approaches, namely, the Lyapunov one and the state transition matrix one, are utilized to design the switching law with mode-dependent average dwell time such that the finite-time stability property is guaranteed. It is shown that each of them has its own advantages. Selecting appropriate one depends on the specific object for study. In addition, the corresponding asymptotic stability criteria can be easily derived as a by-product. Finally, two examples are given to verify the obtained results and illustrate the effectiveness of the proposed strategies.
Keywords: Discrete-time switched singular systems; finite-time stability; asymptotic\r\nstability; mode-dependent average dwell time (MDADT); unstable modes; state transition matrix approach.
Quasi min-max model predictive control for Hammerstein system over networks with packet losses
by Na Liu, Xiaoming Tang, Shuang Yang
Abstract: In this paper, a constrained Model Predictive Control (MPC) approach is presented for the Networked Control Systemsrn(NCSs) containing Hammerstein nonlinearity and bounded packet losses. The Hammerstein nonlinearity is partially removedrnby establishing its pseudo inverse, and the remaining weaker nonlinearity is tackled by the polytopic description. The model ofrnNCS is constructed on the standpoint of robust control, which transforms the stabilization of the control systems with packetrnlosses into the stabilization of a set of subsystems. The constrained networked MPC approach is given by parameterizing therninfinite horizon control moves into a free control move followed by a state feedback law which the input and state constraintsrnare explicitly considered. Compared with the networked MPC without free control move, the presented approach improves therncontrol performance of the closed-loop system, which is verified by a comparison simulation example.
Keywords: Model Predictive Control; Networked Control Systems; Hammerstein model; bounded packet losses.
Prediction of the Product Formation with the AdaBoost Algorithm in Bioprocesses
by Lei Cui
Abstract: The state variables such as product formation could provide important information for the optimization of fermentation processes. Since the kinetic modeling is difficult for bioprocesses, the product formation is predicted by integrating support vector machine (SVM) with the AdaBoost algorithm. The AdaBoost algorithm is used for adaptively boosting the performance of SVM weak learners. The prediction approach is tested by using 2-keto-L-gulonic acid (2-KGA) cultivation as an example. The validation results using the data from industrial 2-KGA cultivation demonstrate that the prediction approach has good generalization performance and noise tolerance.
Keywords: support vector machine; fermentation process; AdaBoost; prediction.
Cross-layer Transmission Design in a Class of Delay-Aware Two-User Interference Networks
by Muhu Li, Ping Wang, Chao Wang, Fuqiang Liu, Yusheng Ji
Abstract: This paper investigates the transmission design problem in a class of two-user interference networks where each source sends two types of delay-sensitive message to its destination. The first type is generated periodically with fixed rate and is desired to be delivered immediately with sufficiently high reliability. The second type, generated randomly, can be placed in queues but the average queueing delay should be finite. Each user applies point-to-point Gaussian random codes to transmit information, using constrained instantaneous and average powers. We utilize the Lyapunov optimization theory to construct a cross-layer transmission strategy, which can adapt to both the channel state information (CSI) at the physical layer and the queue state information at the media access control layer. Our results show that the proposed strategy can achieve a better tradeoff among power consumption, transmission reliability, and queueing delay, compared with the conventional CSI-based transmission design.
Keywords: Wireless interference networks; cross-layer transmission design; power allocation; Lyapunov optimization.
Application of Multi-objective Mathematical Programming Technique for Contractor Selection
by Srikumar Acharya, Ankita Nanda
Abstract: In this paper, a multi-objective mathematical model is formulated for contractor selection problem, which is solved taking into consideration various attributes for supplying goods for a University mess in the hostel. For better mathematical model formulation factors like, past performance, financial status, product return policy, time factors etc. of contractors are considered. In order to illustrate the methodology a case 0f one University is considered. A mathematical model is also formulated by considering the data of the mess of the University. Finally, it is solved to select appropriate contractors using fuzzy programming method.
Keywords: Fuzzy Programming Method; Contractor Selection; Multi-Objective Programming Problem.
Nonlinear power control of Variable Speed Wind Turbines above rated wind speed
by Miaomiao Ma
Abstract: This paper proposes a triple-step nonlinear control scheme for variable speed wind turbines above the rated wind speed to maintain the output power at the rated value. The controller design procedure is divided into three parts: steady-state-like control; feedforward control based on reference dynamics; and state dependent feedback control. The gains of controller are state-dependent and parameter-varying. The simulation results for a NREL-offshore-baseline 5 MW wind turbine system show the efficiency of the proposed nonlinear controller.
Keywords: Variable speed wind turbine; pitch control; nonlinear control; rated power.