CMAC BASED NONLINEAR PROCESS CONTROL SYSTEMS,PART I : CMAC WITH GENERAL BASIS FUNCTIONS FOR MODELLING

ＣＭＡＣＢＡＳＥＤＮＯＮＬＩＮＥＡＲＰＲＯＣＥＳＳＣＯＮＴＲＯＬＳＹＳＴＥＭＳ，ＰＡＲＴＩ：ＣＭＡＣＷＩＴＨＧＥＮＥＲＡＬＢＡＳＩＳＦＵＮＣＴＩＯＮＳＦＯＲＭＯＤ－ＥＬＬＩＮＧＤｕａｎＰｅｉｙｏｎｇ（段培永）ＬｉＣｈｅｎｇｄｏｎｇ（李成东）ＳｈａｏＨ...     

Robust Predictive Control for Polytopic Uncertain Systems with Time-delay Subjected to Actuator Saturation

Robust predictive control algorithms were presented for polytopic uncertain linear discrete systems with time-delay subjected to actuator saturation. In the first algorithm, the parameter dependent state feedback model predictive control (MPC) law was obtained from minimizing the upper bound of the cost function subjected to several linear matrix inequality constraints. In order to reduce computation burden, a second robust MPC algorithm based on nominal performance cost was presented. The feasibility of the optimization problems guarantees that the algorithms are robustly stable. The simulation results verify the effectiveness of the proposed algorithms.     

Improved Learning Algorithm of Hyperball CMAC and Its Convergence Analysis

An improved learning algorithm for hyperball CMAC was presented. Only one parameter is needed to determine the learning rate, and the parameter can be obtained by a self-optimizing method. The convergence of the improved learning algorithm was proved. The simulation research shows that the learning speed and the learning accuracy are both improved.     

RESEARCH ON THE DYNAMIC MATHEMATICAL MODEL OF REHEATING FURNACE

Introduction　　With the increasing global competition amongsteel companies,the enhancement of productivityof the process has become an essential task to sur-vive and succeed in the world trade market.Due tothe energy consumption of furnaces accounting fora large percent in steel plants,it has been a trendto improve the heating quality of slab in the fur-nace and reduce the energy consumption as can aspossible. Owing to:(a) the many different typesof slabs to be processed,(b) the strong intera…     

PASSIVE CONTROL FOR A CLASS OF UNCERTAIN TIME-DELAY SYSTEMS

Introduction　　 Control of time- delay systems has been an at-tractive field in control theory and applicationssince the time- delay systems are frequently en-countered in the real world.They are much differ-ent from their non- delay counterparts.For exam-ple,it is well known that the existence of delaysmay degrade the respond of the closed- loop sys-tems,or even induce instability[1] .Hence,theavailable results of non- delay sytems can notbe di-rectly applied to time- delay systems in genera…     

Nonlinear Statistical Process Monitoring Based on Control Charts with Memory Effect and Kernel Independent Component Analysis

A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.     

MODIFIED AUTOMATIC TUNING OF PI/D CONTROLLERS BASED ON PHASE AND AMPLITUDE MARGIN SPECIFICATIONS

ＩｎｔｒｏｄｕｃｔｉｏｎＩｎｐｒｏｃｅｓｓｃｏｎｔｒｏｌ，ｍｏｒｅｔｈａｎ９５％ｏｆｔｈｅｃｏｎｔｒｏｌｌｏｏｐｓａｒｅｏｆＰＩＤｔｙｐｅ［１］．Ｔｈｅｍａｉｎｒｅａｓｏｎｉｓｉｔｓｒｅｌａｔｉｖｅｌｙｓｉｍｐｌｅｓｔｒｕｃｔｕｒｅ，ｗｈｉｃｈｃａｎｂｅｅａｓｉｌｙｕｎｄｅｒｓｔｏｏｄａｎｄｉｍｐｌｅｍｅｎｔｅｄｉｎｐｒａｃｔｉｃｅ，ａｎｄｔｈａｔｍａｎｙｓｏｐｈｉｓｔｉｃａｔｅｄｃｏｎｔｒｏｌｓｔｒａｔｅｇｉｅｓ，ｓｕｃｈａｓｍｏｄｅｌｐｒｅｄｉｃｔｉｖｅｃｏｎｔｒｏｌ，ａｒｅｂａｓｅｄｏｎｉ…     

Constrained Run-to-Run Optimization for Batch Process Based on Support Vector Regression Model

Introduction Batch and semi-batch processes are very im-portant in the fine chemicals industry to manufac-ture the low-volume and high-value products suchas biochemicals, crystals and speciality chemicals.In the control of batch process, the major objectiveis to improve the end-of-batch product properties.When the control objective is to optimize a perfor-mance index at the end of batch cycle, the problemis called the end-point optimization problem. Tosolve the problem,the traditional approach…     

CMAC BASED NONLINEAR PROCESS CONTROL SYSTEMS,PART Ⅱ:CONTROLLER DESIGN

，ＰＡＲＴ Ⅱ：ＣＯＮＴＲＯＬＬＥＲ ＤＥＳＩＧＮTX＠段培永＠李成东＠邵惠鹤ＩｎｔｒｏｄｕｃｔｉｏｎＩｎｒｅｃｅｎｔｙｅａｒｓ，ＮｅｕｒａｌＮｅｔｗｏｒｋｓ（ＮＮｓ）ｈａｖｅｆｏｕｎｄｇｒｏｗｉｎｇｓｕｃｃｅｓｓｉｎｄｉｖｅｒｓｅｉｎｉｎｄｕｓｔｒｉａｌｃ?..     

On-line Batch Process Monitoring and Diagnosing Based on Fisher Discriminant Analysis

Introduction Nowadays, it has been paying more attentionto the batch or semi-batch process which producedthe high added value and high quality products inchemical industry, such as polymer, pharmaceuti-cal and semiconductor industry.The aim of the batch process monitoring is tokeep the product quality uniform and consistentunder batch-to-batch process and meet specifica-tion limits. The direct approach is to monitor cru-cial product quality variables in batch process.However, quality variables…