Two-degree-of-freedom output feedback controllers for discrete-time nonlinear systems

A discrete-time, model-based output feedback control structure for nonlinear processes is developed in the present work. The structure makes use of a closed-loop observer, while at the same time it guarantees that the overall feedback controller possesses integral action. An algebraic transformation is applied on the observer states to insure that the input/output gain of the observer matches the model upon which the static state feedback control law is based. The resulting control algorithm is a two-degree-of-freedom control law, in the sense that the output and the set point are processed in different ways. The control structure is shown not only to have the same properties as the standard model-state feedback structure, but also that it emerges from a model algorithmic control framework. Finally, a simulation example using an exothermic CSTR operating at an open-loop unstable steady state is used to evaluate the closed-loop performance of the proposed method.     

Thermal Generation of Residual Stress Fields for Purpose of Distortion Minimization

Thermal treatments of steel components with the goal of hardening often result in distortion by releasing the residual stresses which were brought into the specimen during the preceding processing steps. The goal of the presented work is the minimization of this distortion. By generating definite residual stress fields and investigating the resulting distortion, the distortion mechanism can be observed in detail. A flexible and reproducible way to generate such residual stress fields inside a specimen is by means of local thermal treatment with a laser beam. Computer simulations as well as experiments were carried out using an idealized tooth of a gearwheel (finger sample) as a model system. The deformation of the samples due to the laser heat treatment and the stress fields generated inside the samples were determined with respect to different process parameters.     

Optimal control and operation of drum granulation processes

Process optimisation and optimal control of batch and continuous drum granulation processes are studied in this paper. The main focus of the current research has been: (i) construction of optimisation and control relevant, population balance models through the incorporation of moisture content, drum rotation rate and bed depth into the coalescence kernels; (ii) investigation of optimal operational conditions using constrained optimisation techniques; (iii) development of optimal control algorithms based on discretized population balance equations; and (iv) comprehensive simulation studies on optimal control of both batch and continuous granulation processes. The objective of steady state optimisation is to minimise the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation-rate, bed depth (material charge), and moisture content of solids are practical decision (design) parameters for system optimisation. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray-rate is the most effective control (manipulative) variable. Although other possible manipulative variables, such as feed flow-rate and additional powder flow-rate have been investigated in the complete research project, only the single input problem with the binder spray rate as the manipulative variable is addressed in the paper to demonstrate the methodology. It can be shown from simulation results that the proposed models are suitable for control and optimisation studies, and the optimisation algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational conditions and dynamic trajectories with good convergence properties.     

Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor

Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was used to classify the experimental cutting force data of milling operations previously. Preprocessing (PreP) of the approximation coefficients of the WT is proposed just before the classification by using the Adaptive Resonance Theory (ART2) type NNs. Genetic Algorithm (GA) was used to estimate the weights of each coefficient of the PreP. The WT-PreP-NN (ART2) combination worked at lower vigilances by creating only a few meaningful categories without any errors. The WT-NN (ART2) combination could obtain the same error rate only if very high vigilances are used and many categories are allowed.     

层次分析法在工程评标中的应用

根据评标工作多层次多准则的特点,将层次分析方法引入工程评标中,并结合工程实例介绍了方法的具体运用。实践表明,层次分析法思路清晰,方法简便,能减少主观因素的影响,评价结果准确,是一种实用的工程评标方法。     

排序聚类分析算法在派生式CAPP系统中的应用及实现

利用零件的相似性原理对零件分组是派生式CAPP系统的重要内容,对零件的分组是否合理,直接影响到派生式CAPP系统能否正常运行。阐述了排序聚类分析算法在生产流程分析法中的工作原理,分析了利用该算法实现零件分组的实现过程,并用示例验证了该算法。     

城市排水系统集成模拟研究进展

在回顾城市排水系统集成模拟研究发展和现状的基础上,结合可持续性城市排水系统理论,分析了现阶段城市排水系统集成模拟研究的局限和面临的问题。为了适应城市排水系统结构和功能的演变,实现系统的可持续性,今后城市排水系统集成模拟的研究应当完善对系统结构的描述,在集成模拟的过程中考虑不确定性因素对系统的影响,并构建高效能计算平台,解决城市排水系统大规模计算问题。     

国外几种脱硫醇工艺技术

硫醇是一种易挥发、有毒、腐蚀活性强的物质，在环保要求越来越严格的今天，必须将原油和凝析气中的硫醇加以脱除，才能达到环保要求。文章介绍了目前世界上采用的几种脱硫醇工艺。     

集成电路的现状及其发展趋势

集成电路是信息社会经济发展的基石。通过对集成电路发展规律的分析,从集成电路的设计、制造、新产品研发和市场动态等方面,描述了集成电路的最新动态;探讨了集成电路的发展趋势;指出集成电路与其它学科、技术的结合,不断形成新的研究方向;新材料、新结构、新器件不断涌现,特征尺寸继续缩小,摩尔定律仍然起作用。     

非织造布印花技术探讨

介绍了应用于非织造布印花的技术及工艺，对非织造布印花时应注意的事项进行了说明。