Hierarchical optimal control of large-scale nonlinear chemical processes

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.     

Sliding mode control: an approach to regulate nonlinear chemical processes

A new approach for the design of sliding mode controllers based on a first-order-plus-deadtime model of the process, is developed. This approach results in a fixed structure controller with a set of tuning equations as a function of the characteristic parameters of the model. The controller performance is judged by simulations on two nonlinear chemical processes.     

基于多级模糊神经网络的故障诊断在化工生产过程中的应用

化工生产过程一般都非常复杂，控制回路与测控参数很多，生产过程的故障检测与诊断问题非常困难。文中提出一种基于神经网络的多级故障诊断系统。采用三级递阶模糊神经网络，降解整个系统故障诊断问题的复杂性，同时采用所有子神经网络全局并行的推理方式，具有快速处理能力，适合系统实时在线故障诊断。     

仿人机器人仰卧-直立构态变化分析

基于GF集理论描述了仿人形机器人的末端特征,分析了机器人的躺构态和站立构态.进行了人躺-站构态变化实验,将这个变化过程用GF集描述为几个简单的动作.根据关节力矩最小,通过对人体实验的分析,得出了躺-站构态变化的最优路径.     

Experimental simulation of chemical reactions between ZDDP tribofilms and steel surfaces during friction processes

Friction tests are performed in a controlled environment (Ultra High Vacuum), between steel surfaces and a ZDDP tribofilm at different contact severities. According to AES analyses, evidence of chemical reactions activated by friction is given. The reaction of the ZDDP tribofilm with the native iron oxide could partially explain its antiwear behavior.     

Control of chemical processes using neural networks: implementation in a plant for xylose production

This work demonstrates the use of artificial intelligence for control of xylose reactor performance in a paper factory. Two types of neural networks are used, a perceptron for the temperature controller and an adaptive formulation for the noise filter. The results show an improvement in the temperature stabilization time with respect to a classic PID control.     

Fault detection and classification in chemical processes based on neural networks with feature extraction

Feed forward neural networks are investigated here for fault diagnosis in chemical processes, especially batch processes. The use of the neural model prediction error as the residual for fault diagnosis of sensor and component is analyzed. To reduce the training time required for the neural process model, an input feature extraction process for the neural model is implemented. An additional radial basis function neural classifier is developed to isolate faults from the residual generated, and results are presented to demonstrate the satisfactory detection and isolation of faults using this approach.     

An integrated material removal model for silicon dioxide layers in chemical mechanical polishing processes

The material removal rate in CMP processes obeys Preston's equation, which can be expressed as a linear function of the applied areal power density under usual operating conditions. However, some experimental results have shown a nonlinear relationship between the CMP material removal rate and the applied areal power density, suggesting non-Prestonian behavior under certain operating regimes. Although the material removal rate is caused by the coupled effect of both mechanical and chemical actions in actual CMP processes, the treatment of the chemical action as a mere supplementary means of softening the surface makes it difficult to explain this non-Prestonian behavior. In this work, we propose an integrated material removal model for silicon dioxide during CMP based on a multiscale mechanical abrasion model coupled with the slurry chemical diffusion effects. The synergetic effects on the material removal mechanism due to both mechanical and chemical actions are incorporated in the model, and the total material removal rate is predicted by accounting for both effects. Consequently, the non-Prestonian behavior often shown in silicon dioxide CMP may be explained using the proposed model. The validity of the model is supported by comparing the predicted material removal rates with experimental values available in the literature.     

Incorporating delayed measurements in an improved high-degree cubature Kalman filter for the nonlinear state estimation of chemical processes

The on-line estimation of process quality variables has a large impact on the advanced monitoring and control techniques of chemical processes. The present study offers an improved high-degree cubature Kalman filter (HCKF) to solve the nonlinear state estimation problem of high-dimensional chemical processes. We substituted the Cholesky decomposition in the HCKF filter with a diagonalization transformation of the matrix. In addition, we enhanced numerical stability and estimation accuracy. On this basis, we present one nonlinear state estimation method based on the sample-state augmentation and improved HCKF to handle issues with delayed measurements. Finally, we used the nonlinear state estimation experiments for the polymerization process to validate the proposed method. The numerical results indicated the achievement of state estimation with higher accuracy and better stability following the effective utilization of the delayed measurements for nonlinear chemical processes.     

New large volume hydrothermal reaction cell for studying chemical processes under supercritical hydrothermal conditions using time-resolved in situ neutron diffraction

The design and testing of a new large volume Inconel pressure cell for the in situ study of supercritical hydrothermal syntheses using time-resolved neutron diffraction is introduced for the first time. The commissioning of this new cell is demonstrated by the measurement of the time-of-flight neutron diffraction pattern for TiO(2) (Anatase) in supercritical D(2)O on the POLARIS diffractometer at the United Kingdom's pulsed spallation neutron source, ISIS, Rutherford Appleton Laboratory. The sample can be studied over a wide range of temperatures (25-450 °C) and pressures (1-355 bar). This novel apparatus will now enable us to study the kinetics and mechanisms of chemical syntheses under extreme environments such as supercritical water, and in particular to study the crystallization of a variety of technologically important inorganic materials.     

Thermodynamic and kinetic analyses of probable chemical reactions in the tribocontact zone and the effect of heavy pressure on evolution of adsorption processes

The paper presents thermodynamic and kinetic analyses of probable chemical reactions and adsorption processes depending on their energy, temperature, and pressure. It is shown that only lubricating adsorption films that appear on the rubbing surfaces due to mechanoactivated reactions can play a significant role in improving the tribological properties of a sliding contact. It is also demonstrated that heavy pressures in the zone of real contact between the asperities of rubbing surfaces enhance equilibrium adsorption of low-molecular-weight additives and of a number of high-molecular-weight additives to fluid lubricants.     

Peculiarities of erosion-corrosion processes

Investigations have been carried out on an erosion-corrosion apparatus to investigate the behaviour of corrosion-resistant highalloy iron-base materials containing hard phases. These materials had been optimized for increased wear resistance under complex stress conditions. As expected, in dry erosion tests, very low mass losses were established; there was little difference between the materials. Also, in corrosive environments (NaCl, H₂SO₄), the materials showed good stability; however, the duplex structures were superior to the martensitic ones. The combination of erosion and corrosion produced large differences and, in some cases, markedly reduced resistance to damage. These results confirmed observations that it is impossible to deduce the environmentally influenced mechanical behaviour of an alloy from its behaviour in separate corrosion and erosion experiments. The basic mechanisms underlying these processes have been investigated only tentatively.     

Optimization of cutting processes

Known criteria for the optimization of cutting processes are appraised. A new criterion for determining the optimal conditions in metal cutting is proposed.     

Satic states of cohesive granular media

This paper investigates the influence of cohesion on the behavior of 2D granular media simulated by using a molecular dynamics method, involving a simple contact law with adhesion. The study considers an adhesion index which is non intrinsic but significant for interpreting the mechanical effects of applied pressure. A static state system of 4000 particles is numerically simulated by oedometrical compression under a constant force, without gravity. The results show how the geometrical texture and the network of contact forces change according to the level of adhesion. This effect is explained essentially in term of the increase in the number of the tensile contacts and by the development of the internal self-stress structure. As in the case of non cohesive granular media, a high spatial heterogeneity of the contact forces is observed.