Welding current and arc voltage control in a GMAW process using ARMarkov based MPC

A predictive functional controller based on ARMarkov model structure has been designed to control welding current and arc voltage in a GMAW process. The closed loop system performance is investigated through computer simulations and is compared by those achieved from implementing two commonly used controllers i.e. PI and feedback linearization based PID. The local stability of the closed loop system is analyzed in the presence of uncertainties in the linearized model of the process as well as the control parameters. Finally it is shown that the proposed controller performs like a PI controller along with a pre-filter compensator.     

An effective 3-in-1 keyword search method over heterogeneous data sources

Conventional keyword search engines are restricted to a given data model and cannot easily adapt to unstructured, semi-structured or structured data. In this paper, we propose an efficient and adaptive keyword search method, called EASE, for indexing and querying large collections of heterogeneous data. To achieve high efficiency in processing keyword queries, we first model unstructured, semi-structured and structured data as graphs, and then summarize the graphs and construct graph indices instead of using traditional inverted indices. We propose an extended inverted index to facilitate keyword-based search, and present a novel ranking mechanism for enhancing search effectiveness. We have conducted an extensive experimental study using real datasets, and the results show that EASE achieves both high search efficiency and high accuracy, and outperforms the existing approaches significantly.     

Countering the loss of extended vigilance in supervisory control using a fuzzy logic model

When an operator first detects unusual and/or infrequent or irregular signals in a system, the operator does not need to take any action, but must increase his/her level of attention and be alert for any more serious signals that may confirm a problem with the system. This is referred to as extended vigilance. The purpose of this study was to construct a fuzzy vigilance-measuring model for countering the loss of extended vigilance. The model extends two-valued logic (“Yes” or “No”) to multi-valued logic through fuzzy sets. Then a fuzzy logic alarm was developed by the model for combating the extended vigilance decrement. The first experiment compared the effect of the fuzzy measuring model with signal detection theory (SDT) and discussed the relationship between preliminary and extended vigilance for a simulated feed-water monitoring system. The results indicated that the sensitivity of the fuzzy vigilance-measuring model is better than index d′ and β, and that the preliminary vigilance significantly influences the extended vigilance. The second experiment verified the effect of the fuzzy logic alarm. The results indicated that the effect of the fuzzy logic alarm for combating the extended vigilance decrement is significant. When the preliminary vigilance is poor, an appropriate alarm will improve the extended vigilance. However, if the preliminary vigilance is very poor, the improvement of the extended vigilance will be limited.Relevance to industry: The extended vigilance is a new and important issue in human performance problems in industry, particularly in such areas as air-traffic control, industrial inspection and power plant monitor. The measuring model of vigilance could be applied to develop an alarm for promoting supervisory performance of human and human–machine detectors.     

Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.     

Robust adaptive fuzzy logic power system stabilizer

This paper introduces a robust adaptive fuzzy controller as a power system stabilizer (RFPSS) used to damp inter-area modes of oscillation following disturbances in power systems. In contrast to the IEEE standard multi-band power system stabilizer (MB-PSS), robust adaptive fuzzy-based stabilizers are more efficient because they cope with oscillations at different operating points. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, components that ensure robust and adaptive performance are included in the control law to compensate for modelling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearities. The second system is an adaptive one that compensates for modelling errors. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.     

反馈线性化在液压型风力发电机组功率追踪中的应用

以液压型风力发电机组为研究对象,为使功率追踪的过程平稳,研究机组的最佳功率追踪控制方法.本文利用反馈线性化方法解决系统非线性问题,以液压系统压力为控制输出,设计最佳功率追踪控制器,并提出一种反馈线性化方法的工程应用解决方案,即结合传统PID控制解决反馈线性化工程应用中依赖模型参数精度的问题.依托30 k VA液压型风力发电机组半物理仿真实验台进行仿真和实验研究,验证了该方法的可行性,为机组进一步研究奠定理论与实验基础.     

异步电机反馈线性化二阶滑模定子磁链观测器设计

为了提高异步电机定子磁链的观测精度,提出了基于反馈线性化的二阶滑模磁链观测方法,设计了定子磁链观测器,并应用到异步电机直接转矩控制中.为更准确的观测磁链,选取转子磁链为系统输出,运用微分几何理论将异步电机系统的输入/输出线性化,得到以转子磁链为输出的异步电机反馈线性化模型.在此基础上设计基于Super-twisting算法的二阶滑模转子磁链观测器,实现对转子磁链的准确估算,并对所设计的观测器进行稳定性分析.然后再利用转子磁链与定子磁链的关系,估算出定子磁链.将该观测器用于异步电机直接转矩控制中,达到了很好的控制效果.仿真与实验结果验证了该方法的可行性和有效性.     

运输机低空重装空投增益自适应滑模控制

本文针对带有不确定性且不确定性边界未知的低空重装备空投过程控制问题,提出了基于增益自适应全局滑模的飞行控制方法.该方法采用反馈线性化技术对重装空投过程模型进行线性化,解决了空投模型的强非线性问题,在此基础上,设计了切换增益自适应全局滑模控制器,保证了系统在响应全程的鲁棒性,克服了滑模到达阶段系统初始误差对切换增益自适应过程的影响.提出了一种改进的增益自适应方法,解决了滑动阶段的切换增益过度自适应问题.基于Lyapunov理论证明了控制器的稳定性和鲁棒性.仿真验证了控制方法的控制性能和优越性.     

一类非线性系统的奇异点克服控制

针对一类非线性系统, 研究存在奇异点时的跟踪控制问题. 在采用反馈线性化方法将对象转换成标准型后, 构造线性补偿器并结合期望轨迹的高阶导数构成伪控制量. 通过引入梯度动力学方法求解控制律, 以克服在控制过程中遇到的奇异点问题. 通过稳定性分析验证了闭环系统的稳定性和跟踪误差的收敛性. 仿真结果表明, 此类控制器具有良好的控制性能, 并且能有效克服奇异点问题.

     

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

This paper proposes an approach for Inertial Measurement Unit sensor fault reconstruction by exploiting a ground speed-based kinematic model of the aircraft flying in a rotating earth reference system. Two strategies for the validation of sensor fault reconstruction are presented: closed-loop validation and open-loop validation. Both strategies use the same kinematic model and a newly-developed Adaptive Two-Stage Extended Kalman Filter to estimate the states and faults of the aircraft. Simulation results demonstrate the effectiveness of the proposed approach compared to an approach using an airspeed-based kinematic model. Furthermore, the major contribution is that the proposed approach is validated using real flight test data including the presence of external disturbances such as turbulence. Three flight scenarios are selected to test the performance of the proposed approach. It is shown that the proposed approach is robust to model uncertainties, unmodeled dynamics and disturbances such as time-varying wind and turbulence. Therefore, the proposed approach can be incorporated into aircraft Fault Detection and Isolation systems to enhance the performance of the aircraft.