Predictive compensation for variable network delays and packet losses in networked control systems

Networked control systems (NCSs) offer many advantages over conventional control; however, they also demonstrate challenging problems such as network-induced delay and packet losses. This paper proposes an approach of predictive compensation for simultaneous network-induced delays and packet losses. Different from the majority of existing NCS control methods, the proposed approach addresses co-design of both network and controller. It also alleviates the requirements of precise process models and full understanding of NCS network dynamics. For a series of possible sensor-to-actuator delays, the controller computes a series of corresponding redundant control values. Then, it sends out those control values in a single packet to the actuator. Once receiving the control packet, the actuator measures the actual sensor-to-actuator delay and computes the control signals from the control packet. When packet dropout occurs, the actuator utilizes past control packets to generate an appropriate control signal. The effectiveness of the approach is demonstrated through examples.

Network protocols and predictive control strategies for distributed real-time control applications

A trend in design and implementation of modern industrial automation systems is to integrate computing, communication and control into a unified framework at different levels of machine/factory operations and information processing. These distributed control systems are referred to as networked control systems (NCSs). They are composed of sensors, actuators, and controllers interconnected over communication networks. As most of communication networks are not designed for NCS applications, the communication requirements of NCSs may be not satisfied. For example, traditional control systems require the data to be accurate, timely and lossless. However, because of random transmission delays and packet losses, the control performance of a control system may be badly deteriorated, and the control system rendered unstable. The main challenge of NCS design is to both maintain and improve stable control performance of an NCS. To achieve this, communication and control methodologies have to be designed. In recent decades, Ethernet and 802.11 networks have been introduced in control networks and have even replaced traditional fieldbus productions in some real-time control applications, because of their high bandwidth and good interoperability. As Ethernet and 802.11 networks are not designed for distributed control applications, two aspects of NCS research need to be addressed to make these communication networks suitable for control systems in industrial environments. From the perspective of networking, communication protocols need to be designed to satisfy communication requirements for NCSs such as real-time communication and high-precision clock consistency requirements. From the perspective of control, methods to compensate for network-induced delays and packet losses are important for NCS design. To make Ethernet-based and 802.11 networks suitable for distributed control applications, this thesis develops a high-precision relative clock synchronisation protocol and an analytical model for analysing the real-time performance of 802.11 networks, and designs a new predictive compensation method. Firstly, a hybrid NCS simulation environment based on the NS-2 simulator is designed and implemented. Secondly, a high-precision relative clock synchronization protocol is designed and implemented. Thirdly, transmission delays in 802.11 networks for soft-real-time control applications are modeled by use of a Markov chain model in which real-time Quality-of- Service parameters are analysed under a periodic traffic pattern. By using a Markov chain model, we can accurately model the tradeoff between real-time performance and throughput performance. Furthermore, a cross-layer optimisation scheme, featuring application-layer flow rate adaptation, is designed to achieve the tradeoff between certain real-time and throughput performance characteristics in a typical NCS scenario with wireless local area network. Fourthly, as a co-design approach for both a network and a controller, a new predictive compensation method for variable delay and packet loss in NCSs is designed, where simultaneous end-to-end delays and packet losses during packet transmissions from sensors to actuators is tackled. The effectiveness of the proposed predictive compensation approach is demonstrated using our hybrid NCS simulation environment.

Predictive technology and natural hazards: Risk for Australian planning authorities?

Purpose The object of this paper is to examine whether the improvements in technology that enhance community understanding of the frequency and severity of natural hazards also increased the risk of potential liability of planning authorities in negligence. In Australia, the National Strategy imposes a resilience based approach to disaster management and stresses that responsible land use planning can reduce or prevent the impact of natural hazards upon communities. Design/methodology/approach This paper analyses how the principles of negligence allocate responsibility for loss suffered by a landowner in a hazard prone area between the landowner and local government. Findings The analysis in this paper concludes that despite being able to establish a causal link between the loss suffered by a landowner and the approval of a local authority to build in a hazard prone area, it would be in the rarest of circumstances a negligence action may be proven. Research limitations/implications The focus of this paper is on planning policies and land development, not on the negligent provision of advice or information by the local authority. Practical implications This paper identifies the issues a landowner may face when seeking compensation from a local authority for loss suffered due to the occurrence of a natural hazard known or predicted to be possible in the area. Originality/value The paper establishes that as risk managers, local authorities must place reliance upon scientific modelling and predictive technology when determining planning processes in order to fulfil their responsibilities under the National Strategy and to limit any possible liability in negligence.

Clipping noise compensation for OFDMA systems

This paper presents an efficient low-complexity clipping noise compensation scheme for PAR reduced orthogonal frequency division multiple access (OFDMA) systems. Conventional clipping noise compensation schemes proposed for OFDM systems are decision directed schemes which use demodulated data symbols. Thus these schemes fail to deliver expected performance in OFDMA systems where multiple users share a single OFDM symbol and a specific user may only know his/her own modulation scheme. The proposed clipping noise estimation and compensation scheme does not require the knowledge of the demodulated symbols of the other users, making it very promising for OFDMA systems. It uses the equalized output and the reserved tones to reconstruct the signal by compensating the clipping noise. Simulation results show that the proposed scheme can significantly improve the system performance.

Semi-active control for structural vibration based on predictive algorithm [Chinese title = 基于预测算法的结构振动半主动控制]

Based on Newmark-β method, a structural vibration response is predicted. Through finding the appropriate control force parameters within certain ranges to optimize the objective function, the predictive control of the structural vibration is achieved. At the same time, the numerical simulation analysis of a two-storey frame structure with magneto-rheological (MR) dampers under earthquake records is carried out, and the parameter influence on structural vibration reduction is discussed. The results demonstrate that the semi-active control based on Newmark-β predictive algorithm is better than the classical control strategy based on full-state feedback control and has remarkable advantages of structural vibration reduction and control robustness.

Estimation and compensation of clipping noise in OFDMA systems

We propose an efficient and low-complexity scheme for estimating and compensating clipping noise in OFDMA systems. Conventional clipping noise estimation schemes, which need all demodulated data symbols, may become infeasible in OFDMA systems where a specific user may only know his own modulation scheme. The proposed scheme first uses equalized output to identify a limited number of candidate clips, and then exploits the information on known subcarriers to reconstruct clipped signal. Simulation results show that the proposed scheme can significantly improve the system performance.

A new predictive current control technique for multilevel converters

Multilevel inverters provide an attractive solution for power electronics when both reduced harmonic contents and high voltages are required. In this paper, a novel predictive current control technique is proposed for a three-phase multilevel inverter, which controls the capacitors voltages and load currents with low switching losses. The advantage of this contribution is that the technique can be applied to more voltage levels without significantly changing the control circuit. The three-phase three-level inverter with a pure inductive load has been implemented to track reference currents using analogue circuits and programmable logic device.

Dengue fever and el nino-southern oscillation in Queensland, Australia : a time series predictive model

Background It remains unclear over whether it is possible to develop an epidemic forecasting model for transmission of dengue fever in Queensland, Australia. Objectives To examine the potential impact of El Niño/Southern Oscillation on the transmission of dengue fever in Queensland, Australia and explore the possibility of developing a forecast model of dengue fever. Methods Data on the Southern Oscillation Index (SOI), an indicator of El Niño/Southern Oscillation activity, were obtained from the Australian Bureau of Meteorology. Numbers of dengue fever cases notified and the numbers of postcode areas with dengue fever cases between January 1993 and December 2005 were obtained from the Queensland Health and relevant population data were obtained from the Australia Bureau of Statistics. A multivariate Seasonal Auto-regressive Integrated Moving Average model was developed and validated by dividing the data file into two datasets: the data from January 1993 to December 2003 were used to construct a model and those from January 2004 to December 2005 were used to validate it. Results A decrease in the average SOI (ie, warmer conditions) during the preceding 3–12 months was significantly associated with an increase in the monthly numbers of postcode areas with dengue fever cases (β=−0.038; p = 0.019). Predicted values from the Seasonal Auto-regressive Integrated Moving Average model were consistent with the observed values in the validation dataset (root-mean-square percentage error: 1.93%). Conclusions Climate variability is directly and/or indirectly associated with dengue transmission and the development of an SOI-based epidemic forecasting system is possible for dengue fever in Queensland, Australia.

A prospective study of personality features predictive of early adolescent alcohol misuse

Personality factors implicated in alcohol misuse have been extensively investigated in adult populations. Fewer studies have clarified the robustness of personality dimensions in predicting early onset alcohol misuse in adolescence. The aim of this study was to examine the predictive utility of two prominent models of personality (Cloninger, 1987; Eysenck & Eysenck, 1975) in emergent alcohol misuse in adolescence. One hundred and 92 secondary school students (mean age = 13.8 years, SD = 0.5) were administered measures of personality (Revised Junior Eysenck Personality Questionnaire – abbreviated; Temperament scale of Junior Temperament and Character Inventory) and drinking behavior (quantity and frequency of consumption, Alcohol Use Disorders Identification Test) at Time 1. At 12-month follow-up, 170 students (88.5%) were retained. Hierarchical multiple regressions revealed the dimensions of psychoticism, extraversion, and Novelty-Seeking to be the most powerful predictors of future alcohol misuse in adolescents. Results provide support for the etiological relevance of these dimensions in the development of early onset alcohol misuse. Findings can be used to develop early intervention programs that target personality risk factors for alcohol misuse in high-risk youth.