Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Development and verification of control and protection strategies in hybrid AC/DC power systems for smart grid applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Airport ground movement

Worldwide air traffic tends to increase and for many airports it is no longer an op-tion to expand terminals and runways, so airports are trying to maximize their op-erational efficiency. Many airports already operate near their maximal capacity. Peak hours imply operational bottlenecks and cause chained delays across flights impacting passengers, airlines and airports. Therefore there is a need for the opti-mization of the ground movements at the airports. The ground movement prob-lem consists of routing the departing planes from the gate to the runway for take-off, and the arriving planes from the runway to the gate, and to schedule their movements. The main goal is to minimize the time spent by the planes during their ground movements while respecting all the rules established by the Ad-vanced Surface Movement, Guidance and Control Systems of the International Civil Aviation. Each aircraft event (arrival or departing authorization) generates a new environment and therefore a new instance of the Ground Movement Prob-lem. The optimization approach proposed is based on an Iterated Local Search and provides a fast heuristic solution for each real-time event generated instance granting all safety regulations. Preliminary computational results are reported for real data comparing the heuristic solutions with the solutions obtained using a mixed-integer programming approach.

Organizational, systems and human issues in production planning, scheduling and control

With global markets and global competition, pressures are placed on manufacturing organizations to compress order fulfillment times, meet delivery commitments consistently and also maintain efficiency in operations to address cost issues. This chapter argues for a process perspective on planning, scheduling and control that integrates organizational planning structures, information systems as well as human decision makers. The chapter begins with a reconsideration of the gap between theory and practice, in particular for classical scheduling theory and hierarchical production planning and control. A number of the key studies of industrial practice are then described and their implications noted. A recent model of scheduling practice derived from a detailed study of real businesses is described. Socio-technical concepts are then introduced and their implications for the design and management of planning, scheduling and control systems are discussed. The implications of adopting a process perspective are noted along with insights from knowledge management. An overview is presented of a methodology for the (re-)design of planning, scheduling and control systems that integrates organizational, system and human perspectives. The most important messages from the chapter are then summarized.

Ambient Air Quality Monitoring in Metropolitan City of Lagos, Nigeria

Twenty one sampling locations were assessed for carbon monoxide (CO), carbondioxide (CO2), oxygen (O2), sulphur dioxide (SO2), nitrogen dioxide (NO2), nitrogen oxide (NO), suspended particulate matter (SPM) and noise level using air pollutants measurement methods approved by ASTM for each specific parameter. All equipments and meters were all properly pre-calibrated before each usage for quality assurance. Findings of the study showed that measured levels of noise (61.4 - 101.4 dBA), NO (0.0 - 3.0 ppm), NO2 (0.0 - 3.0 ppm), CO (1.0 – 42.0 ppm) and SPM (0.14 – 4.82 ppm) in all sampling areas were quite high and above regulatory limits however there was no significant difference except in SPM (at all the sampling points), and noise, NO2 and NO (only in major traffic intersection). Air quality index (AQI) indicates that the ambient air can be described as poor for SPM, varied from good to very poor for CO, while NO and NO2 are very good except at major traffic intersection where they were both poor and very poor (D-E). The results suggest that strict and appropriate vehicle emission management, industrial air pollution control coupled with close burning management of wastes should be considered in the study area to reduce the risks associated with these pollutants.

Development and Verification of Control and Protection Strategies in Hybrid AC/DC Power Systems for Smart Grid Applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Hybrid system simulation of computer control applications over communication networks

Discrete event-driven simulations of digital communication networks have been used widely. However, it is difficult to use a network simulator to simulate a hybrid system in which some objects are not discrete event-driven but are continuous time-driven. A networked control system (NCS) is such an application, in which physical process dynamics are continuous by nature. We have designed and implemented a hybrid simulation environment which effectively integrates models of continuous-time plant processes and discrete-event communication networks by extending the open source network simulator NS-2. To do this a synchronisation mechanism was developed to connect a continuous plant simulation with a discrete network simulation. Furthermore, for evaluating co-design approaches in an NCS environment, a piggybacking method was adopted to allow the control period to be adjusted during simulations. The effectiveness of the technique is demonstrated through case studies which simulate a networked control scenario in which the communication and control system properties are defined explicitly.

Non-motorized public transport development : present scenario and future approach in developing cities

Over the last few decades, most large cities in the developing world have been experiencing rapid and imbalanced transport sector development resulting in severe congestion and poor levels of service. The most common response at a policy level under this circumstance has been to focus on private and public motorized transport modes, and especially on traffic control measures and mass transit systems. Despite their major role in the overall transport system in many developing cities in Asia & Latin America, relatively little attention is given to non-motorized transport (NMT) modes (walk, bicycle and cycle-rickshaw). In particular, this ideology is applicable to the paid category of non-motorized public transport (NMPT), notably three-wheeler cycle rickshaws that still have an important socio-economic, environmental and trip-making role in many developing cities. Despite, they are often seen as inefficient and backward; an impediment to progress; and inconsistent with modern urban image. Policy measures therefore, to restrict or eliminate non-motorized transport from urban arterials and other feeder networks have been implemented in cities as diverse as Dhaka, Delhi, Karachi, Bangkok, Jakarta, Manila, Surabaya and Beijing . This paper will primarily investigate the key contribution of NMPT in the sustainable transport system and urban fabric of developing cities, with Dhaka as case study. The paper will also highlight in detail the impediments towards NMPT development and provide introductory concept on possible role this mode is expected to play into the future of these cities

Use of Probe Vehicles to Increase Traffic Estimation Accuracy in Brisbane

Traffic congestion is an increasing problem with high costs in financial, social and personal terms. These costs include psychological and physiological stress, aggressivity and fatigue caused by lengthy delays, and increased likelihood of road crashes. Reliable and accurate traffic information is essential for the development of traffic control and management strategies. Traffic information is mostly gathered from in-road vehicle detectors such as induction loops. Traffic Message Chanel (TMC) service is popular service which wirelessly send traffic information to drivers. Traffic probes have been used in many cities to increase traffic information accuracy. A simulation to estimate the number of probe vehicles required to increase the accuracy of traffic information in Brisbane is proposed. A meso level traffic simulator has been developed to facilitate the identification of the optimal number of probe vehicles required to achieve an acceptable level of traffic reporting accuracy. Our approach to determine the optimal number of probe vehicles required to meet quality of service requirements, is to simulate runs with varying numbers of traffic probes. The simulated traffic represents Brisbane’s typical morning traffic. The road maps used in simulation are Brisbane’s TMC maps complete with speed limits and traffic lights. Experimental results show that that the optimal number of probe vehicles required for providing a useful supplement to TMC (induction loop) data lies between 0.5% and 2.5% of vehicles on the road. With less probes than 0.25%, little additional information is provided, while for more probes than 5%, there is only a negligible affect on accuracy for increasingly many probes on the road. Our findings are consistent with on-going research work on traffic probes, and show the effectiveness of using probe vehicles to supplement induction loops for accurate and timely traffic information.

Automated control of a dragline using machine vision

The research described in this paper is directed toward increasing productivity of draglines through automation. In particular, it focuses on the swing-to-dump, dump, and return-to-dig phases of the dragline operational cycle by developing a swing automation system. In typical operation the dragline boom can be in motion for up to 80% of the total cycle time. This provides considerable scope for improving cycle time through automated or partially automated boom motion control. This paper describes machine vision based sensor technology and control algorithms under development to solve the problem of continuous real time bucket location and control. Incorporation of this capability into existing dragline control systems will then enable true automation of dragline swing and dump operations.

Real-time vision, tracking and control

This paper, which serves as an introduction to the mini-symposium on Real-Time Vision, Tracking and Control, provides a broad sketch of visual servoing, the application of real-time vision, tracking and control for robot guidance. It outlines the basic theoretical approaches to the problem, describes a typical architecture, and discusses major milestones, applications and the significant vision sub-problems that must be solved.

Choice of image features for depth-axis control in image based visual servo control

This paper is concerned with choosing image features for image based visual servo control and how this choice influences the closed-loop dynamics of the system. In prior work, image features tend to be chosen on the basis of image processing simplicity and noise sensitivity. In this paper we show that the choice of feature directly influences the closed-loop dynamics in task-space. We focus on the depth axis control of a visual servo system and compare analytically various approaches that have been reported recently in the literature. The theoretical predictions are verified by experiment.