Parallel Genetic Algorithms: A Survey

This report provides a wide-ranging survey of parallel genetic algorithms and reviews a number of approaches that have been adopted to parallelise them. A tutorial level introduction to genetic algorithms is given and the underlying mechanisms are described and discussed with many current developments reviewed. These broad classes of parallel genetic algorithms are considered in detail and compared with conventional sequential implementations. It is argued that significant performance benefits can be realised by using distributed population structures and selection mechanisms even when the paradigm is implemented on a sequential machine

Dynamic modelling and open-loop control of a twin rotor multi-input multi-output system

A dynamic model for a one-degree-of-freedom (DOF) twin rotor multi-input multi-output (MIMO) system (TRMS) in hover is obtained using a black-box system identification technique. The behaviour of the TRMS in certain aspects resembles that of a helicopter; hence, it is an interesting identification and control problem. This paper investigates modelling and open-loop control of the longitudinal axis alone, while the lateral axis movement is physically constrained. It is argued that some aspects of the modelling approach presented are suitable for a class of new generation or innovative air vehicles with complex dynamics. The extracted model is employed for designing and implementing a feedforward/open-loop control. Open-loop control is often the preliminary step for development of more complex feedback control laws. Open-loop control strategies using shaped command inputs are accordingly investigated for resonance suppression in the TRMS. Digital low-pass and band-stop filter shaped inputs are used on the TRMS testbed, based on the identified vibrational modes. A comparative performance study is carried out and the corresponding results presented. The low-pass filter is shown to result in better vibration reduction

Design and use of the MATLAB Parallel Processing Gateway

This report describes a collection of software utilities that together form a "parallel processing gateway" for the computer aided control system design software package,MATLAB. These utilities allow control engineers to configure and boot processes on the parallel computer and concurrent and parallel routines transparently from the MATLAB command line. Here, the requirements of such a gateway, its design, implementation and use and features that enable the control engineer to readily exploit a parallel computer are described and discussed. In addition, the performance of the gateway is assessed in terms of the communications achievable between MATLAB and the parallel computer

First validation of high-resolution satellite-derived methane emissions from an active gas leak in the UK

Atmospheric methane (CH4) is the second-most-important anthropogenic greenhouse gas and has a 20-year global warming potential 82 times greater than carbon dioxide (CO2). Anthropogenic sources account for ∼ 60 % of global CH4 emissions, of which 20 % come from oil and gas exploration, production and distribution. High-resolution satellite-based imaging spectrometers are becoming important tools for detecting and monitoring CH4 point source emissions, aiding mitigation. However, validation of these satellite measurements, such as those from the commercial GHGSat satellite constellation, has so far not been documented for active leaks. Here we present the monitoring and quantification, by GHGSat's satellites, of the CH4 emissions from an active gas leak from a downstream natural gas distribution pipeline near Cheltenham, UK, in the spring and summer of 2023 and provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys. We also use a Lagrangian transport model, the UK Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME), to estimate the flux from both satellite- and ground-based observation methods and assess the leak's contribution to observed concentrations at a local tall tower site (30 km away). We find GHGSat's emission estimates to be in broad agreement with those made from the in situ measurements. During the study period (March–June 2023) GHGSat's emission estimates are 236–1357 kg CH4 h−1, whereas the mobile surface measurements are 634–846 kg CH4 h−1. The large variability is likely down to variations in flow through the pipe and engineering works across the 11-week period. Modelled flux estimates in NAME are 181–1243 kg CH4 h−1, which are lower than the satellite- and mobile-survey-derived fluxes but are within the uncertainty. After detecting the leak in March 2023, the local utility company was contacted, and the leak was fixed by mid-June 2023. Our results demonstrate that GHGSat's observations can produce flux estimates that broadly agree with surface-based mobile measurements. Validating the accuracy of the information provided by targeted, high-resolution satellite monitoring shows how it can play an important role in identifying emission sources, including unplanned fugitive releases that are inherently challenging to identify, track, and estimate their impact and duration. Rapid, widespread access to such data to inform local action to address fugitive emission sources across the oil and gas supply chain could play a significant role in reducing anthropogenic contributions to climate change

Fuzzy scheduling control for gas turbine aero-engine: a multiobjective approach

This paper investigates the use of a nonconventional approach to control a gas turbine aero-engine. The rationale behind this study is the need to develop advanced tools and techniques that can assist in improving the performance of the system and simultaneously enhance the flexibility of the control strategy. Modern techniques are required for many complex systems where increasingly strict performance and regulatory requirements must be achieved. This is particularly true of aerospace systems where consideration of safety, reliability, maintainability, and environmental impact are all necessary as part of the control requirements. This paper investigates a combination of two such potential techniques: fuzzy logic and evolutionary algorithms. Emerging from new requirements for gas turbine aero-engine control, a flexible gain scheduler is developed and analyzed. A hierarchical multiobjective genetic algorithm is employed to search and optimize the potential solutions for a wide envelope controller covering idle, cruise, and full-power conditions. The overall strategy is demonstrated to be a straightforward and feasible method of refining the control system performance and increasing its flexibility

Missile endgame analysis via multiobjective optimization

The traditional approach to improving the lethality of a missile has been to concentrate efforts in the guidance and control systems to improve accuracy and agility. In this paper, we consider how optimizing the endgame, the final few milliseconds before detontation, can yield improvements in overall lethality. As there is likely to be uncertainty in both the target parameters and missile coordinates, a multiobjective problem is developed so that the robustness of a solution can be traded against its efficacy. The ability to quickly determine promising endgames is likely to be of benefit when exploiting modern control schemes, such as MPC, that offer improved accuracy and agility

Improved MOGA-tuning and visualization for a hybrid control system

A hybrid controller is developed for a solar-thermal power plant using a gain-scheduled controller with feedforward to control the more linear operating regimes and a fuzzy PI incremental controller for the highly nonlinear operating region of the plant. An enhanced method of MOGA-tuning is employed by first optimizing the number of input/output membership functions using neuro-fuzzy data clustering. Enhancements to the visualization properties of the MOGA's graphical user interface are evaluated to improve the decision maker's choice when deciding between non-dominated solutions or potential fuzzy controller inference systems

Non-linear modelling of a one-degree-of-freedom twin-rotor multi-input system using radial basis function networks

Modelling of innovative aircraft such as unmanned air vehicles (UAVs), X-wing, tilt body and delta-wing aircraft is not easy. It is argued in this paper that non-linear system identification is suitable for modelling air vehicles of complex configuration. This approach is demonstrated through a laboratory test rig. Extensive time and frequency-domain model-validation tests are employed in order to instil confidence in the estimated model. The estimated model has a good predictive capability and can be utilized for non-linear flight simulation studies. Some aspects of the modelling approach presented may be relevant to flight mechanics modelling of new generations of air vehicle

Parallel computing in CACSD

Computer-aided design of control systems via multiobjective optimisation is a computationally demanding task that may benefit from parallel processing techniques. In this paper, we report on a new parallel processing gateway that supports the use of parallel processing within the framework of an existing computer-aided control system design software package. In many control system design exercises which employ optimisation, the bulk of the computational effort is devoted to the evaluation of the objectives of the optimisation at each iteration. This paper demonstrates, with an example, how, using the gateway, parallel processing can be used within the framework of existing computer-aided control system design tools to compute these objective values