1,721,067 research outputs found
Parallel computing in CACSD
No full textComputer-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
Systems integration using evolutionary algorithms
No full textThis paper describes an approach to the systems integration problem using multiobjective genetic algorithms. An architecture for evolutionary systems integration is presented and the component parts discussed. An example of an aircraft gas turbine engine control system design problem is shown demonstrating aspects of the proposed architecture that allow many design objectives from different disciplines to be considered in parallel. Potential closed-loop control configurations are evaluated and compared against one another within an optimization framework. As a result of this analysis, it is shown how informed decisions may be made regarding the nature of the control employed, acceptable performance margins and elements of the engine design
MATLAB Genetic algorithm toolbox
No full textThe MATLAB Genetic Algorithm Toolbox aims to make genetic algorithms accessible to the control engineer within the framework of an existing computer-aided control system design (CACSD) package. This allows the retention of existing modeling and simulation tools for building objective functions and enables the user to make direct comparisons between genetic methods and traditional procedures
PARSIM: a parallel optimization tool
No full textCurrent computer-aided control system design environments seldom support optimization methods for controller design in a truly interactive manner. A prototype tool, called PARSIM, supporting parallel processing, optimization, and a graphical user interface is presented, addressing many of the problems inherent in current approaches to multiobjective optimization-based design methods. An XWindows interface is used to simplify problem formulation and control the optimization processes. Using a previously developed interface, it is shown how the computational burden may be alleviated by parallel processin
Evolutionary design of gas turbine aero-engine controllers
No full textThis paper describes a novel approach to the design of a control system for an aircraft gas turbine engine. A multi-level multiobjective genetic algorithm is employed to design controllers at both individual operating points using system linearisations and small signal response characteristics, and over the full-flight envelope using a nonlinear model and large signal responses. The proposed approach should allow the selection of smoother controller parameters over the flight envelope and ensure that more consistent control demands are made at off-design operating point
General approach for solving optimal control problems using optimization techniques
No full textA general approach to the determination of approximate solutions of general control problems by exploiting modern global search and optimization techniques is proposed. According to the methodology developed in this paper, controls are represented by discrete vectors and substituted in system equations. The components of these vectors are regarded as variables of a performance index based goal function that is to be minimized with respect to the system constraints. Such an approach enables modeling and solution of a wide class of optimal control problems, arising in engineering practice, within a unified framework of constrained optimization techniques, including implementation of genetic algorithms for global optimization and multiobjective control. Computer realizations of the proposed method are mainly based on MATLAB simulation programs. The results obtained can be implemented to solve optimal control problems in the field of Computer Aided Control Engineering, Computer Integrated Manufacturing, Mechatronics and Robotics
Fuzzy scheduling control for gas turbine aero-engine: a multiobjective approach
No full textThis 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
Evolutionary control mode analysis
No full textThe control configuration design problem is to find appropriate sets of closed - and/or open-loop controls to meet the desired specification including performance, complexity and economic considerations whilst the choice of the final controller configuration is determined by analysis of the acceptable control models. This paper has considered an approach to the problem of control mode analysis based on the use of multiobjective evolutionary algorithms for the search and optimization of suitable control configurations. The proposed method differs from currently available techniques in that it allows a number of potential configurations to be identified and compared with one another, highlighting both the positive and negative aspects of each individual scheme, in a single framework - hopefully realizing a more informed and efficient design process. As aero-engines become more complex and greater numbers of parameters become controllable and measurable, the need for such tools will increase.<br/
Multi-objective optimization approach to the ALSTOM gasifier problem
Full text linkA control system design procedure based on the optimization of multiple objectives is used to realize the control design specifications of the linear gasification plant models. A multi-objective genetic algorithm (MOGA) is used in conjunction with an H? loop-shaping design procedure (LSDP) in order to satisfy the requirements of this critical system. The H? LSDP is used to guarantee the stability and robustness of the controller while its associated weighting matrix parameters are selected using the multi-objective search method in order to achieve performance requirements. A controller emerges which is stable but unable to completely meet some of the control objectives. Despite this shortcoming, the study is an excellent vehicle for introduction to an effective H? loop-shaping procedure. Further work, beyond the scope of this challenge has subsequently produced an improved controller desig
Multiobjective design of a fuzzy controller for a gas turbine aero-engine
No full textThis paper describes the design of a fuzzy logic controller for a gas turbine aero-engine based on multiobjective genetic algorithms. The design is for a single manoeuvre around a 50% operating point at sea-level static conditions. The input-output relationship of the original controller is observed for the manoeuvre and a fuzzy controller constructed to approximate this relationship and verified on a nonlinear thermodynamic of the model engine. The fuzzy rule-base and membership functions are then optimized for a representative set of performance and operational design criteria directly on the nonlinear model and compared with the original controlle
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