64 resultados para Control system stability


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A novel smoke sensor was used to realize smoke feedback control on a diesel engine. The controller design based on a combination of PI control algorithm and the engine performance optimization is described. Experimental results demonstrate how this control system behave to meet both of the speed and smoke requirements during engine transients.

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Vector control provides stability and performance when applied to the brushless doubly-fed machine, however cross-coupling effects can arise between inputs and outputs. To address these effects, a procedure is proposed to both visualize and minimize the cross-coupling by means of steady-state mapping and a re-alignment of the dq reference frame. With this method implemented, gain-response tests show improved decoupling across the operating region. © 2013 EUCA.

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This brief note reviews five papers which were presented at the 1993 IFAC World Congress, on the theme 'standards and guidelines for computer-aided control engineering (CACE)'. This session was organized as part of the CACE Software Standardization Initiative, a combined effort of the IFAC and IEEE Control System Society committees on standards. The motivation of this report is to note the substantial progress that was made in this initiative, and to provide the basis for further discussion and work. The papers under review were concerned with integrated design environments, the use of the EXPRESS language for defining standard data structures, database management, user interfaces, and the modeling and simulation of hybrid systems.

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Computer Aided Control Engineering involves three parallel streams: Simulation and modelling, Control system design (off-line), and Controller implementation. In industry the bottleneck problem has always been modelling, and this remains the case - that is where control (and other) engineers put most of their technical effort. Although great advances in software tools have been made, the cost of modelling remains very high - too high for some sectors. Object-oriented modelling, enabling truly re-usable models, seems to be the key enabling technology here. Software tools to support control systems design have two aspects to them: aiding and managing the work-flow in particular projects (whether of a single engineer or of a team), and provision of numerical algorithms to support control-theoretic and systems-theoretic analysis and design. The numerical problems associated with linear systems have been largely overcome, so that most problems can be tackled routinely without difficulty - though problems remain with (some) systems of extremely large dimensions. Recent emphasis on control of hybrid and/or constrained systems is leading to the emerging importance of geometric algorithms (ellipsoidal approximation, polytope projection, etc). Constantly increasing computational power is leading to renewed interest in design by optimisation, an example of which is MPC. The explosion of embedded control systems has highlighted the importance of autocode generation, directly from modelling/simulation products to target processors. This is the 'new kid on the block', and again much of the focus of commercial tools is on this part of the control engineer's job. Here the control engineer can no longer ignore computer science (at least, for the time being). © 2006 IEEE.

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Computer Aided Control Engineering involves three parallel streams: Simulation and modelling, Control system design (off-line), and Controller implementation. In industry the bottleneck problem has always been modelling, and this remains the case - that is where control (and other) engineers put most of their technical effort. Although great advances in software tools have been made, the cost of modelling remains very high - too high for some sectors. Object-oriented modelling, enabling truly re-usable models, seems to be the key enabling technology here. Software tools to support control systems design have two aspects to them: aiding and managing the work-flow in particular projects (whether of a single engineer or of a team), and provision of numerical algorithms to support control-theoretic and systems-theoretic analysis and design. The numerical problems associated with linear systems have been largely overcome, so that most problems can be tackled routinely without difficulty - though problems remain with (some) systems of extremely large dimensions. Recent emphasis on control of hybrid and/or constrained systems is leading to the emerging importance of geometric algorithms (ellipsoidal approximation, polytope projection, etc). Constantly increasing computational power is leading to renewed interest in design by optimisation, an example of which is MPC. The explosion of embedded control systems has highlighted the importance of autocode generation, directly from modelling/simulation products to target processors. This is the 'new kid on the block', and again much of the focus of commercial tools is on this part of the control engineer's job. Here the control engineer can no longer ignore computer science (at least, for the time being). ©2006 IEEE.

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A semi-active truck damper was developed in conjunction with a commercial shock absorber manufacturer. A linearized damper model was developed for control system design purposes. Open- and closed-loop damper force tracking control was implemented, with tests showing that an open-loop approach gave the best compromise between response speed and accuracy. A hardware-in-the-loop test facility was used to investigate performance of the damper when combined with a simulated quarter-car model. The input to the vehicle model was a set of randomly generated road profiles, each profile traversed at an appropriate speed. Modified skyhook damping tests showed a simultaneous improvement over the optimum passive case of 13 per cent in vertical body acceleration and 8 per cent in dynamic tyre forces. Full-scale vehicle tests of the damper on a heavy tri-axle trailer were carried out. Implementation of modified skyhook damping yielded a simultaneous improvement over the optimum passive case of 8 per cent in vertical body acceleration and 8 per cent in dynamic tyre forces. © IMechE 2008.

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This paper presents the results of a project aimed at minimising fuel usage while maximising steam availability in the power and steam plant of a large newsprint mill. The approach taken was to utilise the better regulation and plant wide optimisation capabilities of Advanced Process Control, especially Model Predictive Control (MPC) techniques. These have recently made their appearance in the pulp and paper industry but are better known in the oil and petrochemical industry where they have been used for nearly 30 years. The issue in the power and steam plant is to ensure that sufficient steam is available when the paper machines require it and yet not to have to waste too much steam when one or more of the machines suffers an outage. This is a problem for which MPC is well suited. It allows variables to be kept within declared constraint ranges, a feature which has been used, effectively, to increase the steam storage capacity of the existing plant. This has resulted in less steam being condensed when it is not required and in significant reductions in the need for supplementary firing. The incidence of steam being dump-condensed while also supplementary firing the Combined Heat & Power (CHP) plant has been reduced by 95% and the overall use of supplementary firing is less than 30% of what it was. In addition the plant runs more smoothly and requires less operator time. The yearly benefit provided by the control system is greater than £200,000, measured in terms of 2005 gas prices.

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This paper presents dynamic and steady-state performance of the Brushless Doubly-Fed Machine (BDFM) operating as a variable speed drive. A simple closed-loop control system is used which only requires a speed feedback. The controller is capable of stabilising the machine when changes in speed and torque are applied. The machine starts in cascade mode and then makes a transition to the synchronous mode to reach the desired speed. This will allow a uni-directional converter to be used. The experiments included in this paper were carried out on a 180 frame size BDFM.

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A simple method of controlling the Brushless Doubly-Fed Machine (BDFM) is presented. The controller comprises two Proportional-Integral (PI) modules and requires only the rotor speed feedback. The machine model and the control system are developed in MATLAB. Both simulation and experimental results are presented. The performance of the system is presented in the motoring and generating operations. The experimental tests included in this paper were carried out on a 180 frame size BDFM with a nested-loop rotor. © 2007 IEEE.