The intelligent multisensor state information fusion based on a new stochastic, fuzzy, neural network is investigated. This network carries out the parameter and structure learning to obtain the optimal fuzzy membersh...
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The intelligent multisensor state information fusion based on a new stochastic, fuzzy, neural network is investigated. This network carries out the parameter and structure learning to obtain the optimal fuzzy membership functions and the optimal number of fuzzy rules of stochastic dynamic systems. The state information fusion with radar and infrared sensors based on the network is simulated in an uncertain environment. The numerical results show that the proposed intelligent method is effective and superior to fuzzy neural network based method
Access to restricted spaces underwater requires a small unencumbered camera. A low cost solution has been envisaged. It consists of an hermetic capsule enclosing the camera and lights, joined to the host by an umbilic...
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Access to restricted spaces underwater requires a small unencumbered camera. A low cost solution has been envisaged. It consists of an hermetic capsule enclosing the camera and lights, joined to the host by an umbilical. Along the umbilical go six water carrying ducts. Three of them end at backwards pointing nozzles located at the capsule body. The jets of water flowing from the nozzles are controlled and their forces allow some restricted positioning of the camera. Another three ducts end at nozzles located some distance up the umbilical, and allow greater maneuverability.
Some frequency-domain properties of innovations sequence are studied. As their applications, a frequency-domain method for the identification of statistical parameters in adaptive Kalman filtering is proposed. This me...
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Some frequency-domain properties of innovations sequence are studied. As their applications, a frequency-domain method for the identification of statistical parameters in adaptive Kalman filtering is proposed. This method has clear physical meaning, and by using the weighted least-squares estimation algorithm, the statistical parameters can be identified accurately and robustly. A sufficient condition for the identifiability of model mismatches with arbitrary phase characters in adaptive Kalman filtering is also given, by using the structure of innovations sequence and the theory of higher-order statistics.
control of a gas-turbine engine requires management of continuous and discrete (state-event) behaviour. A design environment- the Development Framework, is used to define both the continuous and discrete aspects of a ...
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control of a gas-turbine engine requires management of continuous and discrete (state-event) behaviour. A design environment- the Development Framework, is used to define both the continuous and discrete aspects of a turbine engine controller. The approach uses purpose-built software translation tools to capture the system's specification from commercial simulation tools. A unified design model based on a data flow notation, comprising both continuous and state-event behaviour is automatically generated. Specification and design models of selected gas-turbine engine controller subsystems are presented. The complexity of the application suggests that the approach can be used for industrial scale projects.
in this paper a general algorithm to obtain Robust H ∞ Static Output Feedback controllers is derived. The technique used is based on the transformation of the time-varying uncertainty problem into one without uncerta...
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in this paper a general algorithm to obtain Robust H ∞ Static Output Feedback controllers is derived. The technique used is based on the transformation of the time-varying uncertainty problem into one without uncertainty and then applying the dual-iteration numerical technique of Iwasaki to the problem of determining the optimal parameters for a static H ∞ output feedback controller. To show how the method works, we apply it to a model which contains time-varying structured parameter uncertainty and is subject to external disturbances.
Constrained predictive controller that is based on Youla-Kučera (YK) parametrisation of all stabilising controllers is discussed. The optimised variables are not future control increments as usual but directly paramet...
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Constrained predictive controller that is based on Youla-Kučera (YK) parametrisation of all stabilising controllers is discussed. The optimised variables are not future control increments as usual but directly parameters of the controller. Both finite and infinite horizon formulations are handled.
Embedded systems are computer-based systems which must respond to external stimuli within time scales determined by the external environment. Such systems are required to achieve ever more demanding behavioural. perfo...
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Embedded systems are computer-based systems which must respond to external stimuli within time scales determined by the external environment. Such systems are required to achieve ever more demanding behavioural. performance and safety requirements. Embedded systems are found in applications such as primary flight control, gas-turbine engine control and railway traffic management Often complex embedded systems are distributed, typically to achieve demanding performance or dependability requirements, and must operate within hard real-time constraints. Considerable effort is required to select optimal design solutions and ensure adherence to specified requirements. In embedded systems safety, reliability and response-times are considered as strict constraints on the system design. Achievement of these constraints requires meticulous analysis, typically through the use of specialist modelling and simulation techniques. Integration of knowledge and understanding obtained from disparate detailed models remains a considerable challenge. Ideally, a system which has both continuous dynamics and event-driven parts. would be modelled in one environment, using the most appropriate techniques for each part, and allowing the analysis of the whole system to be carried out simultaneously. The paper presents an integrated approach in order to translate automatically the information manipulated during the different phases of the design: specification. analysis, design and implementation.
Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capa...
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Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capabilities of neural networks to model objective functions, and to use them to supply their values to a genetic algorithm which performs on-line minimization. Simulation results show that this is a valid approach, offering desired properties for on-line use such as a dramatic reduction in computation time and avoiding the need of perturbing the closed-loop operation
This paper introduces a new multi-mode scannable memory element which allows pseudorandom testing to be integrated with scan in sequential circuits without the need of any design changes. As in the case of scan, the n...
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This paper introduces a new multi-mode scannable memory element which allows pseudorandom testing to be integrated with scan in sequential circuits without the need of any design changes. As in the case of scan, the new element is used in place of regular flip-flops in the design library. Concurrent with normal operation, the design can accumulate a signature of the state variables in the scan-register configured as a multiple input signature analyzer (MISA). Thus virtually complete state observability is achieved without the need of scanning-out the state for each test-input. The pseudorandom states of the MISA can also be utilized as state inputs in pseudorandom testing. In this way, most faults are covered in a pseudorandom, `test per clock' mode. Only a few random pattern resistant faults require scan, greatly reducing test application time. Pseudorandom delay testing of the true normally active circuit paths is also possible. Two-pattern tests are supported. Finally, we show that the new memory element can also be used for fault-tolerant design.
A MATLAB-based rapid controller prototyping and development system for on-line tuning is presented. This is capable of automatically generating executable code for a digital signal processor from a Simulink specificat...
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A MATLAB-based rapid controller prototyping and development system for on-line tuning is presented. This is capable of automatically generating executable code for a digital signal processor from a Simulink specification of a controller and also has a real-time parameter adjustment and data logging facility. An optimisation problem can therefore be formulated in MATLAB with the controller parameters as decision variables and direct measures of the controller's performance as optimisation objectives. A multiobjective genetic algorithm is used as an optimisation engine to perform on-line tuning for the controller of an active magnetic bearing system. The optimisation objective function is based on on-line H ∞ and H 2 , measures of controller performance.
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