In this paper, we propose a new observerdesign for the estimation of the biomass concentration in a bioreactor, using the measurements of the substrate concentration. We consider two cases: in the first, a full knowl...
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In this paper, we propose a new observerdesign for the estimation of the biomass concentration in a bioreactor, using the measurements of the substrate concentration. We consider two cases: in the first, a full knowledge of the specific growth rate is assumed and in the second, only a partial knowledge of the latter is assumed. We show that the bioreactor model is in a special canonical form called the extended Jordan observable canonical (EJOC) form. It is shown, in particular, that an observerdesign for systems in the EJOC form is fairly simple and straightforward. No particular nonlinear transformation is needed in the design procedure. In addition, the gain of the observer is adaptive since it is a function of the input and the output of the system, and can be tuned in order to obtain a desirable rate of convergence
Due to the saliency of the IPMSM, the model-based adaptive observer used in the sensorless control is nonlinear and difficult to analyze. With the extended EMF concept, the model though becomes partly linear, the exte...
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Due to the saliency of the IPMSM, the model-based adaptive observer used in the sensorless control is nonlinear and difficult to analyze. With the extended EMF concept, the model though becomes partly linear, the extended EMF dynamic itself is very complicated making the application of an adaptive full-order observer troublesome. This problem is eliminated with a fictitious permanent-magnet flux model newly proposed in this paper for the IPMSM, because it converts the IPMSM into an equivalent SPMSM. The new model is simple, approximately linear and allows the adaptive observer algorithm to be applied easily. Also, the EMF induced by the fictitious magnet flux is exactly the fictitious EMF of the phasor diagram of the synchronous machine's two-reaction theory found in electrical machine textbooks. The initial rotor position can also be estimated easily from this fictitious EMF which always points in the d-axis at standstill. A novel sensorless scheme based on the proposed model is constructed, and its stability conditions are derived analytically to give design guidelines. Experiment results are given to verify the theoretical results.
The following topics are dealt with: circuit tuning; communication architecture; UWB communications; adders and multipliers; interconnect and clock distribution; integrated power electronics circuits; biomedical appli...
The following topics are dealt with: circuit tuning; communication architecture; UWB communications; adders and multipliers; interconnect and clock distribution; integrated power electronics circuits; biomedical applications; global/local optimization techniques; data converters; amplifiers; network synthesis; audio and speech enhancement; complex dynamical networks; video coding; channel coding; communication receivers; analog circuits; ASIC design; digital circuits; digital filters; image sensors; repeater insertion for nanometer technologies; low power architecture; low power sensor networks; digital arithmetic; high level synthesis techniques; Class-E power amplifiers; graph theory; continuous-time filters; discrete transforms and wavelets; chaos in communications; transcoding; equalizer design; multimedia coding and segmentation; interface circuits; digital signal processing; ESD protection for nanoelectronics; configurable architecture; video adaptation and abstraction; DC-DC power converters; VLSI design; A/D converters; discrete time filters; signal detection and estimation; chaos and bifurcation in circuits; optical circuits; multimedia database and retrieval systems; operational amplifiers; wideband amplifiers; low power design; sensory systems, chemical and olfactory sensors; network-on-chip; clocking and I/O circuits; placement and routing; charge pumps; sensory and spiking networks; analog signal processing; low voltage/low power filters; FIR digital filters; multidimensional signal processing; image compression; RF communication circuits; FPGA and memory circuits; mixed-signal circuits; oscillators; adaptive signal processing; flip-flops; timing optimization; neural computation; sigma-delta converters; IIR digital filters; motion estimation and postprocessing; mobile ad hoc networks; blind signal processing; neural and fuzzy controllers; sample and hold circuits; switched capacitor circuits; audio and speech processing; nonlinear systems control
Under a single 'fault-type hypothesis', either actuator/component faults or sensor faults, geometric conditions are given such that the original nonlinear system can be transformed into two different subsystem...
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Under a single 'fault-type hypothesis', either actuator/component faults or sensor faults, geometric conditions are given such that the original nonlinear system can be transformed into two different subsystems with uncertainty. The first is in the generalised observer canonical form, which is not affected by faults. The second, whose states can be measured, is affected by the faults. Constructing a nonlinearobserver for the first subsystem allows estimation of the faults from the second subsystem. Robust (sliding mode) observers are proposed depending on different assumptions on the system uncertainties. The decision logic associated with the proposed bank of observers, and some extensions to simultaneous actuator and sensor faults case are also discussed. Two numerical examples are given to illustrate the design procedures and the efficiency of the proposed methods.
For biological wastewater treatment plants, this paper proposes an approach to controldesign based on nonlinear models integrating numerous processes. This paper does not resort to order reduction, localization and l...
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This paper presents real-time, digital image segmentation techniques using variable threshold functions. The approach is based on new learning models used to generate the variable threshold functions. The learning mod...
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This paper presents real-time, digital image segmentation techniques using variable threshold functions. The approach is based on new learning models used to generate the variable threshold functions. The learning models are derived from discrete time functions often used in digital control system design. The techniques are successful to detect regions with different or poor light conditions and can be applied to images with occluded or noisy objects. In addition, the approach can be used to locate objects in a scene. The developed algorithms can also be integrated on a single monolithic integrated circuit or implemented as an embedded system for real-time applications.
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