The paper addresses the problem robust output feedback controller design with guaranteed cost and affine quadratic stability for linear continuous time affine systems. The proposed design method leads to a non-iterati...
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The paper addresses the problem robust output feedback controller design with guaranteed cost and affine quadratic stability for linear continuous time affine systems. The proposed design method leads to a non-iterative LMI based algorithm. A numerical example is given to illustrate the design procedure.
In order to show the handling ability of 16-bit microcontrollers of the Siemens C166-family. The controller for electric bicycle of Rare Earth Permanent Magnet Brushless DC Motor (BLDCM) based on Siemens C164-class is...
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ISBN:
(纸本)7560317685
In order to show the handling ability of 16-bit microcontrollers of the Siemens C166-family. The controller for electric bicycle of Rare Earth Permanent Magnet Brushless DC Motor (BLDCM) based on Siemens C164-class is developed. The control method used in the speed adjustment of DC Motor is the armature voltage control law that changes armature terminal voltage. This system is implemented with pulse wide modulation (PWM) and the principle of microcontroller control. The microcontroller C164CI is used to control the system. The reliability of the system is enhanced by using the microcontroller, and high efficiency and energy saving are achieved.
A simple and effective fuzzy clustering approach is presented for fuzzy modeling from industrial data. In this approach, fuzzy clustering is implemented in two phases: data compression by a self-organizing network, an...
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A simple and effective fuzzy clustering approach is presented for fuzzy modeling from industrial data. In this approach, fuzzy clustering is implemented in two phases: data compression by a self-organizing network, and fuzzy partitioning via fuzzy c-means clustering associated with a proposed cluster validity measure. The approach is used to extract fuzzy models from data and find out the optimal number of fuzzy rules. The simulation results show that the proposed approach has good clustering performance with noise-contaminated data and high-dimensional industrial data.
This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse r...
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The paper discusses the usefulness of Gröbner bases methods in a variety of control problems for a class of polynomial systems. Polynomial systems are described by difference or differential equations in which th...
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In this paper, a robust filter for an in-flight alignment (IFA) is presented to effectively eliminate system errors in the case where a strapdown inertial navigation system (SDINS) has large initial attitude errors. F...
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In this paper, a robust filter for an in-flight alignment (IFA) is presented to effectively eliminate system errors in the case where a strapdown inertial navigation system (SDINS) has large initial attitude errors. First, an extended robust H ∞ filter is proposed for a general nonlinear uncertain system. We also analyze the characteristics of the proposed filter, such as an H ∞ performance criterion, using the Lyapunov function method. Analysis results show that the proposed filter has robustness against disturbances, such as process and measurement noises, and against parameter uncertainties. Then the IFA for the SDINS is designed using the presented filter. Simulation results demonstrate that the proposed filter effectively improve the performance.
Differential linear repetitive processes are a distinct class of 2D continuous-discrete linear systems of both applications and systems theoretic interest. In the latter area, they arise, for example, in the analysis ...
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Differential linear repetitive processes are a distinct class of 2D continuous-discrete linear systems of both applications and systems theoretic interest. In the latter area, they arise, for example, in the analysis of both iterative learning control schemes and iterative algorithms for computing the solutions of nonlinear dynamic optimal control algorithms based on the maximum principle. Repetitive processes cannot be analysed/controlled by direct application of existing systems theory and to date there are few results on the specification and design of control schemes for them. The paper uses an LMI setting to develop the first really significant results in this problem domain.
It is possible to prestabilise the predictions used within Predictive Functional control in order to increase the likelihood of a stabilising control design. However, the minimal order approach to prestabilisation is ...
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It is possible to prestabilise the predictions used within Predictive Functional control in order to increase the likelihood of a stabilising control design. However, the minimal order approach to prestabilisation is not always a good basis for control design. This weakness is investigated and some non-minimal forms of prestabilisation are developed which are a much better basis for control.
A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a f...
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In this paper, an active fault tolerant control (FTC) strategy is presented for linear dynamic systems. The robust observer-based fault detection and isolation (FDI) systems are applied to guide the reconfiguration of...
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In this paper, an active fault tolerant control (FTC) strategy is presented for linear dynamic systems. The robust observer-based fault detection and isolation (FDI) systems are applied to guide the reconfiguration of controller parameters to achieve the optimal control performance during different operating conditions of the system: fault-free, fault detected and fault isolated. The selection of design parameters is achieved using the linear matrix inequality (LMI) optimization technique.
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