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Control Systems Technology, IEEE Transactions on

Issue 2 • Date Mar 1996

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Displaying Results 1 - 10 of 10
  • Nonlinear control of optical fiber diameter variations

    Page(s): 152 - 162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (992 KB)  

    This paper presents a simulation-based investigation of nonlinear control of optical fiber diameter variations. A model of the fiber drawing process is presented and model reference control (MRC) and quasi-nonlinear control (QNC) systems are developed, based on a nonlinear dynamical model of the fiber drawing process. Results of numerical simulation indicate that the control schemes developed in this paper provide the potential for the manufacture of optical fibers at higher speeds. Numerical experiments also indicate that the QNC methodology is robust in the presence of significant model uncertainties and external disturbances View full abstract»

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  • Active noise cancellation in ducts using internal model-based control algorithms

    Page(s): 163 - 170
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    A feedback control algorithm based on the internal model principle is proposed to solve the active noise control (ANC) problem in ducts. Because of its infinite open-loop gain at selected frequencies, the controller is able, at the cancellation speaker position, to block noise transmission of these frequencies. In other words, the speaker acts like a totally reflective boundary. Stability analysis of the closed-loop system is performed using the Nyquist criterion. Experimental results confirm the theoretical analysis, showing an average noise level reduction of 30 to 40 dB at the target frequencies View full abstract»

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  • Nonlinear control of synchronous servo drive

    Page(s): 177 - 184
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    The complete control design for a permanent magnet synchronous (PMAC) motor, derived from the input-output linearization, is presented in the paper. The motor model, written in the rotor's d-q coordinates, is nonlinear with respect to the state variables and linear in the control. The input-output linearization makes it possible to write the motor's model in Brunovski decoupled canonical form which makes the synthesis of linear controllers possible. The proposed control structure allows perfect tracking of smooth references in the case of nominal parameters. In relation to the bounded parameter perturbations, the robustness of the feedback system is improved by introducing an additional compensation signal which assures the stability of the perturbed system in Lyapunov's sense. The influence of parameter variations that prevents exact compensation of the control plant nonlinearities was analyzed for the PMAC motor. A description of the laboratory setup is given, and the experimental results of the proposed PMAC servo drive control are presented View full abstract»

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  • An analysis of the destabilizing effect of daisy chained rate-limited actuators

    Page(s): 171 - 176
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    The response of a rate-limited actuator will lag behind a rapidly changing command. This lag may destabilize the closed-loop system. When multiple actuators are arranged in a daisy chain this effect can be significantly worse. The cost of daisy chaining, in terms of lost stability margin, is estimated analytically and numerically. A comparison of a simple daisy chain with a simple “cooperative” control selector shows that the daisy chain may cause as much as 30° of additional phase lag View full abstract»

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  • A sliding-mode approach to fuzzy control design

    Page(s): 141 - 151
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    This study develops a method for fuzzy control design with sliding modes in which robustness is inherent. Fuzzy control is formulated to become a class of variable structure system (VSS) control. Sliding modes are used to determine best values for parameters in fuzzy control rules, thereby robustness in fuzzy control can be improved. A switching manifold is prescribed and the phase trajectory is demanded to satisfy both the reaching condition and the sliding condition for sliding modes. Both computer simulations and experiments are carried out for an apparatus which can to some extent represent cornering motion of a motorcycle on which a rider leans to maintain stability. Experimental results demonstrate that the proposed method outperforms both proportional integral derivative (PID) control and neural-network-based fuzzy control View full abstract»

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  • Optimal Popov controller analysis and synthesis for systems with real parameter uncertainties

    Page(s): 200 - 207
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    Robust performance analysis plays an important role in the design of controllers for uncertain multivariable systems. Recent research has investigated the use of absolute stability criteria to develop less conservative analysis tests for systems with linear and nonlinear real parameter uncertainties. This note extends previous work on optimal ℋ2 performance analysis using the Popov criterion by presenting a numerical homotopy algorithm that can be used to analyze systems with less restrictive assumptions on the structure of the uncertainty block. The technique is used to compare relative robustness capabilities of the various control algorithms that have been designed for the Middeck active control experiment (MACE). The analysis is combined with the previously presented Popov controller synthesis to yield compensators that guarantee robust performance for systems with real parameter uncertainty View full abstract»

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  • Effects of torsional dynamics on nonlinear generator control

    Page(s): 125 - 140
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    The performance of a feedback-linearizing control for excitation control of a synchronous generator is investigated with respect to unmodeled dynamics of both the turbine generator unit and the transmission network. It is found that certain types of dynamics that were not modeled during the design of the control enter in a manner that does affect the performance of the control, but that preserves the linearity of the closed-loop system. Moreover, the control acts to decouple the dynamics associated with the machine from the dynamics of the transmission grid, thus preventing subsynchronous resonance between the two subsystems when a series capacitor is used to compensate the transmission line. The stability robustness of the feedback-linearizing control is investigated with respect to a structured uncertainty. The uncertainty considered corresponds to the spring modes of the generator shaft and enters in such a way that analysis by Kharitonov's theorem is feasible. It is shown that the control remains stable over a wide range of values of the shaft parameters. A sliding control is designed and compared to the feedback-linearizing control with respect to performance degradation for this type of uncertainty, and it is found that, because of the tight saturation limits on the control signal, the sliding control offers no discernable performance advantage for this type of structured uncertainty View full abstract»

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  • Failure diagnosis using discrete-event models

    Page(s): 105 - 124
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    Detection and isolation of failures in large, complex systems is a crucial and challenging task. The increasingly stringent requirements on performance and reliability of complex technological systems have necessitated the development of sophisticated and systematic methods for the timely and accurate diagnosis of system failures. We propose a discrete-event systems (DES) approach to the failure diagnosis problem. This approach is applicable to systems that fall naturally in the class of DES; moreover, for the purpose of diagnosis, continuous-variable dynamic systems can often be viewed as DES at a higher level of abstraction. We present a methodology for modeling physical systems in a DES framework and illustrate this method with examples. We discuss the notion of diagnosability, the construction procedure of the diagnoser, and necessary and sufficient conditions for diagnosability. Finally, we illustrate our approach using realistic models of two different heating, ventilation, and air conditioning (HVAC) systems, one diagnosable and the other not diagnosable. While the modeling methodology presented here has been developed for the purpose of failure diagnosis, its scope is not restricted to this problem; it can also be used to develop DES models for other purposes such as control View full abstract»

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  • Control loop performance monitoring

    Page(s): 185 - 192
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    Control loop monitoring can be used to improve the performance of processes in industry. The monitoring tools presented are concerned with reducing the output variance of regulation loops. As a result, three different estimators are used to determine the minimum achievable output variance, the time delay and the static input-output relationship of the process. These three properties can be used together or individually to provide insights into the process. Once the methods are introduced and their algorithms outlined, the monitoring tools are tested on data from industrial processes. These results show the capabilities and limitations of the proposed estimation methods and the potential benefits to be obtained from monitoring View full abstract»

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  • A fuzzy-Gaussian neural network and its application to mobile robot control

    Page(s): 193 - 199
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (520 KB)  

    A fuzzy-Gaussian neural network (FGNN) controller is described by applying a Gaussian function as an activation function. A specialized learning architecture is used so that membership function can be tuned without using expert's manipulated data. As an example of the application, a tracking control problem for the speed and azimuth of a mobile robot driven by two independent wheels is solved by using the FGNN controller. To simplify the implementation of the FGNN controller for the two-input/two-output controlled system, a learning controller is utilized consisting of two FGNN's based on independent reasoning and a connection net with fixed weights. The effectiveness of the proposed method is illustrated by performing the simulation of a circular or square trajectory tracking control View full abstract»

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