The purpose of this study is to design a gain-scheduled feedback compensator for a system constrained on the input. Description of the input saturation by the hyperbolic tangential function transfers the system descri...
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The purpose of this study is to design a gain-scheduled feedback compensator for a system constrained on the input. Description of the input saturation by the hyperbolic tangential function transfers the system description to a form of a linear parameter-dependent system. This formulation allows applying the gain-scheduling control synthesis via linear matrix inequalities (LMI). In order to avoid the windup phenomena caused by input limitation suppression of the input derivatives is employed. While the input derivatives could not be taken into account in the previous studies because of using the discontinuous functions as the input limitations, in this study it is available to take account of the input derivatives in the controller design. This means that the designed controller includes integrators and constructs a type-one controlsystem. Consideration of input derivatives may mitigate sudden change of the input even if there is no feedback loop of error between input and output of the nonlinear function. Simulation results show usefulness of the proposed design method.
This paper describes the methodology for usage of Bayesian Belief Networks (BBNs) in fault detection for aircraft gas turbine engines. First, the basic theory of BBNs is discussed, followed by a discussion on the appl...
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This paper describes the methodology for usage of Bayesian Belief Networks (BBNs) in fault detection for aircraft gas turbine engines. First, the basic theory of BBNs is discussed, followed by a discussion on the application of this theory to a specific engine. In particular, the selection of faults and the means by which operating regions for the BBN system are chosen are analyzed. This methodology is then illustrated using the GE CFM56-7 turbofan engine as an example.
In this paper we first motivate the use of autonomous micro-sensor arrays for use in semiconductor manufacturing. Following this, we discuss three critical issues that must be addressed in order to realize our goal of...
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In this paper we first motivate the use of autonomous micro-sensor arrays for use in semiconductor manufacturing. Following this, we discuss three critical issues that must be addressed in order to realize our goal of building these micro-sensor arrays. We then describe our on-going development efforts of fabricating spatially resolved etch-rate and temperature sensors.
In this paper, a new self-tuning PID controller design scheme is proposed. The PID parameters are calculated on-line based on the relationship between the PID and generalized minimum variance control (GMVC) laws. In d...
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In this paper, a new self-tuning PID controller design scheme is proposed. The PID parameters are calculated on-line based on the relationship between the PID and generalized minimum variance control (GMVC) laws. In designing GMVC system, user-specified polynomials are computed by considering the pole-assignment in the controlsystem. Therefore, this scheme has approximate minimum variance properties with specified closed-loop time-constant. The newly proposed control scheme can also deal with unknown and/or varying process time-delays. The proposed control scheme is experimentally evaluated on a SISO air pressure controlsystem. Experimental results illustrate the effectiveness of this new scheme.
This note presents a sliding mode controller for the robust stabilization of a magnetic bearing system. The approach avoids the need of pre magnetization currents frequently used to linearize the system model. It util...
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This note presents a sliding mode controller for the robust stabilization of a magnetic bearing system. The approach avoids the need of pre magnetization currents frequently used to linearize the system model. It utilizes two sliding manifolds achieving desired dynamics and complementarity of coil currents. Two differents controller has been designed. The second one takes account of discrete inputs as is the case in electronic power amplifiers. Simulations are presented to show the effectiveness and robustness of the designed feedback sliding mode controller.
The purpose of this paper is to describe some main aspects on the development of an integrated CAD Toolbox for nD system theory, named nD controlsystem Toolbox, for use with the software product. MATLAB and the assoc...
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The purpose of this paper is to describe some main aspects on the development of an integrated CAD Toolbox for nD system theory, named nD controlsystem Toolbox, for use with the software product. MATLAB and the associated Extended Symbolic Math Toolbox. The developed toolbox consists of several functional packages which provide various basic tools and facilities for both numerical and symbolic manipulations required in analysis and synthesis of 2D controlsystems such as stability test, factor coprime factorizations and solution of various linear matrix equations, etc. that usually involve very complicated procedures.
Over the last decade, multirate control has been an area of active research. Multirate output controllers (MROCs) sample the plant outputs at a faster rate than they change the plant inputs. Consequently, they offer g...
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Over the last decade, multirate control has been an area of active research. Multirate output controllers (MROCs) sample the plant outputs at a faster rate than they change the plant inputs. Consequently, they offer greater flexibility for controller design than conventional single-rate controllers. MROCs designed under H∞ performance have offered a new dimension in the design process. In this paper, we introduce the concept of lifting technique, LMIs and multirate output sampling and calculate the H∞ norm of the sampled-data controlsystems induced via multirate output sampling. Furthermore, in order to avoid dynamic parameters of MROCs, we use additional pole placement constraints to guarantee satisfactory transient behavior.
Over the last few decades digital computer technology has matured to the point that the engineering world has witnessed a revolution in the way in which mathematical problems are solved. Problems too complex to be sol...
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Over the last few decades digital computer technology has matured to the point that the engineering world has witnessed a revolution in the way in which mathematical problems are solved. Problems too complex to be solved analytically can now be solved in a feasible manner, by employing a computersystem which emulates the human learning and decision-making process. Areas such as neural networks, expert systems, and fuzzy logic systems implement `human-like' capabilities. This work focuses on the design of Adaptive Fuzzy Logic control of an anti-lock braking system. This controller will never know the exact plant model, but will know input-output relations of the plant (training data). The controller will initially employ a priori training data to control the braking system, but will continue to train on-line while continuously updating confidence parameters and placement of fuzzy sets by employing optimization algorithms. Old data will be slowly forgotten while up-to-date training data are acquired. Thus, changes in road conditions or in the plant itself will be learned.
This paper presents a new robust and optimal fuzzy control. The optimal fuzzy controller is designed by solving the minimization problem that minimizes the upper bound of a given quadratic performance index. Next, rob...
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This paper presents a new robust and optimal fuzzy control. The optimal fuzzy controller is designed by solving the minimization problem that minimizes the upper bound of a given quadratic performance index. Next, robust stability conditions for a class of uncertain fuzzy systems are derived. The robust fuzzy controller is designed so as to maximize the norm of the uncertain blocks in a Takagi-Sugeno fuzzy model. More importantly, the control problem that simultaneously considers both the optimal fuzzy controller design and the robust fuzzy controller design is defined and is efficiently solved via convex optimization techniques based on LMIs.
Identification methods are applied to experimental data (hand motion) from a design study on a human interface system. The internal model of the Kalman Filter employed for the state estimation implicitly utilizes two ...
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Identification methods are applied to experimental data (hand motion) from a design study on a human interface system. The internal model of the Kalman Filter employed for the state estimation implicitly utilizes two competing systems (involving an agonist and an antagonist human muscle actuator). The parameters (parsimonious representation) are obtained by minimizing the sums of the squares of the output error residuals, which are tested for whiteness. This technique is a generalization of a method borrowed from pharmacological studies.
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