This paper presents a learning mechanism to extract a action pattern under various network conditions. A multi-attribute learning mechanism has the ability to indicate the success probability of each action pattern un...
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This paper presents a learning mechanism to extract a action pattern under various network conditions. A multi-attribute learning mechanism has the ability to indicate the success probability of each action pattern under given network conditions. Not only observed network information but also qualitative factors can be used in this mechanism. It is an effective way to support decision-making to take multiple factors including probabilistic or uncertain factors. A dynamic routing scheme employing this mechanism and a performance evaluation are shown as an application example.
As magnetic bearing applications become more complicated, the need for accurate models of the controlled bearing systems becomes more important. Ordinarily, accurate models are obtained by first levitating and then pe...
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As magnetic bearing applications become more complicated, the need for accurate models of the controlled bearing systems becomes more important. Ordinarily, accurate models are obtained by first levitating and then performing system identification. The method for measuring the actuator properties often involves lengthy tests that are performed manually. This paper presents the initial research into using adaptive estimation to identify unknown and parameters and disturbances for a simple one-dimensional magnetic bearing system. Analysis of the plant and construction of an estimator are presented with simulation results that show the estimator performance. Lastly, a more general model with hysteresis is parameterized and estimated.
An underwater manipulator mounted on a mobile platform such as underwater vehicles is a multi-body dynamic system. The hydrodynamics of the manipulator mounted on the vehicle are poorly known and time-varying. Further...
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An underwater manipulator mounted on a mobile platform such as underwater vehicles is a multi-body dynamic system. The hydrodynamics of the manipulator mounted on the vehicle are poorly known and time-varying. Furthermore, its motion is disturbed by the vehicle motion. This paper presents a non-regressor based adaptive control scheme for the trajectory tracking of underwater mobile platform-mounted manipulators. The presented adaptive controlsystem dose not require any information about the system. The adaptive control law estimates control gains defined by the combinations of the bounded constants of system parameter matrices. To evaluate the performance of the adaptive controller, computer simulation was performed with a two-link planar manipulator mounted on a one degree-of-freedom mobile platform. The effects of hydrodynamic forces acting on the manipulator are included.
Our goal is to develop a complete mathematical model to perform nonlinear analysis and design for multivariable diesel-electric drivetrains. This allows one to study energy conversion needed to perform sophisticated a...
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Our goal is to develop a complete mathematical model to perform nonlinear analysis and design for multivariable diesel-electric drivetrains. This allows one to study energy conversion needed to perform sophisticated analysis of hybrid-electric vehicle performance (driveability and controllability, maneuverability and agility), efficiency, fuel economy and exhaust emission, etc. The full spectrum of the physical phenomena of interconnected energy conversion processes in diesel and electric machines are studied in the contest of multivariable nonlinear analysis, optimization and control. Using a set of differential equations derived, which maps the steady-state and dynamic behavior of high-performance diesel-electric powertrains, an optimal energy management system is designed and tested.
The problem of change detection in the poles of signals having unknown time varying zeroes is addressed. It is used, instead of the test statistics based upon the standard likelihood ratio approach, which is of no hel...
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The problem of change detection in the poles of signals having unknown time varying zeroes is addressed. It is used, instead of the test statistics based upon the standard likelihood ratio approach, which is of no help in this case because of the unknown zeroes, a test statistics based on an identification method (instrumental variables), which is known to decouple the AR and MA coefficients of the model. The procedure has been used for change detection in modal characteristics of a single degree of freedom oscillator and of a vibrating structure, a multi-story reinforced concrete building, subject to a strong seismic motion.
This paper presents a novel testbed for vehicle control experiments: The Illinois Roadway Simulator (IRS). This is a scaled roadway suitable for easily visualizing preliminary vehicle control studies. The concept of t...
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This paper presents a novel testbed for vehicle control experiments: The Illinois Roadway Simulator (IRS). This is a scaled roadway suitable for easily visualizing preliminary vehicle control studies. The concept of the IRS is given along with the details of its design and construction. A review of vehicle dynamics gives the standard Bicycle Model for linear operating conditions. The parameters of the model are then obtained for representative IRS vehicles. The resulting vehicle dynamics are then compared with dynamics of full-scale vehicles for dynamic similitude. The dynamic similitude comparison is the key to gaining confidence in the scaled testbed as an accurate representation of actual vehicles. A series of experimental verifications are used to match the identified vehicle dynamics to the responses predicted by the standard vehicle model with some additional augmentations.
This paper proposes a unified power flow approach to the modeling of hybrid electric vehicles, resulting in a highly scalable and reconfigurable modeling tool. Furthermore, this simulation tool is used in conjunction ...
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This paper proposes a unified power flow approach to the modeling of hybrid electric vehicles, resulting in a highly scalable and reconfigurable modeling tool. Furthermore, this simulation tool is used in conjunction with a fuzzy logic, ruled-based controller to optimize the energy efficiency through the control of the power flows of a parallel HEV configuration. Finally, this modeling and control approach is applied to the design and optimization of a hybrid electric sport-utility vehicle. The results show that this modeling approach provides the required modeling flexibility, and that the model and the control strategy based on this power flow approach can be optimized to yield significant fuel economy gains.
This paper presents the design of a differentiable, robust tracking controller for a mobile robot system. The controller provides robustness with regard to parametric uncertainty and additive bounded disturbances in t...
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This paper presents the design of a differentiable, robust tracking controller for a mobile robot system. The controller provides robustness with regard to parametric uncertainty and additive bounded disturbances in the dynamic model. Through the use of a dynamic oscillator and a Lyapunov-based stability analysis, we demonstrate that the position/orientation tracking errors exponentially converge to a neighborhood about zero that can be made arbitrarily small (i.e., the controller ensures that the tracking error is globally uniformly ultimately bounded (GUUB)). In addition, we illustrate how the robust tracking controller can be reconfigured as a variable structure controller that ensures global exponential regulation to an arbitrary desired setpoint.
This paper considers position and attitude control of large space structures composed of a number of subsystems which are interconnected by springs and dampers. A decentralized control law of dynamic displacement feed...
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This paper considers position and attitude control of large space structures composed of a number of subsystems which are interconnected by springs and dampers. A decentralized control law of dynamic displacement feedback compatible with subsystems is applied under the assumption that sensors and actuators are collocated. The overall closed-loop system is robustly stable against perturbations in mass, damping, and stiffness if rigid modes of each subsystem are controllable and observable. The objective of this paper is to derive conditions under which stability of the overall system is preserved even when some local controllers fail. The conditions are expressed in terms of the stiffness (or damping) matrices and interconnection location matrices of the subsystems whose local controllers fail.
Automatic Gage control (A.G.C.) system is important for the cold tandem mill rolling of steel. A new gage and tension controlsystem based on Inverse Linear Quadratic (I.L.Q.) design theory which is superior to the co...
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Automatic Gage control (A.G.C.) system is important for the cold tandem mill rolling of steel. A new gage and tension controlsystem based on Inverse Linear Quadratic (I.L.Q.) design theory which is superior to the conventional cross control law in point of preventing undesirable strip vibration, is studied. First, the I.L.Q. controller for the first stand of the cold tandem mill is designed. Next, the I.L.Q. control law is analyzed, and the original controller was modified. Finally, we confirmed that the modified I.L.Q. controller is able to improve the strip gage accuracy through the simulation and the experimental test. The focus of this study is the analysis of the function of the control loops, using parametric representation of the control law.
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