scholarly journals Reduced-order multiple model adaptive controller for flexible spacestructure

1992 ◽  
Vol 28 (3) ◽  
pp. 756-767 ◽  
Author(s):  
P.S. Maybeck ◽  
M.R. Schore
Author(s):  
Vu Trieu Minh

This chapter presents the design and calculation procedure for a teleoperation and remote control of a medical robot that can help a doctor to use his hands/fingers to examine patients in remote areas. This teleoperation system is simple and low cost, connected to the global Internet system, and through the interaction with the master device, the medical doctor is able to communicate control signals for the slave device. This controller is robust to the time-variant delays and the environment uncertainties while assuring the stability and the high transparent performance. A novel theoretical framework and algorithms are developed with time forward observer-based adaptive controller and neural network-based multiple model. The system allows the medical doctor to feel the real sense of the remote environments.


Author(s):  
Mark J. Balas ◽  
Susan A. Frost

Linear infinite dimensional systems are described by a closed, densely defined linear operator that generates a continuous semigroup of bounded operators on a general Hilbert space of states and are controlled via a finite number of actuators and sensors. Many distributed applications are included in this formulation, such as large flexible aerospace structures, adaptive optics, diffusion reactions, smart electric power grids, and quantum information systems. We have developed the following stability result: an infinite dimensional linear system is Almost Strictly Dissipative (ASD) if and only if its high frequency gain CB is symmetric and positive definite and the open loop system is minimum phase, i.e. its transmission zeros are all exponentially stable. In this paper, we focus on infinite dimensional linear systems for which a fixed gain linear infinite or finite dimensional controller is already in place. It is usually true that fixed gain controllers are designed for particular applications but these controllers may not be able to stabilize the plant under all variations in the operating domain. Therefore we propose to augment this fixed gain controller with a relatively simple direct adaptive controller that will maintain stability of the full closed loop system over a much larger domain of operation. This can ensure that a flexible structure controller based on a reduced order model will still maintain closed-loop stability in the presence of unmodeled system dynamics. The augmentation approach is also valuable to reduce risk in loss of control situations. First we show that the transmission zeros of the augmented infinite dimensional system are the open loop plant transmission zeros and the eigenvalues (or poles) of the fixed gain controller. So when the open-loop plant transmission zeros are exponentially stable, the addition of any stable fixed gain controller does not alter the stability of the transmission zeros. Therefore the combined plant plus controller is ASD and the closed loop stability when the direct adaptive controller augments this combined system is retained. Consequently direct adaptive augmentation of controlled linear infinite dimensional systems can produce robust stabilization even when the fixed gain controller is based on approximation of the original system. These results are illustrated by application to a general infinite dimensional model described by nuclear operators with compact resolvent which are representative of distributed parameter models of mechanically flexible structures. with a reduced order model based controller and adaptive augmentation.


2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Haisen Ke ◽  
Jiang Li

Multiple model adaptive control has been investigated extensively during the last ten years in which the “switching” or “switching and tuning” have emerged as the mainly approaches. It is the “switching” that can improve the transient performance to some extent and also make it difficult to analyze the stability of the system with multiple models adaptive controller. Towards this goal, this paper develops a novel multiple models adaptive controller for a class of nonlinear system in parameter-strict-feedback form which not only improves the transient performance significantly, but also guarantees the stability of all the states of the closed-loop system. A simulation example is proposed to illustrate the effectiveness of the developed multiple models adaptive controller.


Robotica ◽  
2005 ◽  
Vol 23 (6) ◽  
pp. 721-729 ◽  
Author(s):  
M. Kemal Ciliz ◽  
M. Ömer Tuncay

In this paper, different adaptive control algorithms will be experimentally tested on a two axis SCARA type direct drive robot arm, and the performance of these algorithms will be compared. Being a direct drive system, the nonlinear effects, arising from the dynamics of the manipulator under high velocities, are directly reflected in the control of the manipulator. This makes the manipulator a more efficient test bed for testing the efficiency of the proposed adaptive schemes. In the experiments, we used fast trajectories rather than slow ones to observe how the proposed controllers compensate the dynamic nonlinear effects of manipulator dynamics. We will test some known adaptive control algorithms given in the literature along with our proposed adaptive control scheme which makes use of multiple models.


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