The set of equations to be solved for parameter estimation in model updating has no unique solution when, as will often be the case in structural applications, the dimensionality of the model exceeds the number of target parameters estimated from experiments. One approach for enlarging the target space is to create closed-loop systems that, in addition, can be designed with pole sensitivities favorable for updating the model. The present paper will focus on designing gains for model updating using a recently proposed virtual implementation of output feedback, which allows computation of several closed-loop systems, from a single open loop realization and removes the constraint of closed-loop stability. The gains are designed through an eigenstructure assignment procedure, in which the model parameters of interest in the updating are divided into two different classes; one where the pole sensitivities with respect to the parameters are to be enhanced and one where they are to be reduced. A numerical example with a structural system is presented that demonstrates the merit of the proposed gain design procedure.
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Design of controllers with distributed central pattern generator architecture for adaptive oscillations
This article introduces a systematic method for designing a distributed nonlinear controller to achieve multiple distinct gaits, each of which is characterized by a prescribed oscillation profile and velocity, for a class of locomotion systems. We base the controller on the central pattern generator (CPG), a neural circuit which governs repetitive motions, such as walking and swimming, in most animals. First, we establish a general method for designing a nonlinear CPG‐inspired controller to assign a single gait for a linear plant; we show that this problem reduces to an eigenstructure assignment problem for which a solution has recently become available. We then extend the design to an adaptive, structured controller that can adjust the gait in response to variations in the environment. The essential problem becomes a controller design to satisfy different eigenstructure conditions for different plants; a computationally tractable formulation is provided for this problem. We provide two numerical examples using a link‐chain model as a plant representative of animals that move through undulatory motions, such as leeches or eels, to demonstrate the efficacy of this theory. In the first example, we employ an analytical condition for eigenstructure assignment to design an unstructured controller that assigns a single gait for the link‐chain model. The second example searches for a structured controller to assign two different gaits that can be switched using a higher level command.
more » « less- NSF-PAR ID:
- 10455031
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- International Journal of Robust and Nonlinear Control
- Volume:
- 31
- Issue:
- 2
- ISSN:
- 1049-8923
- Page Range / eLocation ID:
- p. 694-714
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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