Abstract
This paper presents techniques to linearly combine the sensor measurements and/or actuator inputs of a linear time-invariant system to obtain a new system that is interior conic with prescribed bounds. In the optimal sensor combination problem, a desired system output is defined, and in the optimal actuator combination problem, a desired system input is defined, along with a frequency bandwidth in which the desired system input or output should be matched. The simultaneous optimal sensor and actuator combination problem includes desired system outputs and inputs. In all cases, the weighted H2 or H∞ norm of the difference between the system with linearly combined sensors or actuators and the desired system is minimized while rendering the new system interior conic with prescribed bounds. The weighting transfer matrix used in the H2 - or H∞ -optimization problem is determined by the frequency bandwidth of interest. The individual sensor and actuator combination methods involve linear matrix inequality constraints and are posed as convex optimization problems, whereas the combined sensor and actuator method is an iterative procedure composed of convex optimization steps. Numerical examples illustrate superior tracking performance with the proposed sensor and actuator combination techniques over comparable techniques in the literature when implemented with a simple feedback controller. Robust asymptotic stability of the closed-loop system to plant uncertainty is demonstrated in the numerical examples.
Original language | English (US) |
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Pages (from-to) | 6288-6310 |
Number of pages | 23 |
Journal | International Journal of Robust and Nonlinear Control |
Volume | 29 |
Issue number | 17 |
DOIs | |
State | Published - Nov 25 2019 |
Bibliographical note
Publisher Copyright:© 2019 John Wiley & Sons, Ltd.
Keywords
- Conic Sector Theorem
- LMIs
- actuator selection
- linear systems
- robust control
- sensor selection
- uncertain systems