Robust control and control system integration using finite-signal-to-noise model
Abstract
The objective of this research is to develop a systematic method to solve some control system integration problems. The control system integrations considered here include: (i) integrating hardware specifications with feedback control law development; (ii) integrating system identification (modeling) with feedback control law development; (iii) integrating system design with feedback control law development. The key concept used here is the finite-signal-to-noise model and the core theory is the control synthesis theory to tolerate the finite-signal-to-noise models. The main contributions of this research contain a complete control theory for systems with finite-signal-to-noise effects and the associated iterative but convergent algorithms, designing together the signal-to-noise ratios and the feedback control law, designing the system dynamics (passive elements) with the active elements in a control system. This research provides the practical engineers with the primary knowledge about the specifications of control system components, about how to design a high performance control system with as low cost as possible, and about how to modify system dynamics (for example damping and stiffness) to achieve better vibration performance with less power consumption.
Degree
Ph.D.
Advisors
Skelton, Purdue University.
Subject Area
Electrical engineering|Mechanical engineering
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