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Inversion-Based Optimal Output Transition With Input and Time Constraints for Non-Minimum Phase Linear System

[+] Author Affiliations
Jiangbo Liu, Qingze Zou

Rutgers, The State University of New Jersey, New Brunswick, NJ

Paper No. DSCC2014-6316, pp. V002T25A005; 8 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME


In this article, the problem of trajectory design and tracking of non-periodic tracking-transition switching for non-minimum phase linear systems is considered. Such a trajectory design and tracking problem exists in applications such as nanomanipulation, robotic operation, and hard-disk control, where the whole trajectory consists of tracking sessions with the application-specified desired trajectory to be tracked, and transition sessions with the output trajectory to be designed. This problem becomes challenging as multiple control objectives need to be achieved. The proposed approach extends the previous work that attained smooth output transition and smooth tracking-transition switching to further achieve amplitude-constrained input-energy minimization and transition time minimization. First, the constrained input optimization problem is converted to an unconstrained input minimization problem. Then the optimal output and input are obtained by using an improved conjugate gradient method. Finally, the total transition time is further minimized via one dimensional search. The proposed approach is illustrated through a simulation example in probe-based nanomanipulation utilizing a piezoelectric actuator.

Copyright © 2014 by ASME
Topics: Linear systems



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