Author ORCID Identifier
https://orcid.org/0009-0000-0284-5830
Date Available
4-1-2025
Year of Publication
2024
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy (PhD)
College
Engineering
Department/School/Program
Mechanical Engineering
Advisor
Dr. Jesse B. Hoagg
Abstract
This dissertation addresses challenges in control design for safety-critical robotic systems with input constraints. It focuses on developing novel control barrier function (CBF) approaches to ensure safety while optimizing performance. The work is motivated by the limitations of traditional methods in handling nonlinear systems with multiple constraints and actuator limits.
Three main contributions are presented. First, a soft-minimum barrier function is introduced, utilizing finite-time horizon predictions to create control forward invariant subsets of the safe set while respecting actuator constraints. This method is extended to multiple backup controls, which can enlarge the safe operating region.
Second, a technique for composing multiple CBFs with different relative degrees into a single relaxed CBF is developed. This enables a closed-form control solution that optimizes performance while satisfying both safety and input constraints.
Finally, a guaranteed-safe model-predictive-path-integral (GS-MPPI) control algorithm is proposed, integrating CBFs with MPPI to address the myopic behavior of traditional CBF methods while maintaining long-term performance optimization. This method ensures all trajectories generated for MPPI planning are safe, thus, improving computational efficiency.
The effectiveness of these approaches is demonstrated through simulations of robotic systems, including inverted pendulums and nonholonomic ground robots.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2024.402
Funding Information
This study was supported by the National Science Foundation (1849213,1932105,193210) and the Air Force Office of Scientific Research (FA9550-20-1-0028) from 2019 to 2024.
Recommended Citation
Rabiee, Pedram, "Provably Safe Control for Input-Constrained Robotic Systems" (2024). Theses and Dissertations--Mechanical Engineering. 230.
https://uknowledge.uky.edu/me_etds/230
