Title :
Structured Linearization of Discrete Mechanical Systems for Analysis and Optimal Control
Author :
Johnson, Eric ; Schultz, Jamie ; Murphey, Todd
Author_Institution :
Southwest Res. Inst., San Antonio, TX, USA
Abstract :
Variational integrators are well-suited for simulation of mechanical systems because they preserve mechanical quantities about a system such as momentum, or its change if external forcing is involved, and holonomic constraints. While they are not energy-preserving they do exhibit long-time stable energy behavior. However, variational integrators often simulate mechanical system dynamics by solving an implicit difference equation at each time step, one that is moreover expressed purely in terms of configurations at different time steps. This paper formulates the first- and second-order linearizations of a variational integrator in a manner that is amenable to control analysis and synthesis, creating a bridge between existing analysis and optimal control tools for discrete dynamic systems and variational integrators for mechanical systems in generalized coordinates with forcing and holonomic constraints. The forced pendulum is used to illustrate the technique. A second example solves the discrete Linear Quadratic Regulator (LQR) problem to find a locally stabilizing controller for a 40 DOF system with six constraints.
Keywords :
control system analysis; control system synthesis; discrete systems; linear quadratic control; pendulums; 40 DOF system; control analysis; control synthesis; controller stabilization; discrete LQR problem; discrete dynamic systems; discrete linear quadratic regulator problem; discrete mechanical systems; energy behavior; external forcing; first-order linearization; forced pendulum; holonomic constraints; implicit difference equation; mechanical system dynamics simulation; mechanical system simulation; optimal control tools; second-order linearization; structured linearization; variational integrators; Approximation methods; Equations; Mathematical model; Mechanical systems; Optimal control; Torque; Trajectory; Simulation; mechanism analysis; optimal control;
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
DOI :
10.1109/TASE.2014.2333239