TY - GEN
T1 - Qualitative heterogeneous control of higher order systems
AU - Ramamoorthy, Subramanian
AU - Kuipers, Benjamin
PY - 2003
Y1 - 2003
N2 - This paper presents the qualitative heterogeneous control framework, a methodology for the design of a controlled hybrid system based on attractors and transitions between them. This framework designs a robust controller that can accommodate bounded amounts of parametric and structural uncertainty. This framework provides a number of advantages over other similar techniques. The local models used in the design process are qualitative, allowing the use of partial knowledge about system structure, and nonlinear, allowing regions and transitions to be defined in terms of dynamical attractors. In addition, we define boundaries between local models in a natural manner, appealing to intrinsic properties of the system. We demonstrate the use of this framework by designing a novel control algorithm for the cart-pole system. In addition, we illustrate how traditional algorithms, such as linear quadratic regulators, can be incorporated within this framework. The design is validated by experiments with a physical system.
AB - This paper presents the qualitative heterogeneous control framework, a methodology for the design of a controlled hybrid system based on attractors and transitions between them. This framework designs a robust controller that can accommodate bounded amounts of parametric and structural uncertainty. This framework provides a number of advantages over other similar techniques. The local models used in the design process are qualitative, allowing the use of partial knowledge about system structure, and nonlinear, allowing regions and transitions to be defined in terms of dynamical attractors. In addition, we define boundaries between local models in a natural manner, appealing to intrinsic properties of the system. We demonstrate the use of this framework by designing a novel control algorithm for the cart-pole system. In addition, we illustrate how traditional algorithms, such as linear quadratic regulators, can be incorporated within this framework. The design is validated by experiments with a physical system.
U2 - 10.1007/3-540-36580-X_31
DO - 10.1007/3-540-36580-X_31
M3 - Conference contribution
SN - 978-3-540-00913-9
T3 - Lecture Notes in Computer Science
SP - 417
EP - 434
BT - Hybrid systems: Computation and control
PB - Springer
ER -