The use of mobile actuators for the control of spatially distributed systems governed by PDEs results in both implementational and computational challenges. First it requires the backward-in-time solution to the actuator guidance and the backward-in-time solution to the control operator Riccati equation. A way to address this computational challenge is to consider a continuous-discrete alternative whereby the mobile actuator is repositioned at discrete instances and resides in a specific spatial location for a certain time interval. In order to find optimal paths for a given time interval, a set of feasible locations is derived using the reachability set. These reachability sets are further constrained to take into account the time it takes to travel to any spatial position with a prescribed maximum velocity. The proposed hybrid continuous-discrete control and actuator guidance is demonstrated for a 2D diffusion PDE that uses no constraints and angular constraints on the actuator motion.
Controlling 2D PDEs using mobile collocated actuators-sensors and their simultaneous guidance constrained over path-dependent reachability regions
Employing mobile actuators and sensors for control and estimation of spatially distributed processes offers a significant advantage over immobile actuators and sensors. In addition to the control performance improvement, one also comes across the economic advantages since fewer devices, if allowed to be repositioned within a spatial domain, must be employed. While simulation studies of mobile actuators report superb controller performance, they are far from reality as the mechanical constraints of the mobile platforms carrying actuators and sensors have to satisfy motional constraints. Terrain platforms cannot behave as point masses without inertia; instead they must satisfy constraints which are adequately represented as path-dependent reachability sets. When the control algorithm commands a mobile platform to reposition itself in a different spatial location within the spatial domain, this does not occur instantaneously and for the most part the motion is not omnidirectional. This constraint is combined with a computationally feasible and suboptimal control policy with mobile actuators to arrive at a numerically viable control and guidance scheme. The feasible control decision comes from a continuous-discrete control policy whereby the mobile platform carrying the actuator is repositioned at discrete times and dwells in a specific position for a certain time interval. Moving to more »
- Award ID(s):
- 1825546
- Publication Date:
- NSF-PAR ID:
- 10333825
- Journal Name:
- 021 American Control Conference (ACC)
- Page Range or eLocation-ID:
- 1491 to 1496
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/10.23919/ACC50511.2021.9482892
