1,191 research outputs found
Separating Controller Design from Closed-Loop Design: A New Perspective on System-Level Controller Synthesis
We show that given a desired closed-loop response for a system, there exists an affine subspace of controllers that achieve this response. By leveraging the existence of this subspace, we are able to separate controller design from closed-loop design by first synthesizing the desired closed-loop response and then synthesizing a controller that achieves the desired response. This is a useful extension to the recently introduced System Level Synthesis framework, in which the controller and closed-loop response are jointly synthesized and we cannot enforce controller-specific constraints without subjecting the closed-loop map to the same constraints.We demonstrate the importance of separating controller design from closed-loop design with an example in which communication delay and locality constraints cause standard SLS to be infeasible. Using our new two-step procedure, we are able to synthesize a controller that obeys the constraints while only incurring a 3% increase in LQR cost compared to the optimal LQR controller
Distributed Robust Control for Systems with Structured Uncertainties
We present D-Phi iteration: an algorithm for distributed, localized, and
scalable robust control of systems with structured uncertainties. This
algorithm combines the System Level Synthesis (SLS) parametrization for
distributed control with stability criteria from L1, L-infinity, and nu robust
control. We show in simulation that this algorithm achieves near-optimal
nominal performance (within 12% of the LQR controller) while doubling or
tripling the stability margin (depending on the stability criterion) compared
to the LQR controller. To the best of our knowledge, this is the first
distributed and localized algorithm for structured robust control; furthermore,
algorithm complexity depends only on the size of local neighborhoods and is
independent of global system size. We additionally characterize the suitability
of different robustness criteria for distributed and localized computation, and
discuss open questions on the topic of distributed robust control.Comment: Submitted to CDC 202
Separating Controller Design from Closed-Loop Design: A New Perspective on System-Level Controller Synthesis
We show that given a desired closed-loop response for a system, there exists an affine subspace of controllers that achieve this response. By leveraging the existence of this subspace, we are able to separate controller design from closed-loop design by first synthesizing the desired closed-loop response and then synthesizing a controller that achieves the desired response. This is a useful extension to the recently introduced System Level Synthesis framework, in which the controller and closed-loop response are jointly synthesized and we cannot enforce controller-specific constraints without subjecting the closed-loop map to the same constraints.We demonstrate the importance of separating controller design from closed-loop design with an example in which communication delay and locality constraints cause standard SLS to be infeasible. Using our new two-step procedure, we are able to synthesize a controller that obeys the constraints while only incurring a 3% increase in LQR cost compared to the optimal LQR controller
Hexyl (E)-3-(3,4-dihyÂdroxyÂphenÂyl)acrylate
The title molÂecule, C15H20O4, has an E conformation about its C=C bond and is almost planar (r.m.s. deviation of all non-H atoms = 0.04 Å). The crystal structurere features O—H⋯O and C—H⋯O hydrogen bonds
A Low Rank Approach to Minimize Sensor-to-Actuator Communication in Finite Horizon Output Feedback
Many modern controllers are composed of different components that communicate
in real-time over some network with limited resources. In this work, we are
interested in designing a controller that can be implemented with a minimum
number of sensor-to-actuator messages, while satisfying safety constraints over
a finite horizon. For finite horizon problems, a linear time-varying controller
with memory can be represented as a block-lower-triangular matrix. We show that
the rank of this matrix exactly captures the minimum number of messages needed
to be sent from the sensors to actuators to implement such a controller.
Moreover, we introduce a novel matrix factorization called causal factorization
that gives the required implementation. Finally, we show that the rank of the
controller is the same as the rank of the Youla parameter, enabling the Youla
parametrization (or analogous parametrizations) to be used to design the
controller, which reduces the overall design problem into a rank minimization
one over a convex set. Finally, convex relaxations for rank are used to
demonstrate that our approach leads to 20-50% less messages on a simulation
than a benchmark method.Comment: 6 pages, 5 figure
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