Recursos de colección
Caltech Authors (160.918 recursos)
Repository of works by Caltech published authors.
Group = Control and Dynamical Systems Technical Reports
Repository of works by Caltech published authors.
Group = Control and Dynamical Systems Technical Reports
Dathathri, Sumanth; Murray, Richard M.
Temporal logic based synthesis approaches are often
used to find trajectories that are correct-by-construction for
tasks in systems with complex behavior.
Some examples of such tasks include synchronization
for multi-agent hybrid systems, reactive motion planning for
robots. However, the scalability of such approaches is of concern and
at times a bottleneck when transitioning from theory to
practice. In this paper, we identify a class of problems
in the GR(1) fragment of linear-time temporal
logic (LTL) where the synthesis problem allows for a
decomposition that enables easy parallelization.
This decomposition also reduces the alternation depth,
resulting
in more efficient synthesis.
A...
Dathathri, Sumanth; Livingston, Scott C.; Reder, Leonard J.; Murray, Richard M.
This paper describes the implementation of an interface connecting the two tools : the JPL SCA (Statechart Autocoder) and TuLiP (Temporal Logic Planning Toolbox) to enable the automatic synthesis of low level implementation code directly from formal specifications. With system dynamics, bounds on uncertainty and formal specifications as inputs, TuLiP synthesizes Mealy machines that are correct-by-construction. An interface is built that automatically translates these Mealy machines into UML statecharts. The SCA accepts the UML statecharts (as XML files) to synthesize flight-certified implementation code. The functionality of the interface is demonstrated through three example systems of varying complexity a) a simple...
Han, Shuo; Topcu, Ufuk; Tao, Molei; Owhadi, Houman; Murray, Richard M.
How does one evaluate the performance of a stochastic system in the absence of a perfect model (i.e. probability distribution)? We address this question under the framework of optimal uncertainty quantification (OUQ), which is an information-based approach for worst-case analysis of stochastic systems. We are able to generalize previous results and show that the OUQ problem can be solved using convex optimization when the function under evaluation can be expressed in a polytopic canonical form (PCF). We also propose iterative methods for scaling the convex formulation to larger systems. As an application, we study the problem of storage placement in...
Zhao, Changhong; Topcu, Ufuk; Low, Steven H.
Frequency regulation and generation-load balancing are key issues in power transmission networks. Complementary to generation control, loads provide flexible and fast responsive sources for frequency regulation, and local frequency measurement capability of loads offers the opportunity of decentralized control. In this paper, we propose an optimal load control problem, which balances the load reduction (or increase) with the generation shortfall (or surplus), resynchronizes the bus frequencies, and minimizes a measure of aggregate disutility of participation in such a load control. We find that, a frequency-based load control coupled with the dynamics of swing equations and branch power flows serve as...
Gan, Lingwen; Topcu, Ufuk; Low, Steven H.
To address the grid-side challenges associated with the anticipated high electric vehicle (EV) penetration level, various charging protocols have been proposed in the literature. Most if not all of these protocols assume continuous charging rates and allow intermittent charging. However, due to charging technology limitations, EVs can only be charged at a fixed rate, and the intermittency in charging shortens the battery lifespan. We consider these charging requirements, and formulate EV charging scheduling as a discrete optimization problem.
We propose a stochastic distributed algorithm to approximately
solve the optimal EV charging scheduling problem in an
iterative procedure. In each iteration, the transformer receives
charging...
Zhao, Changhong; Topcu, Ufuk; Low, Steven H.
Matching demand with supply and regulating frequency
are key issues in power system operations. Flexibility
and local frequency measurement capability of loads offer new regulation mechanisms through load control. We present a
frequency-based fast load control scheme which aims to match
total demand with supply while minimizing the global end-use
disutility. Local frequency measurement enables loads to make decentralized decisions on their power from the estimates of total demand-supply mismatch. To resolve the errors in such estimates caused by stochastic frequency measurement errors, loads communicate via a neighborhood area network. Case studies show that the proposed load control can balance demand with supply and restore...
Zhao, Changhong; Topcu, Ufuk; Low, Steven H.
Maintaining demand-supply balance and regulating frequency are key issues in power system control. Conventional approaches focus on adjusting the generation so that it follows the load. However, relying on solely regulating generation is inefficient, especially for power systems where contingencies like sudden loss in generation or sudden change in load frequently occur and the proportion of intermittent renewable power is increasing. We present a frequency-based load control scheme for demand-supply balancing and frequency regulation. We formulate a load control optimization problem which aims to balance the change in load with the change in supply while minimizing the overall end-use disutility....
Zheng, Zhi Qiang (Alex)
Most practical control problems are dominated by constraints. Although a rich theory has been developed for the robust control of linear systems, very little is known about the robust control of linear systems with constraints. Over the years various model-based algorithms (given a generic term Model Predictive Control) have been used in industry to control complex multivariable systems with operating constraints. The design and tuning of these controllers is difficult for two reasons:
1. Process models are always inaccurate which implies that the controllers must be robust.
2. Even in the simplest case where process rnodels are linear, the overall...