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We consider robust control synthesis for linear systems with complex specifications that are affected by uncertain disturbances. This letter is motivated by autonomous systems interacting with partially known, time-varying environments. Given a specificati ...
The steady advances of computational methods make model-based optimization an increasingly attractive method for process improvement. Unfortunately, the available models are often inaccurate. The traditional remedy is to update the model parameters, but th ...
Due to recent advances, constraint solvers have become efficient tools for synthesizing optimum Boolean circuits. We take advantage of this by showing how SAT based exact synthesis may be used as a method for finding minimum length Boolean chains. As oppos ...
Humanoid robots have many degrees of freedom which ideally enables them to accomplish different tasks. From a control viewpoint, however, the geometric complexity makes planning and control difficult. Favoring controllability properties, it is popular to o ...
Holant is a framework of counting characterized by local constraints. It is closely related to other well-studied frameworks such as the counting constraint satisfaction problem (#CSP) and graph homomorphism. An effective dichotomy for such frameworks can ...
Nematic elastomers and glasses are solids that display spontaneous distortion under external stimuli. Recent advances in the synthesis of sheets with controlled heterogeneities have enabled their actuation into nontrivial shapes with unprecedented energy d ...
This paper presents a coordinated primal-dual interior point (PDIP) method for solving structured convex linear and quadratic programs (LP-QP) in a distributed man- ner. The considered class of problems represents a multi-agent setting, where the aggregate ...
The major research in the resource management literature focuses primarily on two directions: 1) specification languages for formulating resource requests and 2) constraint problems modelling allocation and scheduling. Both directions assume the knowledge ...
This paper deals with a novel Plug-and-Play (PnP) architecture for the control and monitoring of Large-Scale Systems (LSSs). The proposed approach integrates a distributed Model Predictive Control (MPC) strategy with a distributed Fault Detection (FD) arch ...
We consider distributed multitask learning problems over a network of agents where each agent is interested in estimating its own parameter vector, also called task, and where the tasks at neighboring agents are related according to a set of linear equalit ...