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Found 8 papers, 0 papers with code
Stabilizing switched nonlinear systems under restricted but arbitrary switching signals
This paper deals with input/output-to-state stability (IOSS) of switched nonlinear systems whose switching signals obey pre-specified restrictions on admissible switches between the subsystems and admissible dwell times on the subsystems.
A Sparsity Approach to Scheduling and Control of Networked Systems
Our key contribution is a new algorithm that co-designs (a) an allocation scheme of the communication network among the plants (scheduling logic) and (b) the control inputs for the plants accessing the network (control logic) under which given non-zero initial states are steered to zero in a given time horizon for all the plants in the NCS.
A probabilistic algorithm for scheduling networked control systems under data losses
This paper deals with the design of scheduling logics for networked control systems (NCSs) whose communication networks have limited capacity and are prone to data losses.
A probabilistic scheduling algorithm for networked control systems
First, we present a probabilistic algorithm to design scheduling logics that, under certain conditions on the plant and controller dynamics and the capacity of the network, ensure stochastic stability of each plant in an NCS.
Learning event-driven switched linear systems
We propose an automata theoretic learning algorithm for the identification of black-box switched linear systems whose switching logics are event-driven.
A reinforcement learning approach to hybrid control design
Second, we model a set of benchmark examples of hybrid control design problem in the proposed MDP framework.
Data-driven switching logic design for switched linear systems
This paper deals with stabilization of discrete-time switched linear systems when explicit knowledge of the state-space models of their subsystems is not available.
Data-based computation of stabilizing minimum dwell times for discrete-time switched linear systems
A numerical example is presented to demonstrate the proposed algorithm.
