ACM Transactions on Programming Languages and Systems (TOPLAS)
Efficient distributed event-driven simulations of multiple-loop networks
Communications of the ACM
Reliable solution of special event location problems for ODEs
ACM Transactions on Mathematical Software (TOMS)
State event location in differential-algebraic models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Studies in hybrid systems: modeling, analysis, and control
Studies in hybrid systems: modeling, analysis, and control
Timewarp rigid body simulation
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Efficient optimistic parallel simulations using reverse computation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Solving Ordinary Differential Equations with Discontinuities
ACM Transactions on Mathematical Software (TOMS)
Cost/benefit analysis of interval jumping in power-control simulation
Proceedings of the 32nd conference on Winter simulation
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations
Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations
Distributed Simulation of Multi-Agent Hybrid Systems
ISORC '02 Proceedings of the Fifth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
Simulation and control of hybrid systems with applications to mobile robotics
Simulation and control of hybrid systems with applications to mobile robotics
Proceedings of the 6th international conference on Hybrid systems: computation and control
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
A state event detection algorithm for numerically simulating hybrid systems with model singularities
ACM Transactions on Modeling and Computer Simulation (TOMACS)
On the stability and performance of discrete event methods for simulating continuous systems
Journal of Computational Physics
Monte-carlo techniques for falsification of temporal properties of non-linear hybrid systems
Proceedings of the 13th ACM international conference on Hybrid systems: computation and control
A survey of numerical methods for IVPs of ODEs with discontinuous right-hand side
Journal of Computational and Applied Mathematics
Probabilistic Temporal Logic Falsification of Cyber-Physical Systems
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on Probabilistic Embedded Computing
Original article: Rosenbrock-type methods applied to discontinuous differential systems
Mathematics and Computers in Simulation
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A simulation algorithm is presented for multi-agent hybrid systems---systems consisting of many sets of nonsmooth differential equations---such as systems involving multiple rigid bodies, vehicles, or airplanes. The differential equations are partitioned into coupled subsystems, called "agents"; and the conditions which trigger the discontinuities in the derivatives, called "events", may depend on the global state vector. Such systems normally require significant computational resources to simulate because a global time step is used to ensure the discontinuity is properly handled. When the number of systems is large, forcing all system to be simulated at the same rate creates a computational bottleneck, dramatically decreasing efficiency. By using a control systems approach for selecting integration step sizes, we avoid using a global time step. Each subsystem can be simulated asynchronously when the state is away from the event. As the state approaches the event, the simulation is able to synchronize each of the local time clocks in such a way that the discontinuities are properly handled without the need for "roll back". The algorithm's operation and utility is demonstrated on an example problem inspired by autonomous highway vehicles. Using a combination of stochastic modelling and numerical experiments we show that the algorithm requires significantly less computation time when compared with traditional simulation techniques for such problems, and scales more favorably with problem size.