Hybrid diagrams: A deductive-algorithmic approach to hybrid system verification

1997 ◽  
pp. 153-164 ◽  
Author(s):  
Luca de Alfaro ◽  
Arjun Kapur ◽  
Zohar Manna
Keyword(s):  
Hybrid System ◽  
Algorithmic Approach ◽  
System Verification

scholarly journals Progress on Powertrain Verification Challenge with C2E2

10.29007/1kq2 ◽  
2018 ◽  
Author(s):  
Chuchu Fan ◽  
Parasara Sridhar Duggirala ◽  
Sayan Mitra ◽  
Mahesh Viswanathan
Keyword(s):  
Rate Of Convergence ◽  
Control Systems ◽  
Hybrid System ◽  
State Machines ◽  
Powertrain Control ◽  
Verification Tool ◽  
Discrepancy Rate ◽  
System Verification ◽  
Made In

In this paper, we present the progress we have made in verifying the benchmark powertrain control systems introduced in the last ARCH workshop. We implemented the algorithm for computing local discrepancy (rate of convergence or divergence of trajectories) reported in the hybrid system verification tool C2E2. We created Stateflow translations of the original models to aid the processing using C2E2 tool. We also had to encode the different driver behaviors in the form of state machines. With these customizations, we have been successful in verifying one of the easier (but still challenging) benchmarks from the powertrain suite. In this paper, we present some of the engineering challenges and describe the artifacts we created in the process.

ACTL strong negation and its application to hybrid system verification

2004 ◽  
Vol 37 (18) ◽  
pp. 321-326
Author(s):  
Alongkrit Chutinan ◽  
Zhi Han ◽  
Bruce H. Krogh
Keyword(s):  
Hybrid System ◽  
Strong Negation ◽  
System Verification

scholarly journals PARAMETRIC VERIFICATION AND TEST COVERAGE FOR HYBRID AUTOMATA USING THE INVERSE METHOD

2013 ◽  
Vol 24 (02) ◽  
pp. 233-249 ◽  
Author(s):  
LAURENT FRIBOURG ◽  
ULRICH KÜHNE
Keyword(s):  
Hybrid Systems ◽  
Hybrid System ◽  
Inverse Method ◽  
Timed Automata ◽  
Test Coverage ◽  
Hybrid Automata ◽  
System Verification

Hybrid systems combine continuous and discrete behavior. Hybrid Automata are a powerful formalism for the modeling and verification of such systems. A common problem in hybrid system verification is the good parameters problem, which consists in identifying a set of parameter valuations which guarantee a certain behavior of a system. Recently, a method has been presented for attacking this problem for Timed Automata. In this paper, we show the extension of this methodology for hybrid automata with linear and affine dynamics. The method is demonstrated with a hybrid system benchmark from the literature.

scholarly journals $$\mathsf {SceneChecker}$$: Boosting Scenario Verification Using Symmetry Abstractions

2021 ◽  
pp. 580-594
Author(s):  
Hussein Sibai ◽  
Yangge Li ◽  
Sayan Mitra
Keyword(s):  
Neural Network ◽  
Nonlinear Dynamics ◽  
Hybrid System ◽  
Analysis Tool ◽  
Aerial Vehicles ◽  
Verification Problem ◽  
Verification Time ◽  
System Verification ◽  
Refinement Algorithm ◽  
Neural Network Controllers

AbstractWe present $$\mathsf {SceneChecker}$$ SceneChecker , a tool for verifying scenarios involving vehicles executing complex plans in large cluttered workspaces. $$\mathsf {SceneChecker}$$ SceneChecker converts the scenario verification problem to a standard hybrid system verification problem, and solves it effectively by exploiting structural properties in the plan and the vehicle dynamics. $$\mathsf {SceneChecker}$$ SceneChecker uses symmetry abstractions, a novel refinement algorithm, and importantly, is built to boost the performance of any existing reachability analysis tool as a plug-in subroutine. We evaluated $$\mathsf {SceneChecker}$$ SceneChecker on several scenarios involving ground and aerial vehicles with nonlinear dynamics and neural network controllers, employing different kinds of symmetries, using different reachability subroutines, and following plans with hundreds of waypoints in complex workspaces. Compared to two leading tools, DryVR and Flow*, $$\mathsf {SceneChecker}$$ SceneChecker shows 14$$\times $$ × average speedup in verification time, even while using those very tools as reachability subroutines.

HYBRID SYSTEM VERIFICATION IS NOT A SINECURE — THE ELECTRONIC THROTTLE CONTROL CASE STUDY

2006 ◽  
Vol 17 (04) ◽  
pp. 885-901 ◽  
Author(s):  
ANSGAR FEHNKER ◽  
BRUCE KROGH
Keyword(s):  
Model Checking ◽  
Hybrid System ◽  
Formal Model ◽  
Control Case ◽  
Automotive Control ◽  
Electronic Throttle ◽  
System Verification ◽  
Automated Process ◽  
Informal Description

Though model checking itself is a fully automated process, verifying correctness of a hybrid system design using model checking is not. This paper describes the necessary steps, and choices to be made, to go from an informal description of the problem to the final verification result for a formal model and requirement. It uses an automotive control system for illustration.

Extending model checkers for hybrid system verification: the case study ofSPIN

2013 ◽  
Vol 24 (6) ◽  
pp. 438-471 ◽  
Author(s):  
María-del-Mar Gallardo ◽  
Laura Panizo
Keyword(s):  
Hybrid System ◽  
System Verification
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