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Safe Control Synthesis with Uncertain Dynamics and Constraints [article]

Kehan Long, Vikas Dhiman, Melvin Leok, Jorge Cortés, Nikolay Atanasov
2022 arXiv   pre-print
We formulate novel probabilistic and robust (worst-case) control Lyapunov function (CLF) and control barrier function (CBF) constraints that take into account the effect of uncertainty in either case.  ...  We show that either the probabilistic or the robust (worst-case) formulation leads to a second-order cone program (SOCP), which enables efficient safe and stable control synthesis.  ...  When worst-case error bounds on the system dynamics, barrier function and its gradient are given, we formulate a robust safe control synthesis problem.  ... 
arXiv:2202.09557v2 fatcat:ckqm2x4vfvcfhlclo4f4ulkhhu

Robust Estimator-Based Safety Verification: A Vector Norm Approach [article]

Binghan He, Gray C. Thomas, Luis Sentis
2019 arXiv   pre-print
The barrier function controller combination is then used to construct a safety backup controller. And we demonstrate the system in a simulation of a 1 degree-of-freedom human-exoskeleton interaction.  ...  Barrier function and estimator synthesis is proposed as two convex sub-problems, exploiting linear matrix inequalities.  ...  EXAMPLE To illustrate robust barrier function estimation and hybrid safety control, we introduce a simplified human-exoskeleton interaction model.  ... 
arXiv:1910.02317v1 fatcat:g54fyvbv4feg3mxicaelj6q46i

Robust Safe Control Synthesis with Disturbance Observer-Based Control Barrier Functions [article]

Ersin Daş, Richard M. Murray
2022 arXiv   pre-print
This paper presents a robust stabilizing safety-critical controller synthesis framework with control Lyapunov functions (CLFs) and control barrier functions (CBFs) in the presence of disturbance.  ...  The estimated unknown input and associated error bound are used to ensure robust safety and exponential stability by formulating a CLF-CBF quadratic program.  ...  Safety and Control Barrier Functions Control barrier functions are a useful tool for rendering the set C ⊂ R n as forward invariant throughout its state-space.  ... 
arXiv:2201.05758v3 fatcat:numgt5mkkffbbp2glidcydmbcm

Learning Barrier Functions with Memory for Robust Safe Navigation [article]

Kehan Long, Cheng Qian, Jorge Cortés, Nikolay Atanasov
2021 arXiv   pre-print
Control barrier functions are widely used to enforce safety properties in robot motion planning and control.  ...  This allows us to formulate a novel robust control barrier safety constraint which takes into account the error in the estimated distance fields and its gradient.  ...  Safe Control with Estimated Barrier Functions A useful tool to ensure that the robot state remains in the safe set S throughout its evolution is the notion of control barrier function (CBF).  ... 
arXiv:2011.01899v2 fatcat:bnc5ea7wcndqlcdv5xmrvayca4

Measurement-Robust Control Barrier Functions: Certainty in Safety with Uncertainty in State [article]

Ryan K. Cosner, Andrew W. Singletary, Andrew J. Taylor, Tamas G. Molnar, Katherine L. Bouman, Aaron D. Ames
2021 arXiv   pre-print
the synthesis of Measurement-Robust Control Barrier Functions (MR-CBFs).  ...  We develop this framework by leveraging Control Barrier Functions (CBFs) and unifying the method of Backup Sets for synthesizing control invariant sets with robustness requirements -- the end result is  ...  In [14] safety and robustness were enforced by Measurement-Robust Control Barrier Functions (MR-CBFs).  ... 
arXiv:2104.14030v1 fatcat:kdi472hzgvdx3fex5ifw523shi

Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions [article]

Charles Dawson, Zengyi Qin, Sicun Gao, Chuchu Fan
2021 arXiv   pre-print
We take inspiration from robust convex optimization and Lyapunov theory to define robust control Lyapunov barrier functions that generalize despite model uncertainty.  ...  Safety and stability are common requirements for robotic control systems; however, designing safe, stable controllers remains difficult for nonlinear and uncertain models.  ...  article solely reflects the opinions and conclusions of its authors and not any NASA entity, DSTA Singapore, or the Singapore Government.  ... 
arXiv:2109.06697v2 fatcat:3nfpe2ijqffmrfsptm233lhlhi

Control Barrier Functions and Input-to-State Safety with Application to Automated Vehicles [article]

Anil Alan and Andrew J. Taylor and Chaozhe R. He and Aaron D. Ames and Gabor Orosz
2022 arXiv   pre-print
In this work we present a constructive approach for safety-critical control synthesis via Control Barrier Functions (CBF).  ...  We characterize these disturbances and using ISSf, produce a robust controller that achieves safety without conceding performance.  ...  II, we now define Input-to-State Safe Control Barrier Functions as a tool for robust safety-critical control synthesis: Definition 4 (Input-to-State Safe Control Barrier Function (ISSf-CBF)).  ... 
arXiv:2206.03568v1 fatcat:pu7oxiseafa3lpo3lpeny7znku

Robust Control Barrier and Control Lyapunov Functions with Fixed-Time Convergence Guarantees [article]

Kunal Garg, Dimitra Panagou
2021 arXiv   pre-print
We use robust variants of control barrier functions (CBF) and fixed-time control Lyapunov functions (FxT-CLF) to incorporate a class of additive disturbances in the system dynamics, and state-estimation  ...  To solve the underlying constrained control problem, we formulate a quadratic program and use the proposed robust CBF-FxT-CLF conditions to compute the control input.  ...  We use robust variants of control barrier functions (CBF) and control Lyapunov functions (CLF) to incorporate a class of additive disturbances in the system dynamics, and sensing errors in the system states  ... 
arXiv:2004.01054v3 fatcat:jsiyc44tzvhejem5skwa4q6xni

Safe Controller Synthesis with Tunable Input-to-State Safe Control Barrier Functions [article]

Anil Alan, Andrew J. Taylor, Chaozhe R. He, Gábor Orosz, Aaron D. Ames
2021 arXiv   pre-print
This is achieved by formulating the concept of tunable input to state safe control barrier functions (TISSf-CBFs) which guarantee safety for disturbances that vary with state and, therefore, provide less  ...  To bring complex systems into real world environments in a safe manner, they will have to be robust to uncertainties - both in the environment and the system.  ...  Examples of the use of control barrier functions include adaptive and connected cruise control [2] , [9] and lane keeping [10] problems.  ... 
arXiv:2103.08041v2 fatcat:xnwo44ik2fg3tivul2qtgoqwpe

Controller Synthesis for Safety of Physically-Viable Data-Driven Models [article]

Mohamadreza Ahmadi, Arie Israel, Ufuk Topcu
2018 arXiv   pre-print
We consider the problem of designing finite-horizon safe controllers for a dynamical system for which no explicit analytical model exists and limited data only along a single trajectory of the system are  ...  Given samples of the states and inputs of the system, and additional side information in terms of regularity of the evolution of the states and conservation laws, we synthesize a controller such that the  ...  It was also shown that this control barrier function structure allows the safe controller synthesis problem to be solved by a set of quadratic programs, satisfies robustness properties such as input-to-state  ... 
arXiv:1801.04072v1 fatcat:fs4d54uecne4vbyvoixfwam4yy

Gaussian Control Barrier Functions : A Non-Parametric Paradigm to Safety [article]

Mouhyemen Khan, Tatsuya Ibuki, Abhijit Chatterjee
2022 arXiv   pre-print
Inspired by the success of control barrier functions (CBFs) in addressing safety, and the rise of data-driven techniques for modeling functions, we propose a non-parametric approach for online synthesis  ...  We validate our approach experimentally on a quadrotor by demonstrating safe control for fixed but arbitrary safe sets and collision avoidance where the safe set is constructed online.  ...  This research was supported by the US National Science Foundation under Grant S&AS:1723997.  ... 
arXiv:2203.15474v2 fatcat:qv47nq3ucvht3htuhaxmnq476e

Data-driven Safety Verification of Stochastic Systems via Barrier Certificates [article]

Ali Salamati, Abolfazl Lavaei, Sadegh Soudjani, Majid Zamani
2021 arXiv   pre-print
We first reformulate the barrier-based safety verification as a robust convex problem (RCP).  ...  The proposed framework is based on a notion of barrier certificates together with data collected from trajectories of unknown systems.  ...  We first formulated a barrier-based safety problem Zamani, M. (2020a). Formal controller synthesis for as a robust convex problem (RCP).  ... 
arXiv:2112.12709v1 fatcat:fq5v6mh2hvhgrhtlwyfwqb7adu

Data-driven verification and synthesis of stochastic systems through barrier certificates [article]

Ali Salamati, Abolfazl Lavaei, Sadegh Soudjani, Majid Zamani
2021 arXiv   pre-print
In this work, we formulate the computation of barrier certificates as a robust convex program (RCP).  ...  This provides a lower bound on the safety probability of the original unknown system together with a controller in the case of synthesis.  ...  The results in [22] uses barrier certificates for the synthesis of controllers against complex requirements expressed as co-safe linear temporal logic formulas.  ... 
arXiv:2111.10330v1 fatcat:inyzusqlfjdylddbrptfybivf4

Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty

Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames
2021 2021 60th IEEE Conference on Decision and Control (CDC)  
This paper develops a data-driven approach to robust control synthesis in the presence of model uncertainty using Control Certificate Functions (CCFs), resulting in a convex optimization based controller  ...  Modern nonlinear control theory seeks to endow systems with properties such as stability and safety, and has been deployed successfully across various domains.  ...  Functions (Artstein, 1983) , Control Barrier Functions (Ames et al., 2014a) , and Control Barrier-Lyapunov Functions (Prajna and Jadbabaie, 2004) .  ... 
doi:10.1109/cdc45484.2021.9683511 fatcat:zo3a67jg65dyxphm4pyaq7f7qy

Input-to-State Safety with Input Delay in Longitudinal Vehicle Control [article]

Tamas G. Molnar, Anil Alan, Adam K. Kiss, Aaron D. Ames, Gabor Orosz
2022 arXiv   pre-print
A controller is proposed based on control barrier function theory and predictor feedback for provably safe, collision-free behavior by taking into account the significant response time of the truck as  ...  Safe longitudinal control is discussed for a connected automated truck traveling behind a preceding connected vehicle.  ...  Furthermore, the safety of delayfree systems with input disturbance have been investigated by robust control barrier functions (Jankovic, 2018b) and using the notion of input-to-state safety (Kolathaya  ... 
arXiv:2205.14567v1 fatcat:kctiku4nancvxcbutlevl5f4dm
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