arXiv subjects

Maryam Sharifi

Publications and source records attributed to Maryam Sharifi.

9 recordsLinked to original sources

arXiv2026

Distributed model predictive control via finite-step control Lyapunov functions

As opposed to classical converse Lyapunov theorems, finite-step converse results are constructive and offer a different starting point: for sufficiently large finite step ahead, say $M$, in an explicit sense, any scaled norm can serve as a converse finite-step Lyapunov function. As for interconnected discrete-time systems, similar lines of argument lead to ``non-conservative'' small-gain conditions. Motivated by this viewpoint, this paper develops a distributed model predictive control framework for constrained interconnected nonlinear discrete-time systems. Each subsystem solves one local optimization problem at each system time step instant by setting the local stage function in form of a local control finite-step like Lyapunov function, using time-aligned neighbor predictions, optimized state-constraint tightening radii, and a finite-step small-gain terminal inequality. Since received neighbor predictions need not equal the trajectories generated by future receding-horizon optimizations, the nominal converse certificates do not alone ensure recursive feasibility or stability. We therefore develop shift-compatible constraint margins, a local one-step terminal feasibility test for networks that are affine in control, and an analytical bound for the prediction and reoptimization mismatch. The resulting analysis gives recursive feasibility, constraint satisfaction, and a practical $M$-step Lyapunov estimate, with asymptotic convergence when the prediction and reoptimization mismatch bound tends to zero. For constrained linear networks, the conditions reduce to finite-dimensional matrix, QP, and SOCP tests. The framework is specialized to current sharing and terminal bus voltage safety under DC/DC power converters' operational constraints in a two-DGU DC microgrid evaluated on a small laboratory-scale prototype.

math.OC↗

arXiv2026

A Distributed Framework for Data-Driven Safe Coordination in Leader-Follower Networks

This paper addresses connectivity preservation in leader-follower multi-agent systems with unknown control-affine dynamics and local state information. We introduce the distributed data-driven zeroing control barrier function (3D-ZCBF) framework, which ensures the controlled invariance of safety sets by identifying derivative bounds from input-state data without requiring explicit models of high-dimensional agent dynamics. In this work, we derive the explicit, decoupled safety conditions necessary to maintain connectivity for leader-leader, and follower-follower pairings. These individual constraints, along with the leader-follower conditions, are aggregated into explicit system-wide conditions that formally guarantee the preservation of the entire communication network. Furthermore, we provide a quantitative analysis demonstrating how the size of the collected data set and the accuracy of the learned Jacobian bounds impact the feasibility of the safety certificates. The proposed conditions are implemented via a projection-based controller, and simulations confirm that these explicit 3D-ZCBF requirements effectively maintain system-level connectivity using only local, two-hop information.

eess.SY↗

arXiv2024

Safe Force/Position Tracking Control via Control Barrier Functions for Floating Base Mobile Manipulator Systems

This paper introduces a safe force/position tracking control strategy designed for Free-Floating Mobile Manipulator Systems (MMSs) engaging in compliant contact with planar surfaces. The strategy uniquely integrates the Control Barrier Function (CBF) to manage operational limitations and safety concerns. It effectively addresses safety-critical aspects in the kinematic as well as dynamic level, such as manipulator joint limits, system velocity constraints, and inherent system dynamic uncertainties. The proposed strategy remains robust to the uncertainties of the MMS dynamic model, external disturbances, or variations in the contact stiffness model. The proposed control method has low computational demand ensures easy implementation on onboard computing systems, endorsing real-time operations. Simulation results verify the strategy's efficacy, reflecting enhanced system performance and safety.

cs.RO↗

arXiv2022

Enhancing Data-Driven Reachability Analysis using Temporal Logic Side Information

This paper presents algorithms for performing data-driven reachability analysis under temporal logic side information. In certain scenarios, the data-driven reachable sets of a robot can be prohibitively conservative due to the inherent noise in the robot's historical measurement data. In the same scenarios, we often have side information about the robot's expected motion (e.g., limits on how much a robot can move in a one-time step) that could be useful for further specifying the reachability analysis. In this work, we show that if we can model this side information using a signal temporal logic (STL) fragment, we can constrain the data-driven reachability analysis and safely limit the conservatism of the computed reachable sets. Moreover, we provide formal guarantees that, even after incorporating side information, the computed reachable sets still properly over-approximate the robot's future states. Lastly, we empirically validate the practicality of the over-approximation by computing constrained, data-driven reachable sets for the Small-Vehicles-for-Autonomy (SVEA) hardware platform in two driving scenarios.

cs.RO↗

arXiv2021

Higher Order Convergent Control Barrier Functions for Leader-Follower Multi-Agent Systems under STL Tasks

This paper presents control strategies based on time-varying convergent higher order control barrier functions for a class of leader-follower multi-agent systems under signal temporal logic (STL) tasks. Each agent is assigned a local STL task which may be dependent on the behavior of agents involved in other tasks. The leader has knowledge on the associated tasks and controls the performance of the subgroup involved agents. Robust solutions for the task satisfaction, based on the leader's accessibility to the follower agents' states are suggested. Our approach finds solutions to guarantee the satisfaction of STL tasks independent of the agents' initial conditions.

eess.SY↗

arXiv2021

Compositional Construction of Abstractions for Infinite Networks of Switched Systems

We construct compositional continuous approximations for an interconnection of infinitely many discrete-time switched systems. An approximation (known as abstraction) is itself a continuous-space system, which can be used as a replacement of the original (known as concrete) system in a controller design process. Having synthesized a controller for the abstract system, the controller is refined to a more detailed controller for the concrete system. To quantify the mismatch between the output trajectory of the approximation and of that the original system, we use the notion of so-called simulation functions. In particular, each subsystem in the concrete network and its corresponding one in the abstract network is related through a local simulation function. We show that if the local simulation functions satisfy a certain small-gain type condition developed for a network of infinitely many subsystems, then the aggregation of the individual simulation functions provides an overall simulation function between the overall abstraction and the concrete network. For a network of linear switched systems, we systematically construct local abstractions and local simulation functions, where the required conditions are expressed in terms of linear matrix inequalities and can be efficiently computed. We illustrate the effectiveness of our approach through an application to frequency control in a power gird with a switched (i.e. time-varying) topology.

eess.SY↗

arXiv2021

Fixed-Time Convergent Control Barrier Functions for Coupled Multi-Agent Systems Under STL Tasks

This paper presents a control strategy based on a new notion of time-varying fixed-time convergent control barrier functions (TFCBFs) for a class of coupled multi-agent systems under signal temporal logic (STL) tasks. In this framework, each agent is assigned a local STL task regradless of the tasks of other agents. Each task may be dependent on the behavior of other agents which may cause conflicts on the satisfaction of all tasks. Our approach finds a robust solution to guarantee the fixed-time satisfaction of STL tasks in a least violating way and independent of the agents' initial condition in the presence of undesired violation effects of the neighbor agents. Particularly, the robust performance of the task satisfactions can be adjusted in a user-specified way.

eess.SY↗

arXiv2021

Robust Finite-Time Consensus Subject to Unknown Communication Time Delays Based on Delay-Dependent Criteria

In this paper, robust finite-time consensus of a group of nonlinear multi-agent systems in the presence of communication time delays is considered. In particular, appropriate delay-dependent strategies which are less conservative are suggested. Sufficient conditions for finite-time consensus in the presence of deterministic and stochastic disturbances are presented. The communication delays don't need to be time invariant, uniform, symmetric, or even known. The only required condition is that all delays satisfy a known upper bound. The consensus algorithm is appropriate for agents with partial access to neighbor agents' signals. The Lyapunov-Razumikhin theorem for finite-time convergence is used to prove the results. Simulation results on a group of mobile robot manipulators as the agents of the system are presented.

eess.SY↗

arXiv2021

Compositional Construction of Abstractions for Infinite Networks of Discrete-Time Switched Systems

In this paper, we develop a compositional scheme for the construction of continuous approximations for interconnections of infinitely many discrete-time switched systems. An approximation (also known as abstraction) is itself a continuous-space system, which can be used as a replacement of the original (also known as concrete) system in a controller design process. Having designed a controller for the abstract system, it is refined to a more detailed one for the concrete system. We use the notion of so-called simulation functions to quantify the mismatch between the original system and its approximation. In particular, each subsystem in the concrete network and its corresponding one in the abstract network are related through a notion of local simulation functions. We show that if the local simulation functions satisfy certain small-gain type conditions developed for a network containing infinitely many subsystems, then the aggregation of the individual simulation functions provides an overall simulation function quantifying the error between the overall abstraction network and the concrete one. In addition, we show that our methodology results in a scale-free compositional approach for any finite-but-arbitrarily large networks obtained from truncation of an infinite network. We provide a systematic approach to construct local abstractions and simulation functions for networks of linear switched systems. The required conditions are expressed in terms of linear matrix inequalities that can be efficiently computed. We illustrate the effectiveness of our approach through an application to AC islanded microgirds.

eess.SY↗