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This study presents a noise-robust closed-loop control strategy for wake flows employing model predictive control. The proposed control framework involves the autonomous offline selection of hyperparameters, eliminating the need for user…

Fluid Dynamics · Physics 2025-01-20 Luigi Marra , Andrea Meilán-Vila , Stefano Discetti

The field of physical human-robot interaction has dramatically evolved in the last decades. As a result, the robotic system's requirements have become more challenging, including personalized behavior for different tasks and users. Various…

Model mismatch and process noise are two frequently occurring phenomena that can drastically affect the performance of model predictive control (MPC) in practical applications. We propose a principled way to tune the cost function and the…

Systems and Control · Electrical Eng. & Systems 2025-06-24 Riccardo Zuliani , Efe C. Balta , John Lygeros

We present a novel extremum seeking method for affine connection mechanical control systems. The proposed control law involves periodic perturbation signals with sufficiently large amplitudes and frequencies. A suitable averaging analysis…

Optimization and Control · Mathematics 2022-11-30 Raik Suttner

In this paper, we consider the problem of computing robust controlled invariants for discrete-time monotone dynamical systems. We consider different classes of monotone systems depending on whether the sets of states, control inputs and…

Systems and Control · Electrical Eng. & Systems 2023-06-27 Adnane Saoud , Murat Arcak

In this paper, we present a way of enforcing safety and passivity properties of robot teleoperation systems, where a human operator interacts with a dynamical system modeling the robot. The approach does so in a holistic fashion, by…

Robotics · Computer Science 2021-02-18 Gennaro Notomista , Xiaoyi Cai

In this work, we introduce a novel gradient descent-based approach for optimizing control systems, leveraging a new representation of stable closed-loop dynamics as a function of two matrices i.e. the step size or direction matrix and value…

Optimization and Control · Mathematics 2024-09-18 Ramin Esmzad , Hamidreza Modares

This paper addresses the design of robust dynamic output feedback control for highly uncertain systems in which the unknown disturbance might be excited by the derivative of the control input. This context appears in many industrial…

Systems and Control · Computer Science 2016-10-20 Mazen Alamir , Jean Dobrowolski , Amgad tarek Mohammed

In this paper, we consider the tracking control problem for robot manipulators which are affected by constant bounded disturbances. Three control schemes are applied for the problem, which composed of integral action and tracking…

Systems and Control · Electrical Eng. & Systems 2020-08-18 Amir. A. Ghavifekr , Saeed Pezeshki , Arash Arjmandi

This paper introduces a novel Nussbaum function-based PID control for robotic manipulators. The integration of the Nussbaum function into the PID framework provides a solution with a simple structure that effectively tackles the challenge…

Robotics · Computer Science 2024-03-05 Hamed Rahimi Nohooji , Holger Voos

This paper addresses the problem of robust and optimal control for the class of nonlinear quadratic systems subject to norm-bounded parametric uncertainties and disturbances, and in presence of some amplitude constraints on the control…

Systems and Control · Computer Science 2017-01-12 Merola Alessio , Cosentino Carlo , Colacino Domenico , Amato Francesco

In this letter we propose a holistic analysis merging the techniques of passivity-based control (PBC) and control barrier functions (CBF). We constructively find conditions under which passivity of the closed-loop system is preserved under…

Systems and Control · Electrical Eng. & Systems 2024-02-15 Federico Califano

The problem of suboptimality under bounded disturbances for the adaptive systems based on speed-graadient approach is discussed. A formulation of the estimated optimality of nonlinear nonlinearly parametrized adaptive control systems is…

Optimization and Control · Mathematics 2025-03-27 Alexander Fradkov

Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-based fashion, using a priori or online collected system…

Systems and Control · Electrical Eng. & Systems 2022-09-01 Lukas Beckenbach , Pavel Osinenko , Stefan Streif

Classical discrete-time adaptive controllers provide asymptotic stabilization. While the original adaptive controllers did not handle noise or unmodelled dynamics well, redesigned versions were proven to have some tolerance; however,…

Optimization and Control · Mathematics 2017-11-28 Daniel E. Miller

In this paper we develop novel results on self triggering control of nonlinear systems, subject to perturbations and actuation delays. First, considering an unperturbed nonlinear system with bounded actuation delays, we provide conditions…

Optimization and Control · Mathematics 2011-08-29 M. D. Di Benedetto , S. Di Gennaro , A. D'Innocenzo

An integral extension of state-feedback controllers for linear time-varying plants is proposed, which preserves performance of the nominal controller in the unperturbed case. Similar to time-invariant state feedback with integral action,…

Systems and Control · Electrical Eng. & Systems 2021-12-28 Richard Seeber , Markus Tranninger

This paper investigates the visual servoing problem for robotic systems with uncertain kinematic, dynamic, and camera parameters. We first present the passivity properties associated with the overall kinematics of the system, and then…

Systems and Control · Computer Science 2016-11-17 Hanlei Wang

Robustness guarantees are important properties to be looked for during control design. They ensure stability of closed-loop systems in face of uncertainties, unmodeled effects and bounded disturbances. While the theory on robust stability…

Systems and Control · Electrical Eng. & Systems 2022-10-10 Samuele Zoboli , Daniele Astolfi , Vincent Andrieu

This paper studies integral-type event-triggered model predictive control (MPC) of continuous-time nonlinear systems. An integral-type event-triggered mechanism is proposed by incorporating the integral of errors between the actual and…

Optimization and Control · Mathematics 2020-02-19 Qi Sun , Jicheng Chen , Yang Shi