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This paper considers the problem of output feedback control for non-square multi-input multi-output systems with arbitrary relative degree. The proposed controller, based on the L1 adaptive control architecture, is designed using the right…

Optimization and Control · Mathematics 2024-12-20 Hanmin Lee , Venanzio Cichella , Naira Hovakimyan

This paper presents a constraint-enforcing control framework for a class of discrete-time strict-feedback nonlinear systems. The objective is to guarantee closed-loop stability while ensuring forward invariance of a prescribed safe set…

Optimization and Control · Mathematics 2026-04-29 Jhon Manuel Portella Delgado , Ankit Goel

We propose a general model-free strategy for feedback control design of turbulent flows. This strategy called 'machine learning control' (MLC) is capable of exploiting nonlinear mechanisms in a systematic unsupervised manner. It relies on…

We study feedback control of coupled nonlinear stochastic oscillators in a force field. We first consider the problem of asymptotically driving the system to a desired {\em steady state} corresponding to reduced thermal noise. Among the…

Mathematical Physics · Physics 2015-07-02 Yongxin Chen , Tryphon Georgiou , Michele Pavon

In this paper, disturbance reconstruction and robust trajectory tracking control of biped robots with hybrid dynamics in the port-Hamiltonian form is investigated. A new type of Hamiltonian function is introduced, which ensures the…

Robotics · Computer Science 2021-10-14 Yousef Farid , Fabio Ruggiero

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

This paper presents a nonlinear control design for highly underactuated balance robots, which possess more numbers of unactuated degree-of-freedom (DOF) than actuated ones. To address the challenge of simultaneously trajectory tracking of…

Robotics · Computer Science 2023-10-03 Feng Han , Jingang Yi

We address modeling and control of a gate access automation system. A model of the mechatronic system is derived and identified. Then an approximate explicit feedback linearization scheme is proposed, which ensures almost linear response…

Systems and Control · Electrical Eng. & Systems 2021-09-29 Daniel Cunico , Angelo Cenedese , Luca Zaccarian , Mauro Borgo

Purpose: This paper presents an impedance control method with mixed $H_2/H_\infty$ synthesis and relaxed passivity for a cable-driven series elastic actuator to be applied for physical human-robot interaction. Design/methodology/approach:…

Robotics · Computer Science 2019-03-26 Ningbo Yu , Wulin Zou

In this paper, we present a controller that combines motion generation and control in one loop, to endow robots with reactivity and safety. In particular, we propose a control approach that enables to follow the motion plan of a first order…

Robotics · Computer Science 2023-07-20 Youssef Michel , Matteo Saveriano , Dongheui Lee

Direct design of a robot's rendered dynamics, such as in impedance control, is now a well-established control mode in uncertain environments. When the physical interaction port variables are not measured directly, dynamic and kinematic…

Robotics · Computer Science 2024-12-20 Kevin Haninger , Masayoshi Tomizuka

The ability of animals to interact with complex dynamics is unmatched in robots. Especially important to the interaction performances is the online adaptation of body dynamics, which can be modeled as an impedance behaviour. However, the…

Shared Control methods often use impedance control to track target poses in a robotic manipulator. The guidance behavior of such controllers is shaped by the used stiffness gains, which can be varying over time to achieve an adaptive…

This paper proposes a new framework and several results to quantify the performance of data-driven state-feedback controllers for linear systems against targeted perturbations of the training data. We focus on the case where subsets of the…

Systems and Control · Electrical Eng. & Systems 2019-12-24 Rajasekhar Anguluri , Abed AlRahman Al Makdah , Vaibhav Katewa , Fabio Pasqualetti

In commercial robotic systems, it is common to encounter a closed inner-loop torque controller that is not user-modifiable. However, the outer-loop controller, which sends kinematic commands such as position or velocity for the inner-loop…

Robotics · Computer Science 2025-12-09 Fan Zhang , Jinfeng Chen , Joseph J. B. Mvogo Ahanda , Hanz Richter , Ge Lv , Bin Hu , Qin Lin

Passivity is necessary for robots to fluidly collaborate and interact with humans physically. Nevertheless, due to the unconstrained nature of passivity-based impedance control laws, the robot is vulnerable to infeasible and unsafe…

Robotics · Computer Science 2024-03-18 Zhiquan Zhang , Tianyu Li , Nadia Figueroa

This paper introduces a novel method for robust output-feedback model predictive control (MPC) for a class of nonlinear discrete-time systems. We propose a novel interval-valued predictor which, given an initial estimate of the state,…

Systems and Control · Electrical Eng. & Systems 2025-04-15 Scott Brown , Mohammad Khajenejad , Aamodh Suresh , Sonia Martinez

An impedance-based control scheme is introduced for cooperative manipulators grasping a rigid load. The position and orientation of the load are to be maintained close to a desired trajectory, trading off tracking accuracy by low energy…

Optimization and Control · Mathematics 2021-06-15 Amin Ghorbanpour , Hanz Richter

Stable aerial manipulation during dynamic tasks such as object catching, perching, or contact with rigid surfaces necessarily requires compliant behavior, which is often achieved via impedance control. Successful manipulation depends on how…

Systems and Control · Electrical Eng. & Systems 2025-04-04 Amitabh Sharma , Saksham Gupta , Shivansh Pratap Singh , Rishabh Dev Yadav , Hongyu Song , Wei Pan , Spandan Roy , Simone Baldi

We develop data-driven reinforcement learning (RL) control designs for input-affine nonlinear systems. We use Carleman linearization to express the state-space representation of the nonlinear dynamical model in the Carleman space, and…

Systems and Control · Electrical Eng. & Systems 2024-08-09 Jishnudeep Kar , He Bai , Aranya Chakrabortty