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Adaptive Prescribed Performance Asymptotic Tracking for High-Order Odd-Rational-Power Nonlinear Systems

Lv, Maolong (author), De Schutter, B.H.K. (author), Cao, Jinde (author), Baldi, S. (author)

Practical tracking results have been reported in the literature for high-order odd-rational-power nonlinear dynamics (a chain of integrators whose power is the ratio of odd integers). Asymptotic tracking remains an open problem for such dynamics. This note gives a positive answer to this problem in the framework of prescribed performance...

journal article 2023

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Abstracting the Traffic of Nonlinear Event-Triggered Control Systems

Delimpaltadakis, Giannis (author), Mazo, M. (author)

Scheduling communication traffic in networks of event-triggered control (ETC) systems is challenging, as their sampling times are unknown, hindering application of ETC in networks. In previous work, finite-state abstractions were created, capturing the sampling behavior of linear time-invariant (LTI) ETC systems with quadratic triggering...

journal article 2023

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Promises of Deep Kernel Learning for Control Synthesis

Reed, Robert (author), Laurenti, L. (author), Lahijanian, Morteza (author)

Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising tool to learn and control complex dynamical systems. In this letter, we develop a scalable abstraction-based framework that enables the use of DKL for control...

journal article 2023

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Distributed Dynamic Coordination Control for Offshore Platform Transportation Under Ocean Environmental Disturbances

Du, Zhe (author), Negenborn, R.R. (author), Reppa, V. (author)

Transportation of a large offshore platform from inland waters to the open sea is a hazardous and challenging mission. With the development of the autonomous surface vessel (ASV), the problem of large floating object transportation has a chance to be solved by applying multiple physical-connected autonomous tugboats. This article proposes a...

journal article 2023

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A Provably Stable Iterative Learning Controller for Continuum Soft Robots

Pierallini, M. (author), Stella, F. (author), Angelini, Franco (author), Deutschmann, Bastian (author), Hughes, Josie (author), Bicchi, Antonio (author), Garabini, Manolo (author), Della Santina, C. (author)

Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system's underactuation, and the need of using a prominent feedforward control action to...

journal article 2023

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Robotic Skill Mutation in Robot-to-Robot Propagation During a Physically Collaborative Sawing Task

Maessen, Rosa E.S. (author), Prendergast, J.M. (author), Peternel, L. (author)

Skill propagation among robots without human involvement can be crucial in quickly spreading new physical skills to many robots. In this respect, it is a good alternative to pure reinforcement learning, which can be time-consuming, or learning from human demonstration, which requires human involvement. In the latter case, there may not be...

journal article 2023

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Chaos and Order in Event-Triggered Control

de Albuquerque Gleizer, G. (author), Mazo, M. (author)

Event-triggered control (ETC) is claimed to provide significant reductions in sampling frequency when compared to periodic sampling, but little is formally known about its generated traffic. This work shows that ETC can exhibit very complex, even chaotic traffic, especially when the triggering condition is aggressive in reducing...

journal article 2023

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Hierarchical Optimal Maneuver Planning and Trajectory Control at On-Ramps With Multiple Mainstream Lanes

Chen, N. (author), van Arem, B. (author), Wang, M. (author)

Connected Automated Vehicles (CAVs) have the potential to improve traffic operations when they cooperatively maneuver in merging sections. State-of-the-art approaches in cooperative merging either build on heuristics solutions or prohibit mainline CAVs to change lane on multilane highways. This paper proposes a hierarchical cooperative...

journal article 2022

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Neural-adaptive constrained flight control for air ground recovery under terrain obstacles

Su, Zikang (author), Wang, X. (author), Wang, Honglun (author)

This article contrives a neural-adaptive constrained controller of the cable towed air-ground recovery system subject to terrain obstacles, unmeasurable cable tensions, trailing vortex, wind gust, and actuator saturation. In air-ground recovery system modeling, the towed vehicle's nominal 6 DOF affine nonlinear dynamics and the cable system's...

journal article 2022

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Stabilizability of Linear Dynamical Systems Using Sparse Control Inputs

Sriram, Chandrasekhar (author), Joseph, G. (author), Murthy, Chandra R. (author)

The stabilizability of a linear dynamical system (LDS) refers to the existence of control inputs that drive the system state to zero. In this article, we analyze both the theoretical and algorithmic aspects of the stabilizability of an LDS using sparse control inputs with potentially time-varying supports. We show that an LDS is stabilizable...

journal article 2022

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Robust Locomotion Exploiting Multiple Balance Strategies: An Observer-Based Cascaded Model Predictive Control Approach

Ding, J. (author), Han, Linyan (author), Ge, Ligang (author), Liu, Yizhang (author), Pang, Jianxin (author)

Robust locomotion is a challenging task for humanoid robots, especially when considering dynamic disturbances. This article proposes a disturbance observer-based cascaded model predictive control (MPC) approach for bipedal locomotion, with the capability of exploiting ankle, stepping, hip and height variation strategies. Specifically, based...

journal article 2022

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Multi-Objective Cooperative Control for a Ship-Towing System in Congested Water Traffic Environments

Du, Zhe (author), Negenborn, R.R. (author), Reppa, V. (author)

This paper proposes a multi-objective cooperative control method for a ship-towing system in congested water traffic environments. The control objectives are to coordinate multiple autonomous tugboats for transporting a ship to: (i) follow the waypoints, (ii) adjust the heading, (iii) track the speed profile, and (iv) resolve collisions. The...

journal article 2022

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Learning to Pick at Non-Zero-Velocity from Interactive Demonstrations

Mészáros, A. (author), Franzese, G. (author), Kober, J. (author)

This work investigates how the intricate task of a continuous pick & place (P&P) motion may be learned from humans based on demonstrations and corrections. Due to the complexity of the task, these demonstrations are often slow and even slightly flawed, particularly at moments when multiple aspects (i.e., end-effector movement,...

journal article 2022

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Learning Tracking Control for Cyber-Physical Systems

Wu, C. (author), Pan, W. (author), Sun, Guanghui (author), Liu, Jianxing (author), Wu, Ligang (author)

This paper investigates the problem of optimal tracking control for cyber-physical systems (CPS) when the cyber realm is attacked by denial-of-service (DoS) attacks which can prevent the control signal transmitting to the actuator. Attention is focused on how to design the optimal tracking control scheme without using the system dynamics and...

journal article 2021

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Model-Reference Reinforcement Learning for Collision-Free Tracking Control of Autonomous Surface Vehicles

Zhang, Q. (author), Pan, W. (author), Reppa, V. (author)

This paper presents a novel model-reference reinforcement learning algorithm for the intelligent tracking control of uncertain autonomous surface vehicles with collision avoidance. The proposed control algorithm combines a conventional control method with reinforcement learning to enhance control accuracy and intelligence. In the proposed...

journal article 2021

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Actuating Eigenmanifolds of Conservative Mechanical Systems Via Bounded or Impulsive Control Actions

Della Santina, C. (author), Calzolari, Davide (author), Giordano, Alessandro Massimo (author), Albu-Schaffer, Alin (author)

Eigenmanifolds are two-dimensional submanifolds of the state space, which generalize linear eigenspaces to nonlinear mechanical systems. Initializing a robot on an Eigenmanifold (or driving it there by control) yields hyper-efficient and regular oscillatory behaviors, called modal oscillations. This letter investigates the possibility of...

journal article 2021

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Exciting efficient oscillations in nonlinear mechanical systems through Eigenmanifold stabilization

Della Santina, C. (author), Albu-Schaeffer, Alin (author)

Nonlinear modes are a well investigated concept in dynamical systems theory, extending the celebrated modal analysis of linear mechanical systems to nonlinear ones. This letter moves a first step in the direction of combining control theory and nonlinear modal analysis towards the implementation of hyper-efficient oscillatory behaviors in...

journal article 2021

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Effects of Linear Perspective on Human Use of Preview in Manual Control

van der El, Kasper (author), Pool, D.M. (author), van Paassen, M.M. (author), Mulder, Max (author)

Due to linear perspective, the visual stimulus provided by a previewed reference trajectory reduces with increasing distance ahead. This paper investigates the effects of linear perspective on human use of preview in manual control tasks. Results of a human-in-the-loop tracking experiment are presented, where the linear perspective&#x0027...

journal article 2018

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Haptic guidance on demand: A grip-force based scheduling of guidance forces

Smisek, J. (author), Mugge, W. (author), Smeets, Jeroen B J (author), van Paassen, M.M. (author), Schiele, A. (author)

In haptic shared control systems (HSC), a fixed strength of guidance force equates to a fixed level of control authority, which can be insufficient for complex tasks. An adaptable control authority based on operator input can allow the HSC system to better assist the operator under varied conditions. In this paper, we experimentally...

journal article 2018

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Effects of Preview Time in Manual Tracking Tasks

van der El, Kasper (author), Padmos, S. (author), Pool, D.M. (author), van Paassen, M.M. (author), Mulder, Max (author)

In manual control tasks, preview of the target trajectory ahead is often limited by poor lighting, objects, or display edges. This paper investigates the effects of limited preview, or preview time, in manual tracking tasks with single- and double-integrator controlled element dynamics. A quasi-linear human controller model is used to predict...

journal article 2018