A New Time-Varying Feedback RISE Control of PKMs: Theory and Application

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Flexible and adaptive tracked robots show the capacity to navigate in unstructured terrain, with a passive adaption of the track or a morphology change for terrain adaptation. Extending the concept to one in which the morphology can be actively changed has ...

Integrating proprioceptive capabilities in balloon‐type robots holds immense potential to enable safe interactions between humans and machines. These robots, made of elastic or hyperelastic materials, undergo substantial deformations when subjected to chan ...

This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where collaboration and division of labor enhance survival of the whole colony, and are thus considered “superorganisms”. Historically, studying behaviors involving ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

Frequency Response Function (FRF)-based control synthesis methods for Linear Time-Invariant (LTI) systems have been widely used in control theory and industry. Recently, there has been renewed interest in these methods, employing numerical optimization too ...

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded in order to handl ...

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outpu ...

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which provide reduced ...

We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...

This paper proposes a Control by Interconnection design, for a class of constrained Port-Hamiltonian systems, which is based on an associated Model Predictive Control optimization problem. This associated optimization problem allows to consider both state ...

This thesis addresses theoretical and practical aspects of identification and subsequent control of self-exciting point processes. The main contributions correspond to four separate scientific papers. In the first paper, we address the challenge of robust ...

Today, automatic control is integrated into a wide spectrum of real-world systems such as electrical grids and transportation networks. Many of these systems comprise numerous interconnected agents, perform safety-critical operations, or generate large amo ...

This paper proposes a Linear Parameter-Varying loop-shaping controller for a power-synchronized grid-following inverter (PSGFLI). This control strategy regulates the inverter output active and reactive power at the terminal instead of the point of connecti ...

Recently developed Concentric Tube Continuum Robots (CTCRs) are widely exploited in, for example in minimally invasive surgeries which involve navigating inside narrow body cavities close to sensitive regions. These CTCRs can be controlled by extending and ...

This thesis presents an efficient and extensible numerical software framework for real-time model-based control. We are motivated by complex and challenging mechatronic applications spanning from flight control of fixed-wing aircraft and thrust vector cont ...

Background Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. Met ...

The paper aims at minimizing DC voltage oscillations in offshore multiterminal high-voltage direct current (HVDC) grids based on modular multilevel converters (MMCs). The DC voltage stability is a crucial factor in multiterminal HVDC networks since it is a ...

A New Time-Varying Feedback RISE Control of PKMs: Theory and Application

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FLEXIV: Adaptive Locomotion via Morphological Changes in a Flexible Track Vehicle

Low‐Strain Flexible Ink‐Based Sensors Enable Hyperelastic Inflation Perception Via Geometric Patterning for Balloon‐Type Robots

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Biohybrid Superorganisms—On the Design of a Robotic System for Thermal Interactions With Honeybee Colonies

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Achieving Optimal Performance With Data-Driven Frequency-Based Control Synthesis Methods

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Data-driven fixed-structure frequency-based H2 and H∞ controller design

Learning and optimization of anticipatory feedback controllers for robot manipulation

Data-driven Methods for Control: from Linear to Lifting

Homothetic Tube Model Predictive Control With Multi-Step Predictors

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

A combined Control by Interconnection—Model Predictive Control design for constrained Port-Hamiltonian systems

Self-Exciting Point Processes: Identification and Control

Data-driven and Safe Networked Control with Applications to Microgrids

Linear Parameter-Varying Control of A Power-Synchronized Grid-Following Inverter

Navigation of Concentric Tube Continuum Robots using Optimal Control

Real-Time Nonlinear Model Predictive Control for Fast Mechatronic Systems

Review of control strategies for lower-limb exoskeletons to assist gait

Optimal Linear Controller for Minimizing DC Voltage Oscillations in MMC-Based Offshore Multiterminal HVDC Grids