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This paper presents an indirect data-driven controller synthesis for nonlinear systems, leveraging Structured State-space Models (SSMs) as surrogate models. SSMs have emerged as a compelling alternative in modelling time-series data and dynamical systems. They can capture long-term dependencies while maintaining linear computational complexity with respect to the sequence length, in comparison to the quadratic complexity of Transformer-based architectures. The contributions of this work are threefold. We pr

Modern learning methods have proven promising for modeling complex physical phenomena and for designing controllers capable of executing intricate tasks, owing to their remarkable flexibility. However, they can be unreliable in deployment when faced with new scenarios not represented in their training data. This thesis develops data-driven frameworks that retain the expressiveness and scalability of state-of-the-art machine learning while providing formal reliability certificates along two complementary axe

In converter-based grids (CBGs) without support from the main grid or synchronous generators, grid-forming converters (GFMs) are responsible for sustaining frequency and voltage stability. However, disturbances or load variations frequently lead to frequency and voltage deviations, and the operating point (OP) of GFM may not align with the desired stable state. Under severe faults, current-limiting actions may be triggered, potentially leading to instability. This paper proposes a Port-Hamiltonian (PH) fram

Uncertainty quantification is essential for robust controller synthesis to ensure stability and performance under varying conditions, parameters, and external disturbances. To reduce the conservatism in the controller design, a 'tight' description of the uncertainty is crucial. While traditional frequency-domain methods provide effective uncertainty descriptions for single-input single-output (SISO) systems, they often yield inadequate and overly conservative representations in multi-input multi-output (MIM

To exploit the compliant capabilities of soft robot arms we require controller which can exploit their physical capabilities. Teleoperation, leveraging a human in the loop, is a key step towards achieving more complex control strategies. Whilst teleoperation is widely used for rigid robots, for soft robots we require teleoperation methods where the configuration of the whole body is considered. We propose a method of using an identical ‘physical twin’, or demonstrator of the robot. This tendon robot can be

In this paper, we propose a data-driven approach to robust feedback controller design for unknown linear time-invariant (LTI) dynamic systems. Using input-state trajectories and prior knowledge of unknown-but-bounded disturbances, the objective is to synthesize a state-feedback controller that achieves robust stabilization and

\mathcal{H}_2

performance while employing a common quadratic Lyapunov function. Previous works have exclusively considered bounded disturbances described by quadratic matrix inequal

Traffic responsive signal control systems bear high potential in reducing delays in congested networks due to their ability of dynamically adjusting right-of-way assignment among conflicting movements, based on real-time traffic measurements. In this work, we focus on distributed traffic signal control for large-scale networks based on the existing Max-Pressure controller, which has been shown to stabilize queues and maximize throughput in congested conditions. Max-Pressure constitutes a feedback control la

The tokamak in Lausanne, Switzerland (TCV), has been designed to investigate highly elongated plasmas. The elongation improves performance but also introduces a vertical position instability which requires active feedback control to stabilize. The potential high growth rate of this instability requires a fast response time. For this reason TCV has a set of magnetic coils which are placed inside the vacuum vessel. These coils are able to act on the plasma faster than the coils that are located outside of the

This work presents a design methodology and its experimental validation for the input-admittance passivity compliance of LCL grid-connected converters. The designs of the LCL filter parameters and discrete controller are addressed systematically, and suita ...

In air traffic control rooms, paper flight strips are more and more replaced by digital solutions. The digital systems, however, increase the workload for air traffic controllers: For instance, each voice-command must be manually inserted into the system by the controller. Recently the AcListant® project has validated that Assistant Based Speech Recognition (ABSR) can replace the manual inputs by automatically recognized voice commands. Adaptation of ABSR to different environments, however, has shown to be

This paper presents a systematic methodology for the design and the tuning of the current controller in LCL grid-connected converters for wind turbine applications. The design target is formulated as a minimization of the current loop dominant time constan ...

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma ...

A key feature of the new digital plasma control system installed on the TCV (Tokamak à Configuration Variable) tokamak is its possibility to rapidly design, test and deploy real-time algorithms. It accommodates hundreds of diagnostic inputs and actuator ou ...

An integrated numerical system is established to model time-dependent behavior of the neoclassical tearing mode (NTM) in a tokamak which solves the modified Rutherford equation (MRE) by coupling with plasma transport, equilibrium, heating and current drive ...

Nintendo 64 controller

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Controller Design for Structured State-space Models via Contraction Theory

Learning and Control with Generalization and Stability Certificates

Transient Energy Shaping Strategy for Grid-Forming Converters Based on the Port-Hamiltonian Framework

Optimal Frequency-Domain Uncertainty Quantification for MIMO Systems Using Normalised Hausdorff Measure

Control the Soft Robot Arm with its "Physical Twin"

Efficient Sum-of-Squares Approach to Data-Driven Robust Controller Design under Generalized Bounded Disturbances

Efficient Max-Pressure Traffic Management for Large-Scale Congested Urban Networks

Modelling of the FPS for the internal coils and investigating controller discretization effects in TCV

Input-Admittance Passivity Compliance for Grid-Connected Converters With an LCL Filter

Adaptation of Assistant Based Speech Recognition to New Domains and Its Acceptance by Air Traffic Controllers

A Root-Locus Design Methodology Derived From the Impedance/Admittance Stability Formulation and Its Application for LCL Grid-Connected Converters in Wind Turbines

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

Distributed digital real-time control system for the TCV tokamak and its applications

Modeling of neoclassical tearing mode stabilization by electron cyclotron heating and current drive in tokamak plasmas