1 citations · 2 across the 18 of their papers we have counts for
20 papers
On the suboptimality of stochastic MPC with varying constraint horizon
Allan Andre Do Nascimento, Andre Bertolace, Antonis Papachristodoulou +1
Enforcing stochastic state constraints over the full prediction horizon in Model Predictive Control (MPC) can be computationally demanding. Here we study stochastic MPC without ter…
A New Approach for Feedback Stabilization and its Application for Data-Driven Control of Polynomial Systems
Diego de S. Madeira, Joao Gabriel N. Silva, Wilkley B. Correia +1
Inspired by recent developments in dissipativity-based control, this work proposes new sufficient conditions for asymptotic stabilization of nonlinear systems using state feedback.…
A Koopman Set-Membership Approach for Nonlinear Data-Driven Control with Stability Guarantees
Yifan Xie, Zuxun Xiong, Julian Berberich +2
This paper proposes a data-driven controller design method for unknown nonlinear systems based on a Koopman bilinear realization. Using Koopman operator theory, the nonlinear syste…
A Prototyping Framework for Distributed Control of Multi-Robot Systems
Junaid Ahmed Memon, Allan Andre Do Nascimento, Kostas Margellos +1
This paper presents a prototyping framework for distributed control of multi-robot systems, aimed at bridging theory and practical testing of distributed optimization algorithms. U…
Acceleration of Moment Bound Optimization for Stochastic Chemical Reactions Using Reaction-wise Sparsity of Moment Equations
Tomoki Sadatoshi, Antonis Papachristodoulou, Yutaka Hori
Moment dynamics in stochastic chemical kinetics often involve an infinite chain of coupled equations, where lower-order moments depend on higher-order ones, making them analyticall…
Distributed Sum-of-Squares Programming for Local Stability Analysis of Polynomial PDEs
Carl R Richardson, Declan S Jagt, Matthew M Peet +1
It has recently been shown that the evolution of a state, described by a Partial Differential Equation (PDE), can be more conveniently represented as the evolution of the state's h…
Host-Aware Control of Gene Expression using Data-Enabled Predictive Control
Liam Perreault, Idris Kempf, Kirill Sechkar +2
Cybergenetic gene expression control in bacteria enables applications in engineering biology, drug development, and biomanufacturing. AI-based controllers offer new possibilities f…
On the Design of Rational Polynomial State Feedback Controllers
Matthew Newton, Zuxun Xiong, Han Wang +1
One of the desirable objectives in feedback control design is to formulate and solve the design problem as an optimisation problem that is convex, so that an optimal solution can b…
Model Predictive Control with Multiple Constraint Horizons
Allan Andre do Nascimento, Han Wang, Antonis Papachristodoulou +1
We propose a Model Predictive Control (MPC) formulation for nonlinear systems without terminal penalty or dedicated stabilizing terminal set, in which state constraints are enforce…
Constrained Diffusers for Safe Planning and Control
Jichen Zhang, Liqun Zhao, Antonis Papachristodoulou +1
Diffusion models have shown remarkable potential in planning and control tasks due to their ability to represent multimodal distributions over actions and trajectories. However, en…
Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity
Han Wang, Keyan Miao, Diego Madeira +1
Deep learning methods have demonstrated significant potential for addressing complex nonlinear control problems. For real-world safety-critical tasks, however, it is crucial to pro…
Synthesis of safety certificates for discrete-time uncertain systems via convex optimization
Marta Fochesato, Han Wang, Antonis Papachristodoulou +1
We study the problem of co-designing control barrier functions and linear state feedback controllers for discrete-time linear systems affected by additive disturbances. For disturb…
Data-Enabled Predictive Control for Nonlinear Systems Based on a Koopman Bilinear Realization
Zuxun Xiong, Zhenyi Yuan, Keyan Miao +3
This paper extends the Willems' Fundamental Lemma to nonlinear control-affine systems using the Koopman bilinear realization. This enables us to bypass the Extended Dynamic Mode De…
Opt-ODENet: A Neural ODE Framework with Differentiable QP Layers for Safe and Stable Control Design (longer version)
Keyan Miao, Liqun Zhao, Han Wang +2
Designing controllers that achieve task objectives while ensuring safety is a key challenge in control systems. This work introduces Opt-ODENet, a Neural ODE framework with a diffe…
Constraint Horizon in Model Predictive Control
Allan Andre Do Nascimento, Han Wang, Antonis Papachristodoulou +1
In this work, we propose a Model Predictive Control (MPC) formulation incorporating two distinct horizons: a prediction horizon and a constraint horizon. This approach enables a de…
Analysing control-theoretic properties of nonlinear synthetic biology circuits
Antón Pardo, Sandra Díaz Seoane, Dorin A. Ionescu +2
Synthetic biology is a recent area of biological engineering, whose aim is to provide cells with novel functionalities. A number of important results regarding the development of c…
Probabilistically safe controllers based on control barrier functions and scenario model predictive control
Allan Andre do Nascimento, Antonis Papachristodoulou, Kostas Margellos
Control barrier functions (CBFs) offer an efficient framework for designing real-time safe controllers. However, CBF-based controllers can be short-sighted, resulting in poor perfo…
Safe and Stable Filter Design Using a Relaxed Compatibitlity Control Barrier -- Lyapunov Condition
Han Wang, Kostas Margellos, Antonis Papachristodoulou
In this paper, we propose a quadratic programming-based filter for safe and stable controller design, via a Control Barrier Function (CBF) and a Control Lyapunov Function (CLF). Ou…
Data-Driven Stable Neural Feedback Loop Design
Zuxun Xiong, Han Wang, Liqun Zhao +1
This paper proposes a data-driven approach to design a feedforward Neural Network (NN) controller with a stability guarantee for plants with unknown dynamics. We first introduce da…
Convex Co-Design of Control Barrier Function and Safe Feedback Controller Under Input Constraints
Han Wang, Kostas Margellos, Antonis Papachristodoulou +1
We study the problem of co-designing control barrier functions (CBF) and linear state feedback controllers for continuous-time linear systems. We achieve this by means of a single…