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Related papers: An Optimal Control Formulation of Pulse-Based Cont…

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In this paper, we further develop a recently proposed control method to switch a bistable system between its steady states using temporal pulses. The motivation for using pulses comes from biomedical and biological applications (e.g.…

Systems and Control · Computer Science 2016-05-26 Aivar Sootla , Alexandre Mauroy , Jorge Goncalves

In applications, such as biomedicine and systems/synthetic biology, technical limitations in actuation complicate implementation of time-varying control signals. In order to alleviate some of these limitations, it may be desirable to derive…

Systems and Control · Computer Science 2017-08-02 Aivar Sootla , Damien Ernst

The Koopman operator enables simplified representations for nonlinear systems in data-driven optimal control, but the accompanying uncertainties inevitably induce deviations in the optimal controller and associated value function. This…

Systems and Control · Electrical Eng. & Systems 2026-04-08 Yicheng Lin , Bingxian Wu , Nan Bai , Yunxiao Ren , Zhongkui Li , Zhisheng Duan

A high order optimal control strategy implemented in the Koopman operator framework is proposed in this work. The new technique exploits the Koopman representation of the solution of the equations of motion to develop an energy optimal…

Optimization and Control · Mathematics 2022-07-15 Simone Servadio , Roberto Armellin , Richard Linares

This paper presents a study of the Koopman operator theory and its application to optimal control of a multi-robot system. The Koopman operator, while operating on a set of observation functions of the state vector of a nonlinear system,…

Systems and Control · Electrical Eng. & Systems 2023-05-09 Gang Tao , Qianhong Zhao

In recent years, the success of the Koopman operator in dynamical systems analysis has also fueled the development of Koopman operator-based control frameworks. In order to preserve the relatively low data requirements for an approximation…

Optimization and Control · Mathematics 2020-10-15 Sebastian Peitz , Samuel E. Otto , Clarence W. Rowley

We present a new framework for optimal and feedback control of PDEs using Koopman operator-based reduced order models (K-ROMs). The Koopman operator is a linear but infinite-dimensional operator which describes the dynamics of observables.…

Dynamical Systems · Mathematics 2019-08-14 Sebastian Peitz , Stefan Klus

The design and analysis of optimal control policies for dynamical systems can be complicated by nonlinear dependence in the state variables. Koopman operators have been used to simplify the analysis of dynamical systems by mapping the flow…

Dynamical Systems · Mathematics 2019-08-07 Craig Bakker , Steven Rosenthal , Kathleen E. Nowak

In the development of model predictive controllers for PDE-constrained problems, the use of reduced order models is essential to enable real-time applicability. Besides local linearization approaches, Proper Orthogonal Decomposition (POD)…

Optimization and Control · Mathematics 2020-12-15 Sebastian Peitz , Stefan Klus

This paper investigates the impact of approximation error in data-driven optimal control problem of nonlinear systems while using the Koopman operator. While the Koopman operator enables a simplified representation of nonlinear dynamics…

Optimization and Control · Mathematics 2026-03-31 Yicheng Lin , Bingxian Wu , Nan Bai , Yunxiao Ren , Zhisheng Duan

We present a data-driven approach to use the Koopman generator for prediction and optimal control of control-affine stochastic systems. We provide a novel conceptual approach and a proof-of-principle for the determination of optimal control…

Optimization and Control · Mathematics 2024-10-15 Lei Guo , Jan Heiland , Feliks Nüske

Controlling nonlinear dynamical systems remains a central challenge in a wide range of applications, particularly when accurate first-principle models are unavailable. Data-driven approaches offer a promising alternative by designing…

Systems and Control · Electrical Eng. & Systems 2025-12-23 Robin Strässer , Karl Worthmann , Igor Mezić , Julian Berberich , Manuel Schaller , Frank Allgöwer

Nonlinear optimal control is vital for numerous applications but remains challenging for unknown systems due to the difficulties in accurately modelling dynamics and handling computational demands, particularly in high-dimensional settings.…

Systems and Control · Electrical Eng. & Systems 2024-12-03 Zhexuan Zeng , Ruikun Zhou , Yiming Meng , Jun Liu

The path-integral control, which stems from the stochastic Hamilton-Jacobi-Bellman equation, is one of the methods to control stochastic nonlinear systems. This paper gives a new insight into nonlinear stochastic optimal control problems…

Optimization and Control · Mathematics 2021-09-14 Jun Ohkubo

We consider the optimal control of quantum systems interacting non-linearly with an electromagnetic field. We propose new monotonically convergent algorithms to solve the optimal equations. The monotonic behavior of the algorithm is ensured…

Quantum Physics · Physics 2015-05-13 M. Lapert , R. Tehini , G. Turinici , D. Sugny

Trajectory optimization is a widely used tool in the design and control of dynamical systems. Typically, not only nonlinear dynamics, but also couplings of the initial and final condition through implicit boundary constraints render the…

Optimization and Control · Mathematics 2024-12-05 Mohamed Abou-Taleb , Maximilian Raff , Kathrin Flaßkamp , C. David Remy

This paper describes the optimal selection of a control policy to program the steady state of controlled nonlinear systems with hyperbolic fixed points. This work is motivated by the field of synthetic biology, in which saddle points are…

Dynamical Systems · Mathematics 2020-06-11 Aqib Hasnain , Nibodh Boddupalli , Shara Balakrishnan , Enoch Yeung

In this paper we study how to shape temporal pulses to switch a bistable system between its stable steady states. Our motivation for pulse-based control comes from applications in synthetic biology, where it is generally difficult to…

Optimization and Control · Mathematics 2015-10-05 Aivar Sootla , Diego Oyarzun , David Angeli , Guy-Bart Stan

This paper presents a data-driven method to find a closed-loop optimal controller, which minimizes a specified infinite-horizon cost function for systems with unknown dynamics. Suppose the closed-loop optimal controller can be parameterized…

Machine Learning · Computer Science 2025-11-20 Wenjian Hao , Paulo C. Heredia , Shaoshuai Mou

This paper introduces a framework for solving time-autonomous nonlinear infinite horizon optimal control problems, under the assumption that all minimizers satisfy Pontryagin's necessary optimality conditions. In detail, we use methods from…

Optimization and Control · Mathematics 2020-03-04 Mario E. Villanueva , Colin Jones , Boris Houska
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