Zobrazeno 1 - 10
of 177
pro vyhledávání: '"LAZĂR, Mircea"'
Autor:
Lazar, Mircea
In this work, we consider the problem of learning nonlinear operators that correspond to discrete-time nonlinear dynamical systems with inputs. Given an initial state and a finite input trajectory, such operators yield a finite output trajectory comp
Externí odkaz:
http://arxiv.org/abs/2412.18360
Autor:
de Jong, Thomas Oliver, Lazar, Mircea
This paper presents a kernelized offset-free data-driven predictive control scheme for nonlinear systems. Traditional model-based and data-driven predictive controllers often struggle with inaccurate predictors or persistent disturbances, especially
Externí odkaz:
http://arxiv.org/abs/2411.18762
This paper presents a stochastic model predictive control (SMPC) algorithm for linear systems subject to additive Gaussian mixture disturbances, with the goal of satisfying chance constraints. To synthesize a control strategy, the stochastic control
Externí odkaz:
http://arxiv.org/abs/2411.07887
This paper considers learning online (implicit) nonlinear model predictive control (MPC) laws using neural networks and Laguerre functions. Firstly, we parameterize the control sequence of nonlinear MPC using Laguerre functions, which typically yield
Externí odkaz:
http://arxiv.org/abs/2409.09436
Autor:
Xu, Duo, Lazar, Mircea
This paper considers the design of finite control set model predictive control (FCS-MPC) for discrete-time switched affine systems. Existing FCS-MPC methods typically pursue practical stability guarantees, which ensure convergence to a bounded invari
Externí odkaz:
http://arxiv.org/abs/2407.07615
Autor:
Lazar, Mircea
Data-enabled predictive control (DeePC) for linear systems utilizes data matrices of recorded trajectories to directly predict new system trajectories, which is very appealing for real-life applications. In this paper we leverage the universal approx
Externí odkaz:
http://arxiv.org/abs/2406.08003
Mechatronic systems are described by an interconnection of the electromagnetic part, i.e., a static position-dependent nonlinear relation between currents and forces, and the mechanical part, i.e., a dynamic relation from forces to position. Commutat
Externí odkaz:
http://arxiv.org/abs/2406.05040
In this paper, we consider the design of data-driven predictive controllers for nonlinear systems from input-output data via linear-in-control input Koopman lifted models. Instead of identifying and simulating a Koopman model to predict future output
Externí odkaz:
http://arxiv.org/abs/2405.01292
Autor:
Engelaar, Maico H. W., Zhang, Zengjie, Vlahakis, Eleftherios E., Dimarogonas, Dimos V., Lazar, Mircea, Haesaert, Sofie
This paper addresses the control synthesis of heterogeneous stochastic linear multi-agent systems with real-time allocation of signal temporal logic (STL) specifications. Based on previous work, we decompose specifications into sub-specifications on
Externí odkaz:
http://arxiv.org/abs/2404.02111
Well-designed current control is a key factor in ensuring the efficient and safe operation of modular multilevel converters (MMCs). Even though this control problem involves multiple control objectives, conventional current control schemes are compri
Externí odkaz:
http://arxiv.org/abs/2403.18371