Data-driven simulation and control

2008/09/18 by Ivan Markovsky, Paolo Rapisarda · 318 citations
Engineering · Mathematics · Physics and Astronomy · #Artificial intelligence #Computer science #Control (management) #Control Systems and Identification #Control system #Control theory (sociology) #Data modeling #Engineering #Fault Detection and Control Systems #Impulse (physics) #Impulse response #LTI system theory #Linear system #Mathematics #Model Reduction and Neural Networks #Quadratic equation #Representation (politics) #System identification #Trajectory #Transfer function

paper · doi:10.1080/00207170801942170

published in International Journal of Control 81(12), 1946-1959 (Taylor & Francis)

openalex publication_date 2008/09/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

Classical linear time-invariant system simulation methods are based on a transfer function, impulse response, or input/state/output representation. We present a method for computing the response of a system to a given input and initial conditions directly from a trajectory of the system, without explicitly identifying the system from the data. Similar to the classical approach for simulation, the classical approach for control is model-based: first a model representation is derived from given data of the plant and then a control law is synthesised using the model and the control specifications. We present an approach for computing a linear quadratic tracking control signal that circumvents the identification step. The results are derived assuming exact data and the simulated response or control input is constructed off-line.

Cited by

• Data-Driven Model Predictive Control with Stability and Robustness Guarantees
• Combining Prior Knowledge and Data for Robust Controller Design
• Data-Driven Dissipativity Analysis of Linear Parameter-Varying Systems
• From model-based control to data-driven control: Survey, classification and perspective
• Data-driven functional state estimation of complex networks
• Control-Oriented System Identification: Classical, Learning, and Physics-Informed Approaches
• Input-Output Data-Driven Representation: Non-Minimality and Stability
• Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
• An Innovations-Based Data-Driven Kalman Predictor for Predictive Control
• Online Subspace Learning on Flag Manifolds for System Identification
• Data-Driven Stabilization Using Prior Knowledge on Stabilizability and Controllability
• Adaptive Robust Data-Driven Building Control via Bilevel Reformulation: An Experimental Result
• From Time Series to Affine Systems
• Data-driven Stabilization of SISO Feedback Linearizable Systems
• Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
• Koopman based data-driven predictive control
• Data-driven control on encrypted data
• DeeP-TE: Data-enabled Predictive Traffic Engineering
• Direct data-driven interpolation and approximation of linear parameter-varying system trajectories
• DeePConverter: A Data-Driven Optimal Control Architecture for Grid-Connected Power Converters
• Online Data-Enabled Predictive Control
• On Controllability and Persistency of Excitation in Data-Driven Control: Extensions of Willems' Fundamental Lemma
• Non-conservative Design of Robust Tracking Controllers Based on Input-output Data
• Data-Driven Predictive Planning and Control for Aerial 3D Inspection with Back-face Elimination
• Linear-Quadratic Discrete-Time Dynamic Games with Unknown Dynamics
• Data-Driven System Level Synthesis
• Behavioural Approach to Distributed Control of Interconnected Systems
• Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning
• Split-as-a-Pro: behavioral control via operator splitting and alternating projections
• Decentralized Data-Enabled Predictive Control for Power System Oscillation Damping
• Discovering Mechanistic Causality from Time Series: A Behavioral-System Approach
• Controller Design for Robust Invariance From Noisy Data
• Leveraging Non-Steady-State Frequency-Domain Data in Willems' Fundamental Lemma
• Data-driven control of complex networks. [europepmc]
• Data-enabled predictive control for quadcopters. [europepmc]
• Improved data driven strategy for aircraft controller design. [europepmc]

Related

• Data-Based System Analysis and Control of Flat Nonlinear Systems
• Data-Driven System Level Synthesis
• Data-Driven Synthesis of Optimization-Based Controllers for Regulation of Unknown Linear Systems
• Data-Driven Inverse of Linear Systems and Application to Disturbance Observers
• Data-Driven Internal Model Control of Second-Order Discrete Volterra\n Systems