Imperial College London

Dr Dante Kalise

Faculty of Natural SciencesDepartment of Mathematics

Senior Lecturer in Computational Optimisation and Control
 
 
 
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Contact

 

d.kalise-balza Website CV

 
 
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Location

 

742Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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42 results found

Albi G, Herty M, Kalise D, Segala Cet al., 2022, Moment-driven predictive control of mean-field collective dynamics, SIAM Journal on Control and Optimization, Vol: 60, ISSN: 0363-0129

The synthesis of control laws for interacting agent-based dynamics and their mean-field limit is studied. A linearization-based approach is used for the computation of sub-optimal feedback laws obtained from the solution of differential matrix Riccati equations. Quantification of dynamic performance of such control laws leads to theoretical estimates on suitable linearizationpoints of the nonlinear dynamics. Subsequently, the feedback laws are embedded into nonlinear model predictive control framework where the control is updated adaptively in time according to dynamic information on moments of linear mean-field dynamics. The performance and robustness ofthe proposed methodology is assessed through different numerical experiments in collective dynamics.

Journal article

Kalise D, Carrillo J, Rossi F, Trélat Eet al., 2022, Controlling swarming models towards flocks and mills, SIAM Journal on Control and Optimization, ISSN: 0363-0129

Self-organization and control around flocks and mills is studied for second-order swarming systems involving self-propulsion and potential terms. It is shown that through the action of constrained control, it is possible to control any initial configuration to a flock or a mill. The proof builds on an appropriate combination of several arguments: LaSalle invariance principle and Lyapunov-like decreasing functionals, control linearization techniques and quasi-static deformations. A stability analysis of the second-order system guides the design of feedback laws for the stabilization to flock and mills, which are also assessed computationally.

Journal article

Dutta R, Gomes S, Kalise D, Pacchiardi Let al., 2021, Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic, PLoS Computational Biology, Vol: 17, ISSN: 1553-734X

A mathematical model for the COVID-19 pandemic spread, which integratesage-structured Susceptible-Exposed-Infected-Recovered-Deceased dynamics with realmobile phone data accounting for the population mobility, is presented. The dynamicalmodel adjustment is performed via Approximate Bayesian Computation. Optimallockdown and exit strategies are determined based on nonlinear model predictivecontrol, constrained to public-health and socio-economic factors. Through an extensivecomputational validation of the methodology, it is shown that it is possible to computerobust exit strategies with realistic reduced mobility values to inform public policymaking, and we exemplify the applicability of the methodology using datasets fromEngland and France.

Journal article

Edalatzadeh MS, Kalise D, Morris KA, Sturm Ket al., 2021, Optimal actuator design for the Euler-Bernoulli vibration model based on LQR performance and shape calculus, IEEE Control Systems Letters, Vol: 6, Pages: 1334-1339, ISSN: 2475-1456

A method for optimal actuator design in vibration control is presented. The optimal actuator, parametrized as a characteristic function, is found by means of the topological derivative of the LQR cost. An abstract framework is proposed based on the theory for infinite-dimensional optimization of both the actuator shape and the associated control problem. A numerical realization of the optimality condition is developed for the actuator shape using a level-set method for topological derivatives. A numerical example illustrating the design of actuator for Euler-Bernoulli beam model is provided.

Journal article

Albi G, Bicego S, Kalise D, 2021, Gradient-augmented supervised learning of optimal feedback laws using state-dependent Riccati equations, IEEE Control Systems Letters, Vol: 6, Pages: 836-841, ISSN: 2475-1456

A supervised learning approach for the solution of large-scale nonlinear stabilization problems is presented. A stabilizing feedback law is trained from a dataset generated from State-dependent Riccati Equation solvers. The training phase is enriched by the use of gradient information in the loss function, which is weighted through the use of hyperparameters. High-dimensional nonlinear stabilization tests demonstrate that real-time sequential large-scale Algebraic Riccati Equation solvers can be substituted by a suitably trained feedforward neural network.

Journal article

Wells CA, Williams PD, Nichols NK, Kalise D, Poll Iet al., 2021, Reducing transatlantic flight emissions by fuel-optimised routing, ENVIRONMENTAL RESEARCH LETTERS, Vol: 16, ISSN: 1748-9326

Journal article

Dolgov S, Kalise D, Kunisch KK, 2021, TENSOR DECOMPOSITION METHODS FOR HIGH-DIMENSIONAL HAMILTON-JACOBI-BELLMAN EQUATIONS, SIAM JOURNAL ON SCIENTIFIC COMPUTING, Vol: 43, Pages: A1625-A1650, ISSN: 1064-8275

Journal article

Azmi B, Kalise D, Kunisch K, 2021, Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression, JOURNAL OF MACHINE LEARNING RESEARCH, Vol: 22, ISSN: 1532-4435

Journal article

Kalise D, Kunisch K, Rao Z, 2020, Sparse and switching infinite horizon optimal controls with mixed-norm penalizations, ESAIM-CONTROL OPTIMISATION AND CALCULUS OF VARIATIONS, Vol: 26, ISSN: 1292-8119

Journal article

Kalise D, Kundu S, Kunisch K, 2020, Robust Feedback Control of Nonlinear PDEs by Numerical Approximation of High-Dimensional Hamilton-Jacobi-Isaacs Equations, SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS, Vol: 19, Pages: 1496-1524, ISSN: 1536-0040

Journal article

Choi Y-P, Kalise D, Peszek J, Peters AAet al., 2019, A Collisionless Singular Cucker-Smale Model with Decentralized Formation Control, SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS, Vol: 18, Pages: 1954-1981, ISSN: 1536-0040

Journal article

Kalise Balza DF, Kunisch K, Sturm K, 2018, Optimal actuator design based on shape calculus, Mathematical Models and Methods in Applied Sciences, ISSN: 1793-6314

Journal article

Bailo R, Bongini M, Carrillo JA, Kalise Det al., 2018, Optimal consensus control of the Cucker-Smale model, IFAC-PapersOnLine, Vol: 51, Pages: 1-6, ISSN: 2405-8963

We study the numerical realisation of optimal consensus control laws for agent-based models. For a nonlinear multi-agent system of Cucker-Smale type, consensus control is cast as a dynamic optimisation problem for which we derive first-order necessary optimality conditions. In the case of a smooth penalisation of the control energy, the optimality system is numerically approximated via a gradient-descent method. For sparsity promoting, non-smooth l1-norm control penalisations, the optimal controllers are realised by means of heuristic methods. For an increasing number of agents, we discuss the approximation of the consensus control problem by following a mean-field modelling approach.

Journal article

Herty M, Kalise D, 2018, Suboptimal nonlinear feedback control laws for collective dynamics, International Conference in Control and Automation ICCA 2018, Publisher: IEEE, Pages: 556-561, ISSN: 1948-3449

We present feedback control methodologies for the stabilization of nonlinear collective dynamics. The proposed controllers circumvent the curse of dimensionality associated to dynamic programming of large-scale nonlinear dynamics by means of different structural assumptions on the nonlinearity and the associated Hamilton-Jacobi-Bellman equation. We explore a power series expansion method, and a state-dependent Riccati equation approach. The proposed designs are studied for a relaxed optimal power flow model, and for binary interactions arising in opinion and consensus dynamics.

Conference paper

Albi G, Kalise D, 2018, (Sub)Optimal feedback control of mean field multi-population dynamics, IFAC-PapersOnLine, Vol: 51, Pages: 86-91, ISSN: 2405-8963

We study a multiscale approach for the control of agent-based, two-population models. The control variable acts over one population of leaders, which influence the population of followers via the coupling generated by their interaction. We cast a quadratic optimal control problem for the large-scale microscale model, which is approximated via a Boltzmann approach. By sampling solutions of the optimal control problem associated to binary two-population dynamics, we generate sub-optimal control laws for the kinetic limit of the multi-population model. We present numerical experiments related to opinion dynamics assessing the performance of the proposed control design.

Journal article

Briceno-Arias LM, Kalise D, Silva FJ, 2018, Proximal Methods for Stationary Mean Field Games with Local Couplings, SIAM Journal on Control and Optimization, Vol: 56, Pages: 801-836, ISSN: 0363-0129

Journal article

Kalise D, Kunisch K, 2018, POLYNOMIAL APPROXIMATION OF HIGH-DIMENSIONAL HAMILTON JACOBI BELLMAN EQUATIONS AND APPLICATIONS TO FEEDBACK CONTROL OF SEMILINEAR PARABOLIC PDES, SIAM JOURNAL ON SCIENTIFIC COMPUTING, Vol: 40, Pages: A629-A652, ISSN: 1064-8275

Journal article

Albi G, Choi Y-P, Fornasier M, Kalise Det al., 2017, Mean Field Control Hierarchy, APPLIED MATHEMATICS AND OPTIMIZATION, Vol: 76, Pages: 93-135, ISSN: 0095-4616

Journal article

Kalise D, Kunisch K, Rao Z, 2017, Infinite Horizon Sparse Optimal Control, JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, Vol: 172, Pages: 481-517, ISSN: 0022-3239

Journal article

Albi G, Fornasier M, Kalise D, 2017, A Boltzmann approach to mean-field sparse feedback control, IFAC PAPERSONLINE, Vol: 50, Pages: 2898-2903, ISSN: 2405-8963

Journal article

Tonon D, Aronna MS, Kalise D, 2017, Optimal Control: Novel Directions and Applications Preface, OPTIMAL CONTROL: NOVEL DIRECTIONS AND APPLICATIONS, Editors: Tonon, Aronna, Kalise, Publisher: SPRINGER-VERLAG BERLIN, Pages: VII-VIII, ISBN: 978-3-319-60770-2

Book chapter

Fuentes E, Kalise D, Kennel RM, 2016, Smoothened Quasi-Time-Optimal Control for the Torsional Torque in a Two-Mass System, IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, Vol: 63, Pages: 3954-3963, ISSN: 0278-0046

Journal article

Alla A, Falcone M, Kalise D, 2016, A HJB-POD feedback synthesis approach for the wave equation, BULLETIN OF THE BRAZILIAN MATHEMATICAL SOCIETY, Vol: 47, Pages: 51-64, ISSN: 1678-7544

Journal article

Braun P, Hernandez E, Kalise D, 2016, Reduced-order LQG control of a Timoshenko beam model, BULLETIN OF THE BRAZILIAN MATHEMATICAL SOCIETY, Vol: 47, Pages: 143-155, ISSN: 1678-7544

Journal article

Albi G, Bongini M, Cristiani E, Kalise Det al., 2016, INVISIBLE CONTROL OF SELF-ORGANIZING AGENTS LEAVING UNKNOWN ENVIRONMENTS, SIAM JOURNAL ON APPLIED MATHEMATICS, Vol: 76, Pages: 1683-1710, ISSN: 0036-1399

Journal article

Kalise D, Kroener A, Kunisch K, 2016, LOCAL MINIMIZATION ALGORITHMS FOR DYNAMIC PROGRAMMING EQUATIONS, SIAM JOURNAL ON SCIENTIFIC COMPUTING, Vol: 38, Pages: A1587-A1615, ISSN: 1064-8275

Journal article

Bokanowski O, Falcone M, Ferretti R, Gruene L, Kalise D, Zidani Het al., 2015, VALUE ITERATION CONVERGENCE OF epsilon-MONOTONE SCHEMES FOR STATIONARY HAMILTON-JACOBI EQUATIONS, DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS, Vol: 35, Pages: 4041-4070, ISSN: 1078-0947

Journal article

Bongini M, Fornasier M, Kalise D, 2015, (UN)CONDITIONAL CONSENSUS EMERGENCE UNDER PERTURBED AND DECENTRALIZED FEEDBACK CONTROLS, DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS, Vol: 35, Pages: 4071-4094, ISSN: 1078-0947

Journal article

Alla A, Falcone M, Kalise D, 2015, An accelerated value/policy iteration scheme for optimal control problems and games, Lecture Notes in Computational Science and Engineering, Vol: 103, Pages: 489-497, ISSN: 1439-7358

We present an accelerated algorithm for the solution of static Hamilton-Jacobi-Bellman equations related to optimal control problems and differential games. The new scheme combines the advantages of value iteration and policy iteration methods by means of an efficient coupling. The method starts with a value iteration phase on a coarse mesh and then switches to a policy iteration procedure over a finer mesh when a fixed error threshold is reached.We present numerical tests assessing the performance of the scheme.

Journal article

Alla A, Falcone M, Kalise D, 2015, An accelerated value/policy iteration scheme for optimal control problems and games, Lecture Notes in Computational Science and Engineering, Vol: 103, Pages: 489-497, ISSN: 1439-7358

We present an accelerated algorithm for the solution of static Hamilton-Jacobi-Bellman equations related to optimal control problems and differential games. The new scheme combines the advantages of value iteration and policy iteration methods by means of an efficient coupling. The method starts with a value iteration phase on a coarse mesh and then switches to a policy iteration procedure over a finer mesh when a fixed error threshold is reached.We present numerical tests assessing the performance of the scheme.

Journal article

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