| Improving lifetime of fuel cell in hybrid energy management system by lure–lyapunov-based control formulation S Mane, M Mejari, F Kazi, N Singh IEEE Transactions on Industrial Electronics 64 (8), 6671-6679, 2017 | 39 | 2017 |
| A bias-correction method for closed-loop identification of Linear Parameter-Varying systems M Mejari, D Piga, A Bemporad Automatica 87, 128-141, 2018 | 32 | 2018 |
| Identification of hybrid and linear parameter‐varying models via piecewise affine regression using mixed integer programming M Mejari, VV Naik, D Piga, A Bemporad International Journal of Robust and Nonlinear Control, 2020 | 13* | 2020 |
| Regularized moving-horizon piecewise affine regression using mixed-integer quadratic programming VV Naik, M Mejari, D Piga, A Bemporad 2017 25th Mediterranean Conference on Control and Automation (MED), 1349-1354, 2017 | 13 | 2017 |
| Regularized least square support vector machines for order and structure selection of LPV-ARX models M Mejari, D Piga, A Bemporad 2016 European Control Conference (ECC), 1649-1654, 2016 | 10 | 2016 |
| Robust tube based MPC for PVTOL trajectory tracking using systems flatness property S Petkar, S Umbarkar, M Mejari, NM Singh, F Kazi 2016 International Conference on Unmanned Aircraft Systems (ICUAS), 1095-1101, 2016 | 8 | 2016 |
| Nonlinear model predictive control of pvtol aircraft under state and input constraints A Gupta, M Mejari, V Ketkar, M Datar, NM Singh Proceedings of conference on advances in robotics, 1-6, 2013 | 8 | 2013 |
| Recursive bias-correction method for identification of piecewise affine output-error models M Mejari, V Breschi, D Piga IEEE Control Systems Letters 4 (4), 970-975, 2020 | 7 | 2020 |
| Energy disaggregation using piecewise affine regression and binary quadratic programming M Mejari, VV Naik, D Piga, A Bemporad 2018 IEEE Conference on Decision and Control (CDC), 3116-3121, 2018 | 7 | 2018 |
| Trajectory tracking of quadrotor with bounded thrust using model predictive control M Mejari, A Gupta, NM Singh, F Kazi Proceedings of Conference on Advances In Robotics, 1-6, 2013 | 6 | 2013 |
| Realization and identification algorithm for stochastic LPV state-space models with exogenous inputs M Mejari, M Petreczky arXiv preprint arXiv:1905.10113, 2019 | 5 | 2019 |
| Realization and identification algorithm for stochastic LPV state-space models with exogenous inputs M Mejari, M Petreczky IFAC-PapersOnLine 52 (28), 13-19, 2019 | 5 | 2019 |
| Consistent and computationally efficient estimation for stochastic LPV state-space models: realization based approach M Mejari, M Petreczky 2019 IEEE 58th Conference on Decision and Control (CDC), 3805-3810, 2019 | 4 | 2019 |
| Regularized moving-horizon pwa regression for lpv system identification M Mejari, VV Naik, D Piga, A Bemporad IFAC-PapersOnLine 51 (15), 1092-1097, 2018 | 4 | 2018 |
| Computation of parameter dependent robust invariant sets for LPV models with guaranteed performance A Gupta, M Mejari, P Falcone, D Piga Automatica 151, 110920, 2023 | 2 | 2023 |
| Direct identification of continuous-time LPV state-space models via an integral architecture M Mejari, B Mavkov, M Forgione, D Piga Automatica 142, 110407, 2022 | 2 | 2022 |
| Shrinkage strategies for structure selection and identification of piecewise affine models V Breschi, M Mejari 2020 59th IEEE Conference on Decision and Control (CDC), 1626-1631, 2020 | 2 | 2020 |
| A bias-correction approach for the identification of piecewise affine output-error models M Mejari, V Breschi, VV Naik, D Piga IFAC-PapersOnLine 53 (2), 1096-1101, 2020 | 2 | 2020 |
| Motion planning for the three wheel mobile robot using the reachable set computation under constraints M Datar, V Ketkar, M Mejari, A Gupta, N Singh, F Kazi IFAC Proceedings Volumes 47 (1), 787-793, 2014 | 2 | 2014 |
| Learning neural state-space models: do we need a state estimator? M Forgione, M Mejari, D Piga arXiv preprint arXiv:2206.12928, 2022 | 1 | 2022 |
Dario PigaSenior Researcher at IDSIA - Dalle Molle Institute for ArtificiaI Intelligence, SUPSI-USI, LuganoVerified email at supsi.ch
