The Experts below are selected from a list of 12048 Experts worldwide ranked by ideXlab platform
Luca Zaccarian - One of the best experts on this subject based on the ideXlab platform.
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High-Gain Dead-Zone Observers for Linear and Nonlinear Plants
IEEE Control Systems Letters, 2019Co-Authors: Matteo Cocetti, Sophie Tarbouriech, Luca ZaccarianAbstract:We propose an adaptive dead-zone mechanism to robustify Observers aGainst high-frequency noise. The construction applies to Luenberger Observers and high-Gain Observers for plants in strict feedback form. The dead-zone improves performances by trimming a portion of the output injection term and trapping the high frequency noise in the dead band. We show that the Observer Gain and the adaptation parameters can be obtained by solving a linear matrix inequality, whose feasibility only requires detectability of the plant. The parameters obtained through this optimization ensure (in the absence of noise) global exponential stability of the estimation error dynamics, and input-to-state stability (ISS) from the measurement noise to the estimation error.
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A kinematic Observer with adaptive dead-zone for vehicles lateral velocity estimation
2018Co-Authors: Luca Zaccarian, Luca De Pascali, Francesco Biral, Matteo Cocetti, Sophie TarbouriechAbstract:In this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic Observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone Observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic Observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger Observer Gain. We use this freedom to increase the Observer Gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations.
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AMC - A kinematic Observer with adaptive dead-zone for vehicles lateral velocity estimation
2018 IEEE 15th International Workshop on Advanced Motion Control (AMC), 2018Co-Authors: Luca De Pascali, Luca Zaccarian, Francesco Biral, Matteo Cocetti, Sophie TarbouriechAbstract:In this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic Observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone Observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic Observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger Observer Gain. We use this freedom to increase the Observer Gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations.
Sophie Tarbouriech - One of the best experts on this subject based on the ideXlab platform.
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High-Gain Dead-Zone Observers for Linear and Nonlinear Plants
IEEE Control Systems Letters, 2019Co-Authors: Matteo Cocetti, Sophie Tarbouriech, Luca ZaccarianAbstract:We propose an adaptive dead-zone mechanism to robustify Observers aGainst high-frequency noise. The construction applies to Luenberger Observers and high-Gain Observers for plants in strict feedback form. The dead-zone improves performances by trimming a portion of the output injection term and trapping the high frequency noise in the dead band. We show that the Observer Gain and the adaptation parameters can be obtained by solving a linear matrix inequality, whose feasibility only requires detectability of the plant. The parameters obtained through this optimization ensure (in the absence of noise) global exponential stability of the estimation error dynamics, and input-to-state stability (ISS) from the measurement noise to the estimation error.
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A kinematic Observer with adaptive dead-zone for vehicles lateral velocity estimation
2018Co-Authors: Luca Zaccarian, Luca De Pascali, Francesco Biral, Matteo Cocetti, Sophie TarbouriechAbstract:In this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic Observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone Observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic Observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger Observer Gain. We use this freedom to increase the Observer Gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations.
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AMC - A kinematic Observer with adaptive dead-zone for vehicles lateral velocity estimation
2018 IEEE 15th International Workshop on Advanced Motion Control (AMC), 2018Co-Authors: Luca De Pascali, Luca Zaccarian, Francesco Biral, Matteo Cocetti, Sophie TarbouriechAbstract:In this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic Observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone Observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic Observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger Observer Gain. We use this freedom to increase the Observer Gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations.
Matteo Cocetti - One of the best experts on this subject based on the ideXlab platform.
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High-Gain Dead-Zone Observers for Linear and Nonlinear Plants
IEEE Control Systems Letters, 2019Co-Authors: Matteo Cocetti, Sophie Tarbouriech, Luca ZaccarianAbstract:We propose an adaptive dead-zone mechanism to robustify Observers aGainst high-frequency noise. The construction applies to Luenberger Observers and high-Gain Observers for plants in strict feedback form. The dead-zone improves performances by trimming a portion of the output injection term and trapping the high frequency noise in the dead band. We show that the Observer Gain and the adaptation parameters can be obtained by solving a linear matrix inequality, whose feasibility only requires detectability of the plant. The parameters obtained through this optimization ensure (in the absence of noise) global exponential stability of the estimation error dynamics, and input-to-state stability (ISS) from the measurement noise to the estimation error.
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A kinematic Observer with adaptive dead-zone for vehicles lateral velocity estimation
2018Co-Authors: Luca Zaccarian, Luca De Pascali, Francesco Biral, Matteo Cocetti, Sophie TarbouriechAbstract:In this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic Observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone Observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic Observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger Observer Gain. We use this freedom to increase the Observer Gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations.
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AMC - A kinematic Observer with adaptive dead-zone for vehicles lateral velocity estimation
2018 IEEE 15th International Workshop on Advanced Motion Control (AMC), 2018Co-Authors: Luca De Pascali, Luca Zaccarian, Francesco Biral, Matteo Cocetti, Sophie TarbouriechAbstract:In this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic Observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone Observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic Observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger Observer Gain. We use this freedom to increase the Observer Gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations.
Tarek Raïssi - One of the best experts on this subject based on the ideXlab platform.
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Design of Optimal Interval Observers Using Set-Theoretic Methods for Robust State Estimation
International Journal of Robust and Nonlinear Control, 2020Co-Authors: Junbo Tan, Tarek Raïssi, Bin LiangAbstract:This paper aims to design an optimal interval Observer for discrete linear time-invariant (LTI) systems. Particularly, the proposed design method first transforms the interval Observer into a zonotopic set-valued Observer by establishing an explicit mathematical relationship between the interval Observer and the zonoptopic set-valued Observer. Then, based on the established mathematical relationship, a local optimal Observer Gain is designed for the interval Observer via the equivalent zonotopic set-valued Observer structure and the Frobenious norm (F-norm) based size of zonotopes. Third, considering that the dynamics of the optimal interval Observer becomes a discrete linear time varying (LTV) system owing to the designed timevarying optimal Gain, an optimization problem to obtain a coordinate transformation matrix and the local optimal Observer Gain for the interval Observer is formulated and handled. Finally, a theoretic comparison on the conservatism of the interval Observer and the zonotopic set-valued Observer is made. At the end of this paper, a microbial growth bioprocess is used to illustrate the effectiveness of the proposed method.
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Design of optimal interval Observers using set‐theoretic methods for robust state estimation
International Journal of Robust and Nonlinear Control, 2020Co-Authors: Junbo Tan, Tarek Raïssi, Bin LiangAbstract:This paper aims to design an optimal interval Observer for discrete linear time-invariant (LTI) systems. Particularly, the proposed design method first transforms the interval Observer into a zonotopic set-valued Observer by establishing an explicit mathematical relationship between the interval Observer and the zonoptopic set-valued Observer. Then, based on the established mathematical relationship, a local optimal Observer Gain is designed for the interval Observer via the equivalent zonotopic set-valued Observer structure and the Frobenious norm (F-norm) based size of zonotopes. Third, considering that the dynamics of the optimal interval Observer becomes a discrete linear time varying (LTV) system owing to the designed timevarying optimal Gain, an optimization problem to obtain a coordinate transformation matrix and the local optimal Observer Gain for the interval Observer is formulated and handled. Finally, a theoretic comparison on the conservatism of the interval Observer and the zonotopic set-valued Observer is made. At the end of this paper, a microbial growth bioprocess is used to illustrate the effectiveness of the proposed method.
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On Interval Observer Design for Time-Invariant Discrete-Time Systems
2013Co-Authors: Denis Efimov, Tarek Raïssi, Wilfrid Perruquetti, Ali ZolghadriAbstract:The problem of interval state Observer design is addressed for time-invariant discrete-time systems. Two solutions are proposed: the first one is based on a similarity transformation synthesis, which connects a constant matrix with its nonnegative representation ensuring the observation error positivity. The second contribution shows that in discrete-time case the estima-tion error dynamics always can be epresented in a cooperative form without a transformation of coordinates. The corresponding Observer Gain can be found as a solution of the formulated LMIs. The performances of the proposed Observers are demonstrated through computer simulations.
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Guaranteed state estimation for nonlinear continuous-time systems based on qLPV transformations
2009Co-Authors: Gaétan Videau, Tarek Raïssi, Ali ZolghadriAbstract:This paper deals with guaranteed state estimation for a large class of nonlinear continuous-time systems in a bounded error context. The proposed Observer is based on a guaranteed Linear Parameter-Varying (LPV) transformation of the original nonlinear model. The linearisation is justified since it is difficult to develop generic methods for computing a stable Observer for a nonlinear system. The Luenberger structure is used and the Observer Gain is designed so that to satisfy the cooperativity property and the positivity of the observation error. This approach makes the Observer less pessimistic than interval Taylor Observers. The methodology is illustrated through simulations on a numerical example.
J Luomi - One of the best experts on this subject based on the ideXlab platform.
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a combined position and stator resistance Observer for salient pmsm drives design and stability analysis
IEEE Transactions on Power Electronics, 2012Co-Authors: Marko Hinkkanen, Lennart Harnefors, Toni Tuovinen, J LuomiAbstract:A reduced-order position Observer with stator-resistance adaptation is proposed for motion-sensorless permanent-magnet synchronous motor drives. A general analytical solution for the stabilizing Observer Gain and stability conditions for the stator-resistance adaptation are derived. Under these conditions, the local stability of the position and stator-resistance estimation is guaranteed at every operating point except the zero frequency, if other motor parameters are known. Furthermore, the effect of inaccurate model parameters on the local stability of the position estimation is studied, and an Observer Gain design that makes the Observer robust is proposed. The proposed Observer is experimentally tested using a 2.2-kW motor drive; stable operation at very low speeds under different loading conditions is demonstrated.
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reduced order flux Observers with stator resistance adaptation for speed sensorless induction motor drives
Energy Conversion Congress and Exposition, 2009Co-Authors: Marko Hinkkanen, Lennart Harnefors, J LuomiAbstract:This paper deals with reduced-order flux Observers with stator-resistance adaptation for speed-sensorless induction motor drives. A general analytical solution for the stabilizing Observer Gain is given. The Gain has two free positive parameters (which may depend on the operating point), whose selection significantly affects the damping, convergence rate, robustness, and other properties of the Observer. The general stability conditions for the stator-resistance adaptation are derived. An Observer design is proposed that yields a robust and well-damped system and requires a minimal amount of tuning work. The proposed Observer design is experimentally tested using a 45-kW induction motor drive; stable operation at very low speeds under different loading conditions is demonstrated.
