Adaptive Model Predictive Control for Nonlinear Elastic Electrical Transmission Servo Drives

Phuong, Tran Huu; Belov, Mikhail P.; Thuy, Doan Van

doi:10.1109/eiconrus.2019.8656891

Cited by 9 publications

(4 citation statements)

References 4 publications

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“…40 Instead of applying only the first control entry Δu(k + 0) at the current time step k and repeating the optimization process for next time step k + 1, a control horizon of N c ≤ N is chosen so that the first N c control entries [u(k + 0), u(k + 1), …, u(k + N c À 1)] are used between current time step k and time step k + N c À 1. Subsequently, the optimization process is repeated at time 41…”

Section: R ðN þ1þnx×nnumentioning

confidence: 99%

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Linear parameter-varying-based transition flight control design for a tilt-rotor aircraft

Zhu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents the development of novel transition flight controllers for a class of urban air mobility aircrafts configured with a fixed-wing and six distributed electric rotor assemblies. Only the two tilt-rotors are utilized for thrust vectoring during transition flight from hovering to steady-level flight, while the four lift-rotors are modulated with aerodynamic lift induced by fixed-wing to maintain stable altitude-hold. Three tractable tilt-rotor articulation profiles are proposed by taking into account of various aircraft and hardware constraints. Given a predefined nominal tilting profile, a family of linear models is obtained by linearizing the nonlinear aircraft model at multiple tilt-rotor angular positions along the tilting profile. Using tilt-rotor angular position as a scheduling parameter, a discrete-time linear parameter-varying model can be constructed, which is then used to develop a novel transition flight control architecture that integrates the adaptive model predictive control law with feedforward effect of the dynamic reference compensation. The simulation results demonstrate the effectiveness of proposed transition flight controllers and its robustness subject to external disturbance.

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Section: R ðN þ1þnx×nnumentioning

confidence: 99%

“…Subsequently, the optimization process is repeated at time step k + N c − 1 to solve for the next control effort [ u ( k + N c ), u ( k + N c + 1), …, u ( k + 2 N c − 1)]. 41…”

Section: Adaptive Mpc-drc For Lpv Systemsmentioning

confidence: 99%

Linear parameter-varying-based transition flight control design for a tilt-rotor aircraft

Zhu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

show abstract

“…Instead of only applying the first control entry at current time step k and repeating the whole optimization process at next time step k + 1, a control horizon of N c is defined, which means that the first N c control in trueu^(k) will be used as the control effort between the current sample time k and sample time k + N c − 1, followed with the new optimization process repeated at time k + N c − 1 to obtain the next control effort Δ u ( k + N c : k + 2 N c − 1); see Ref. 30 for details.…”

Section: Adaptive Mpc Controller Design Of Lpv Systemmentioning

confidence: 99%

Adaptive model predictive control of a six-rotor electric vertical take-off and landing urban air mobility aircraft subject to motor failure during hovering

Zhu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part G:

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In this article, motor failure control of a six-rotor electric vertical take-off and landing (eVTOL) urban air mobility aircraft is investigated using adaptive model predictive control (MPC) based on the linear parameter-varying (LPV) model developed using the nonlinear rigid-body aircraft model. For capturing the aircraft dynamics under motor failure conditions, a family of linearized models are obtained by trimming the nonlinear aircraft model at multiple equilibrium conditions and the LPV model is obtained by linking the linear models using the failed rotor speed, where the system transition from healthy to failure is modeled by a scheduling parameter calculated based on failed rotor speed caused by available motor peak power after failure. The proposed adaptive MPC is developed to optimize the system output performance, including the rigid-body aircraft velocity and altitude, by using quadratic programming optimization with reference compensation subject to a set of time-varying constraints representing the current available propeller acceleration calculated based on the motor power. Simulation study is conducted based on the developed LPV control design and original nonlinear rigid-body model, and the simulation results demonstrate that the designed adaptive MPC controller is able to recover and maintain the aircraft at desired stable condition after motor failure.

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“…Ref. [14] presents an adaptive model predictive control to eliminate the effects of clearance and coulomb dry friction, which is proved to be correct in servo position tracking simulation. In [15], the influence of the backlash and friction is analyzed by a description function method and simulation.…”

Section: Introductionmentioning

confidence: 99%

A Precise Modeling Method for PMSM Servo System of Spacecraft

Xu,

Song,

Xiao

et al. 2024

Applied Sciences

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Permanent magnet synchronous motor (PMSM) servo system is the control and execution mechanism of spacecraft, and its precise modeling is of great practical significance for improving the performance of the spacecraft. A comprehensive model considering elasticity, backlash, and friction was established based on the structural composition and transmission characteristics of spacecraft. Firstly, an elastic-dead zone model was established based on the transmission characteristics, with two mass elastic and gear backlash dead zones as the main features. Then, an improved LuGre friction model was established that considers the effects of vibration and environmental temperature, and the three models were organically combined. Finally, a method for identifying nonlinear parameters of the system using sinusoidal sweep and the least squares method was proposed, and the accuracy of the constructed model was verified. The experiment shows that the error of the simulation results is consistent with the experimental results. This method can precisely obtain the servo system model, providing theoretical support for control method research.

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Adaptive Model Predictive Control for Nonlinear Elastic Electrical Transmission Servo Drives

Cited by 9 publications

References 4 publications

Linear parameter-varying-based transition flight control design for a tilt-rotor aircraft

Linear parameter-varying-based transition flight control design for a tilt-rotor aircraft

Adaptive model predictive control of a six-rotor electric vertical take-off and landing urban air mobility aircraft subject to motor failure during hovering

A Precise Modeling Method for PMSM Servo System of Spacecraft

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