scholarly journals Nonlinear H-infinity control for switched reluctance machines

2019 ◽  
Vol 9 (1) ◽  
pp. 14-27 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Sul Ademi
Keyword(s):  
Control Algorithm ◽  
Control Method ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
H Infinity ◽  
Switched Reluctance ◽  
Reluctance Machine ◽  
Switched Reluctance Machines ◽  
H Infinity Control ◽  
Approximate Linearization

AbstractThe article proposes a nonlinear H-infinity control method for switched reluctance machines. The dynamic model of the switched reluctance machine undergoes approximate linearization round local operating points which are redefined at each iteration of the control algorithm. These temporary equilibria consist of the last value of the reluctance machine’s state vector and of the last value of the control signal that was exerted on it. For the approximate linearization of the reluctance machine’s dynamics, Taylor series expansion is performed through the computation of the associated Jacobian matrices. The modelling errors are compensated by the robustness of the control algorithm. Next, for the linearized equivalent model of the reluctance machine an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each time-step of the control method. It is shown that the control scheme achieves H-infinity tracking performance, which implies maximum robustness to modelling errors and external perturbations. The stability of the control loop is proven through Lyapunov analysis.

Nonlinear H-infinity control for 4-DOF underactuated overhead cranes

2017 ◽  
Vol 40 (7) ◽  
pp. 2364-2377 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh
Keyword(s):  
Control Algorithm ◽  
Control Method ◽  
Control Program ◽  
Algebraic Riccati Equation ◽  
Equivalent Model ◽  
Underactuated System ◽  
H Infinity ◽  
Overhead Cranes ◽  
H Infinity Control ◽  
Approximate Linearization

The article proposes a nonlinear H-infinity control method for four degrees of freedom underactuated overhead cranes. The crane’s system is underactuated because it receives only two external inputs, namely a force that allows the motion of the bridge along the x-axis and a force that allows the motion of the trolley along the y-axis. A solution to the control problem of this underactuated system is obtained by applying nonlinear H-infinity control. The dynamic model of the overhead crane undergoes approximate linearization round local operating points which are redefined at each iteration of the control algorithm. These temporary equilibria consist of the last value of the crane’s state vector and of the last value of the control signal that was exerted on it. For the approximate linearization of the system’s dynamics, a Taylor series expansion is performed through the computation of the associated Jacobian matrices. The modelling errors are compensated by the robustness of the control algorithm. Next, for the linearized equivalent model of the crane an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each iteration of the computer control program. It is shown that the control scheme achieves H-infinity tracking performance, which implies maximum robustness to modelling errors and external perturbations. The stability of the control loop is proven through Lyapunov analysis.

scholarly journals Nonlinear optimal control for ship propulsion with the use of an induction motor and a drivetrain

2018 ◽  
Vol 188 ◽  
pp. 05007 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Krishna Busawon ◽  
Dimitrios Serpanos ◽  
Vasilios Siadimas ◽  
Pierluigi Siano ◽  
...  
Keyword(s):  
Induction Motor ◽  
Control Method ◽  
Taylor Series Expansion ◽  
Propulsion System ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
H Infinity ◽  
H Infinity Control ◽  
Approximate Linearization ◽  
Linearized Model

A nonlinear optimal (H-infinity) control method is proposed for an electric ship's propulsion system that consists of an induction motor, a drivetrain and a propeller. The control method relies on approximate linearization of the propulsion system's dynamic model using Taylor-series expansion and on the computation of the state-space description's Jacobian matrices. The linearization takes place around a temporary equilibrium which is recomputed at each time-step of the control method. For the approximately linearized model of the ship's propulsion system, an H-infinity (optimal) feedback controller is developed. For the computation of the controller's gains an algebraic Riccati equation is solved at each iteration of the control algorithm.The stability properties of the control method are proven through Lyapunov analysis,

Nonlinear optimal control for ship propulsion systems comprising an induction motor and a drivetrain

2019 ◽  
Vol 234 (2) ◽  
pp. 409-425
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh
Keyword(s):  
Induction Motor ◽  
Control Method ◽  
Taylor Series Expansion ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
Propulsion Systems ◽  
H Infinity ◽  
Approximate Linearization ◽  
The Stability ◽  
Linearized Model

The article proposes a nonlinear optimal [Formula: see text] control method for electric ships’ propulsion systems comprising an induction motor, a drivetrain and a propeller. The control method relies on approximate linearization of the propulsion system’s dynamic model using Taylor series expansion and on the computation of the state-space description’s Jacobian matrices. The linearization takes place around a temporary operating point which is recomputed at each time-step of the control method. For the approximately linearized model of the ship’s propulsion system, an H-infinity (optimal) feedback controller is developed. For the computation of the controller’s gains, an algebraic Riccati equation is solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis.

scholarly journals A Nonlinear H-infinity Control Approach for Autonomous Truck and Trailer Systems

2020 ◽  
Vol 08 (01) ◽  
pp. 49-69 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Patrice Wira ◽  
Krishna Busawon ◽  
Richard Binns
Keyword(s):  
Autonomous Vehicles ◽  
Control Method ◽  
Kinematic Model ◽  
Taylor Series Expansion ◽  
Time Instant ◽  
Algebraic Riccati Equation ◽  
Control Loop ◽  
H Infinity ◽  
Control Approach ◽  
H Infinity Control

A nonlinear optimal control method is developed for autonomous truck and trailer systems. Actually, two cases are distinguished: (a) a truck and trailer system that is steered by the front wheels of its truck, (b) an autonomous fire-truck robot that is steered by both the front wheels of its truck and by the rear wheels of its trailer. The kinematic model of the autonomous vehicles undergoes linearization through Taylor series expansion. The linearization is computed at a temporary operating point that is defined at each time instant by the present value of the state vector and the last value of the control inputs vector. The linearization is based on the computation of Jacobian matrices. The modeling error due to approximate linearization is considered to be a perturbation that is compensated by the robustness of the control scheme. For the approximately linearized model of the autonomous vehicles an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. The stability of the control loop is confirmed through Lyapunov analysis. It is shown that the control loop exhibits the H-infinity tracking performance which implies elevated robustness against modeling errors and external disturbances. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven. Finally, to implement state estimation-based control for the autonomous vehicles, through the processing of a small number of sensor measurements, the H-infinity Kalman Filter is proposed.

Nonlinear optimal control for synchronization of distributed hydropower generators

2020 ◽  
pp. 014233122095003
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
Taylor Series Expansion ◽  
Nonlinear Optimal Control ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
H Infinity ◽  
Control Approach ◽  
Linearized Model

Synchronization of distributed hydropower units is necessary for ensuring the quality of the electric power produced by renewable sources. In this article, a nonlinear optimal control approach is proposed for stabilization and synchronization of distributed hydropower generators. The dynamic model of the interacting hydropower generation units undergoes approximate linearization with the use of first-order Taylor series expansion and the computation of the associated Jacobian matrices. The linearization point is updated at each time-step of the control method. For the approximately linearized model of the distributed hydropower system an H-infinity feedback controller is designed. This controller achieves solution of the related optimal control problem under model uncertainty and external perturbations. For the computation of the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, to achieve state estimation-based control for the system of the distributed hydropower generators the H-infinity Kalman Filter is used as a robust state estimator.

scholarly journals A New Control Method for Vibration and Noise Suppression in Switched Reluctance Machines

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1554 ◽  
Author(s):  
Man Zhang ◽  
Imen Bahri ◽  
Xavier Mininger ◽  
Cristina Vlad ◽  
Hongqin Xie ◽  
...  
Keyword(s):  
Control Strategy ◽  
Noise Suppression ◽  
Control Method ◽  
Negative Impact ◽  
Low Cost ◽  
Radial Force ◽  
Torque Control ◽  
Transient Condition ◽  
Switched Reluctance ◽  
Switched Reluctance Machines

Due to their inherent advantages such as low cost, robustness and wide speed range, switched reluctance machines (SRMs) have attracted great attention in electrical vehicles. However, the vibration and noise problems of SRMs limit their application in the automotive industry because of the negative impact on driver and passengers’ comfort. In this paper, a new control method is proposed to improve the vibratory and acoustic behavior of SRMs. Two additional control blocks —direct force control (DFC) and reference current adapter (RCA)—are introduced to the conventional control method (average torque control (ATC)) of SRM. DFC is adopted to control the radial force in the teeth of the stator, since the dynamic of the radial force has a large impact on the vibratory performance. RCA is proposed to handle the trade-off between the DFC and ATC. It produces an auto-tuning current reference to update the reference current automatically depending on the control requirement. The effectiveness of the proposed control strategy is verified by experimental results under both steady and transient condition. The results show that the proposed method improves the acoustic performance of the SRM and maintains the dynamic response of it, which proves the potential of the proposed control strategy.

A Nonlinear Optimal Control Approach for the Vertical Take-off and Landing Aircraft

2021 ◽  
pp. 2150012
Author(s):  
G. Rigatos
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
Nonlinear Optimal Control ◽  
The Body ◽  
Algebraic Riccati Equation ◽  
Control Input ◽  
Time Step ◽  
Control Approach ◽  
Vtol Aircraft ◽  
Optimal Control Approach

The paper proposes a nonlinear optimal control approach for the model of the vertical take-off and landing (VTOL) aircraft. This aerial drone receives as control input a directed thrust, as well as forces acting on its wing tips. The latter forces are not perpendicular to the body axis of the drone but are tilted by a small angle. The dynamic model of the VTOL undergoes approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the computation of the Jacobian matrices of the state-space model of the VTOL aircraft. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the aerial drone, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains, an algebraic Riccati equation is solved at each time-step of the control method. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the VTOL aircraft, under moderate variations of the control inputs. The stability properties of the control scheme are proven through Lyapunov analysis.

Nonlinear Optimal Control for the Wheeled Inverted Pendulum System

Robotica ◽  
2019 ◽  
Vol 38 (1) ◽  
pp. 29-47 ◽  
Author(s):  
G. Rigatos ◽  
K. Busawon ◽  
J. Pomares ◽  
M. Abbaszadeh
Keyword(s):  
Optimal Control ◽  
Inverted Pendulum ◽  
Control Method ◽  
Taylor Series Expansion ◽  
Nonlinear Optimal Control ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Wheeled Inverted Pendulum

SummaryThe article proposes a nonlinear optimal control method for the model of the wheeled inverted pendulum (WIP). This is a difficult control and robotics problem due to the system’s strong nonlinearities and due to its underactuation. First, the dynamic model of the WIP undergoes approximate linearization around a temporary operating point which is recomputed at each time step of the control method. The linearization procedure makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. For the linearized model of the wheeled pendulum, an optimal (H-infinity) feedback controller is developed. The controller’s gain is computed through the repetitive solution of an algebraic Riccati equation at each iteration of the control algorithm. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, by using the H-infinity Kalman Filter as a robust state estimator, the implementation of a state estimation-based control scheme becomes also possible.

Torque Optimization of Double-Stator Switched Reluctance Machine

2013 ◽  
Vol 313-314 ◽  
pp. 45-50 ◽  
Author(s):  
Mohammadali Abbasian ◽  
Vahid Hanaeinejad
Keyword(s):  
Finite Element ◽  
Acoustic Noise ◽  
Optimization Method ◽  
Torque Ripple ◽  
Radial Force ◽  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Torque Density ◽  
Reluctance Machine ◽  
Switched Reluctance Machines

Double-stator switched reluctance machines benefit from a high torque density and a low radial force level in comparison with conventional switched reluctance machines resulting in a lower vibration and acoustic noise. Therefore, they are suitable candidate for automotive applications. However, torque pulsation which is also a source for vibration is still remained and should be alleviate by dimension optimization of the machine. This paper presents a design optimization of a double-stator switched reluctance machine for improving the magnetic torque quality of the machine. For this purpose finite element method along with response surface methodology is used to optimize three parameters of the machine to maximize torque quality factor i.e. the average torque to torque ripple ratio in the machine. Genetic algorithm method is also employed as an optimization tool. The aim of optimization is to maximize the ratio of average torque to torque ripple. Finite element results are presented to verify the optimization method.

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