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

Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh

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.

2018 ◽  
Vol 188 ◽  
pp. 05007 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Krishna Busawon ◽  
Dimitrios Serpanos ◽  
Vasilios Siadimas ◽  
Pierluigi Siano ◽  
...  

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,


Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh

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.


2019 ◽  
Vol 9 (1) ◽  
pp. 14-27 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Sul Ademi

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.


2020 ◽  
Vol 08 (01) ◽  
pp. 49-69 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Patrice Wira ◽  
Krishna Busawon ◽  
Richard Binns

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.


Robotica ◽  
2019 ◽  
Vol 38 (1) ◽  
pp. 29-47 ◽  
Author(s):  
G. Rigatos ◽  
K. Busawon ◽  
J. Pomares ◽  
M. Abbaszadeh

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.


2017 ◽  
Vol 40 (7) ◽  
pp. 2364-2377 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh

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.


2021 ◽  
pp. 27-39
Author(s):  
Gerasimos G. Rigatos

The article proposes a nonlinear optimal control approach for the UAV and suspended load system. The dynamic model of the UAV and payload system undergoes approximate linearization with the use of Taylor series expansion around a temporary operating point which 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 system. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the UAV and payload system, 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 UAV and payload system, under moderate variations of the control inputs. The stability properties of the control scheme are proven through Lyapunov analysis.


2021 ◽  
pp. 2150012
Author(s):  
G. Rigatos

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.


2020 ◽  
Vol 17 (05) ◽  
pp. 2050018
Author(s):  
G. Rigatos ◽  
M. Abbaszadeh ◽  
J. Pomares ◽  
P. Wira

The use of robotic limb exoskeletons is growing fast either for rehabilitation purposes or in an aim to enhance human ability for lifting heavy objects or for walking for long distances without fatigue. The paper proposes a nonlinear optimal control approach for a lower-limb robotic exoskeleton. The method has been successfully tested so far on the control problem of several types of robotic manipulators and this paper shows that it can also provide an optimal solution to the control problem of limb robotic exoskeletons. To implement this control scheme, the state-space model of the lower-limb robotic exoskeleton undergoes first approximate linearization around a temporary operating point, through first-order Taylor series expansion and through the computation of the associated Jacobian matrices. To select the feedback gains of the H-infinity controller an algebraic Riccati equation is solved at each time-step of the control method. The global stability properties of the control loop are proven through Lyapunov analysis. Finally, to implement state estimation-based feedback control, the H-infinity Kalman Filter is used as a robust state estimator.


Author(s):  
Mahmoud Zadehbagheri ◽  
Mehrdad Pishavaie ◽  
Rahim Ildarabadi ◽  
Tole Sutikno

<span>This paper presents a new resistant control method for synchronized connection of FACTS &amp; HVDC aiming to get the stability of small signal of the power system. The efficiency of the proposed controller on the stability of the entire tested system has been proved and also guarantees the stability against uncertainty and turmoil. Applying this method can also reduce the difficulties of oscillations between adjacent areas to generator without strengthening transmission lines or costly constraints on system performance. The simulation results on a system of 68 buses, 16 generators and 5 areas show that the mentioned controller with embedded HVDC and SVC has significant performance despite changes in parameters.</span>


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