A nonlinear optimal control approach for underactuated power-line inspection robots

Robotica ◽  
2021 ◽  
pp. 1-31
Author(s):  
Gerasimos Rigatos ◽  
Nikolaos Zervos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh ◽  
Jorge Pomares ◽  
...  
Keyword(s):  
Optimal Control ◽  
Global Stability ◽  
Control Method ◽  
Nonlinear Dynamical Systems ◽  
Nonlinear Optimal Control ◽  
Power Line ◽  
Robotic Systems ◽  
Time Step ◽  
Control Approach ◽  
Inspection Robots

Abstract The article proposes a nonlinear optimal (H-infinity) control approach for a type of underactuated power-line inspection robots. To implement this control scheme, the state-space model of the power-line inspection robots 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 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. The significance of the article’s results is outlined in the following: (i) the proposed control method is suitable for treating underactuated robotic systems and in general nonlinear dynamical systems with control inputs gain matrices which are in a nonquadratic form, (ii) by achieving stabilization of the power-line inspection robots in underactuation conditions the proposed control method ensures the reliable functioning of these robotic systems in the case of actuators’ failures or enables the complete removal of certain actuators and the reduction of the weight of these robotic systems, (iii) the proposed control method offers a solution to the nonlinear optimal control problem which is of proven global stability while also remaining computationally tractable, (iv) the proposed nonlinear optimal control method retains the advantages of linear optimal control that is fast and accurate tracking of reference setpoints under moderate variations of the control inputs, and (v) by minimizing the amount of energy that is dispersed by the actuators of the power-line inspection robots the proposed control method improves the autonomy and operational capacity of such robotic systems.

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.

scholarly journals A nonlinear optimal control approach for the UAV and suspended payload system

2021 ◽  
pp. 27-39
Author(s):  
Gerasimos G. Rigatos
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
State Space Model ◽  
Taylor Series Expansion ◽  
Nonlinear Optimal Control ◽  
Algebraic Riccati Equation ◽  
State Variables ◽  
Time Step ◽  
Control Approach ◽  
Optimal Control Approach

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.

A Nonlinear Optimal Control Approach for Multi-DOF Brachiation Robots

2021 ◽  
Author(s):  
G. Rigatos ◽  
M. Abbaszadeh ◽  
K. Busawon ◽  
Z. Gao ◽  
J. Pomares
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
State Space ◽  
Control Method ◽  
State Space Model ◽  
Nonlinear Optimal Control ◽  
Time Step ◽  
Control Approach ◽  
Space Model ◽  
Optimal Control Approach

This paper proposes a nonlinear optimal control approach for mulitple degrees of freedom (DOF) brachiation robots, which are often used in inspection and maintenance tasks of the electric power grid. Because of the nonlinear and multivariable structure of the related state-space model, as well as because of underactuation, the control problem of these robots is nontrivial. The dynamic model of the brachiation robots undergoes first 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 Jacobian matrices of the brachiation robots’ state-space model. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the brachiation robots, 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 global stability properties of the control scheme are proven through Lyapunov analysis. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the brachiation robots, under moderate variations of the control inputs.

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.

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.

scholarly journals A Nonlinear Optimal Control Approach for a Lower-Limb Robotic Exoskeleton

2020 ◽  
Vol 17 (05) ◽  
pp. 2050018
Author(s):  
G. Rigatos ◽  
M. Abbaszadeh ◽  
J. Pomares ◽  
P. Wira
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Lower Limb ◽  
Nonlinear Optimal Control ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
H Infinity ◽  
Control Approach ◽  
Robotic Exoskeleton ◽  
Optimal Control Approach

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.

scholarly journals Production and process management: An optimal control approach

2016 ◽  
Vol 26 (3) ◽  
pp. 331-342 ◽  
Author(s):  
Haider Biswas ◽  
Ahad Ali
Keyword(s):  
Optimal Control ◽  
Process Management ◽  
Nonlinear Dynamical Systems ◽  
State Constraint ◽  
Control Technique ◽  
Optimal Control Strategy ◽  
Nonlinear Dynamical ◽  
Control Approach ◽  
Time Operation ◽  
Operation Process

Optimal control and efficient management of industrial products are the key for sustainable development in industrial and process engineering. It is well-known that proper maintenance of process performance, ensuring the quality products after a long time operation of the system, is desirable in any industry. Nonlinear dynamical systems may play crucial role to appropriately design the model and obtain optimal control strategy in production and process management. This paper deals with a mathematical model in terms of ordinary differential equations (ODEs) that describe control of production and process arising in industrial engineering. The optimal control technique in the form of maximum principle, used to control the quality products in the operation processes, is applied to analyze the model. It is shown that the introduction of state constraint can be advantageous for obtaining good products during the longer operation process. We investigate the model numerically, using some known nonlinear optimal control solvers, and we present the simulation results to illustrate the significance of introducing state constraint onto the dynamics of the model.

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