Nonlinear optimal control for the 4-DOF underactuated robotic tower crane
Abstract Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approxi...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2022-08-01
|
| Series: | Autonomous Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43684-022-00040-4 |
| _version_ | 1798004406487089152 |
|---|---|
| author | G. Rigatos M. Abbaszadeh J. Pomares |
| author_facet | G. Rigatos M. Abbaszadeh J. Pomares |
| author_sort | G. Rigatos |
| collection | DOAJ |
| description | Abstract Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control approach is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the article’s nonlinear optimal control scheme is of proven global stability and convergence to the optimum. |
| first_indexed | 2024-04-11T12:23:12Z |
| format | Article |
| id | doaj.art-fb6419b46e3d42a0bd77216089d43e1c |
| institution | Directory Open Access Journal |
| issn | 2730-616X |
| language | English |
| last_indexed | 2024-04-11T12:23:12Z |
| publishDate | 2022-08-01 |
| publisher | Springer |
| record_format | Article |
| series | Autonomous Intelligent Systems |
| spelling | doaj.art-fb6419b46e3d42a0bd77216089d43e1c2022-12-22T04:24:02ZengSpringerAutonomous Intelligent Systems2730-616X2022-08-012113010.1007/s43684-022-00040-4Nonlinear optimal control for the 4-DOF underactuated robotic tower craneG. Rigatos0M. Abbaszadeh1J. Pomares2Unit Industrial Automation, Industrial Systems InstituteDept. ECS Engineering, Rensselaer Polytechnic Inst.Dept. of Systems Engineering, University of AlicanteAbstract Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control approach is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the article’s nonlinear optimal control scheme is of proven global stability and convergence to the optimum.https://doi.org/10.1007/s43684-022-00040-4Tower cranesUnderactuated robotic manipulators4-DOF robotic tower craneNonlinear H-infinity controlTaylor series expansionJacobian matrices |
| spellingShingle | G. Rigatos M. Abbaszadeh J. Pomares Nonlinear optimal control for the 4-DOF underactuated robotic tower crane Autonomous Intelligent Systems Tower cranes Underactuated robotic manipulators 4-DOF robotic tower crane Nonlinear H-infinity control Taylor series expansion Jacobian matrices |
| title | Nonlinear optimal control for the 4-DOF underactuated robotic tower crane |
| title_full | Nonlinear optimal control for the 4-DOF underactuated robotic tower crane |
| title_fullStr | Nonlinear optimal control for the 4-DOF underactuated robotic tower crane |
| title_full_unstemmed | Nonlinear optimal control for the 4-DOF underactuated robotic tower crane |
| title_short | Nonlinear optimal control for the 4-DOF underactuated robotic tower crane |
| title_sort | nonlinear optimal control for the 4 dof underactuated robotic tower crane |
| topic | Tower cranes Underactuated robotic manipulators 4-DOF robotic tower crane Nonlinear H-infinity control Taylor series expansion Jacobian matrices |
| url | https://doi.org/10.1007/s43684-022-00040-4 |
| work_keys_str_mv | AT grigatos nonlinearoptimalcontrolforthe4dofunderactuatedrobotictowercrane AT mabbaszadeh nonlinearoptimalcontrolforthe4dofunderactuatedrobotictowercrane AT jpomares nonlinearoptimalcontrolforthe4dofunderactuatedrobotictowercrane |