scholarly journals Gain-Scheduled Drive-based Damping Control for Industrial Robots

2021 ◽  
Author(s):  
Patrick Mesmer ◽  
Christoph Hinze ◽  
Armin Lechler ◽  
Alexander Verl
Keyword(s):  
Industrial Robot ◽  
Industrial Robots ◽  
Control Performance ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Damping Control ◽  
Dynamic Path ◽  
And Performance ◽  
And Control ◽  
Gain Scheduled

<p>The drivetrain flexibility of industrial robots limits their accuracy. To open up new areas of application for industrial robots, an increased dynamic path accuracy has to be obtained. Therefore, this paper addresses this issue by a gain-scheduled drive-based damping control for industrial robots with secondary encoders. For this purpose, a linear parameter-varying (LPV) model is derived as well as a system identification method is presented. Based on this, a gain-scheduled drive-based LPV damping control design is proposed, which guarantees stability and performance under variation of the manipulator configuration. The control performance of the approach is experimentally validated for the three base joints of a KUKA KR210-2 industrial robot. The approach realizes a trade-off between ease of implementation and control performance as well as robustness.</p>

scholarly journals Gain-Scheduled Drive-based Damping Control for Industrial Robots

2021 ◽  
Author(s):  
Patrick Mesmer ◽  
Christoph Hinze ◽  
Armin Lechler ◽  
Alexander Verl
Keyword(s):  
Industrial Robot ◽  
Industrial Robots ◽  
Control Performance ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Damping Control ◽  
Dynamic Path ◽  
And Performance ◽  
And Control ◽  
Gain Scheduled

<p>The drivetrain flexibility of industrial robots limits their accuracy. To open up new areas of application for industrial robots, an increased dynamic path accuracy has to be obtained. Therefore, this paper addresses this issue by a gain-scheduled drive-based damping control for industrial robots with secondary encoders. For this purpose, a linear parameter-varying (LPV) model is derived as well as a system identification method is presented. Based on this, a gain-scheduled drive-based LPV damping control design is proposed, which guarantees stability and performance under variation of the manipulator configuration. The control performance of the approach is experimentally validated for the three base joints of a KUKA KR210-2 industrial robot. The approach realizes a trade-off between ease of implementation and control performance as well as robustness.</p>

Open-Loop Control Co-Design of Floating Offshore Wind Turbines Using Linear Parameter-Varying Models

2021 ◽  
Author(s):  
Athul K. Sundarrajan ◽  
Yong Hoon Lee ◽  
James T. Allison ◽  
Daniel R. Herber
Keyword(s):  
Wind Turbines ◽  
Open Loop ◽  
Offshore Wind ◽  
Linear Parameter ◽  
Design Decisions ◽  
Linear Parameter Varying ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Parameter Varying ◽  
And Control

Abstract This paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines (FOWTs) in an integrated manner using linear parameter-varying models. Multiple linearized models derived from high-fidelity software are used to model the system in different operating regions characterized by the incoming wind speed. The combined model is then used to generate open-loop optimal control trajectories as part of a nested control co-design strategy that explores the system’s stability and power production in the context of crucial plant and control design decisions. A cost model is developed for the FOWT system, and the effect of plant decisions and subsequent power and stability response of the FOWT is quantified in terms of the levelized cost of energy (LCOE) for that system. The results show that the stability constraints and the plant design decisions affect the turbine’s power and, subsequently, LCOE of the system. The results indicate that a lighter plant in terms of mass can produce the same power for a lower LCOE while still satisfying the constraints.

scholarly journals A vibroacoustic application of modeling and control of linear parameter-varying systems

2010 ◽  
Vol 32 (4) ◽  
pp. 409-419 ◽  
Author(s):  
Jan De Caigny ◽  
Juan Francisco Camino ◽  
Ricardo C L F de Oliveira ◽  
Pedro Luis D Peres ◽  
Jan Swevers
Keyword(s):  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Modeling And Control ◽  
Linear Parameter Varying Systems ◽  
Parameter Varying ◽  
And Control

Experimental Study on an Electric Variable Valve Timing Actuator: Linear Parameter Varying Modeling and Control

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Ali Khudhair Al-Jiboory ◽  
Guoming G. Zhu ◽  
Shupeng Zhang
Keyword(s):  
System Identification ◽  
Engine Speed ◽  
Gain Scheduling ◽  
Variable Valve Timing ◽  
Linear Parameter ◽  
Valve Timing ◽  
Battery Voltage ◽  
Linear Parameter Varying ◽  
Variable Valve ◽  
And Control

This paper presents experimental investigation results of an electric variable valve timing (EVVT) actuator using linear parameter varying (LPV) system identification and control. For the LPV system identification, a number of local system identification tests were carried out to obtain a family of linear time-invariant (LTI) models at fixed engine speed and battery voltage. Using engine speed and battery voltage as time-varying scheduling parameters, the family of local LTI models is translated into a single LPV model. Then, a robust gain-scheduling (RGS) dynamic output-feedback (DOF) controller with guaranteed H∞ performance was synthesized and validated experimentally. In contrast to the vast majority of gain-scheduling literature, scheduling parameters are assumed to be polluted by measurement noises and the engine speed and battery voltage are modeled as noisy scheduling parameters. Experimental and simulation results show the effectiveness of the developed approach.

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