Stability-Guaranteed Force-Sensorless Contact Force/Motion Control of Heavy-Duty Hydraulic Manipulators

2015 ◽  
Vol 31 (4) ◽  
pp. 918-935 ◽  
Author(s):  
Janne Koivumaki ◽  
Jouni Mattila
Author(s):  
Jarmo Nurmi ◽  
Jouni Mattila

Hydraulic manipulators on mobile machines, whose hydraulic actuators are usually controlled by mobile hydraulic valves, are being considered for robotic closed-loop control. A feed-forward-based strategy combining position and velocity feedback has been found to be an effective method for the motion control of pressure-compensated mobile hydraulic valves that have a significant dead zone. The feed-forward can be manually identified. However, manually identifying the feed-forward models for each valve-actuator pair is often very time-consuming and error-prone. For this practical reason, we propose an automated feed-forward learning method based on velocity and position feedback. We present experimental results for a heavy-duty hydraulic manipulator on a forest forwarder to demonstrate the effectiveness of the proposed method. These results motivate the automated identification of velocity feed-forward models for motion control of heavy-duty hydraulic manipulators controlled by pressure-compensated mobile hydraulic valves that have a significant input dead zone.


Author(s):  
Janne Koivumäki ◽  
Jouni Mattila

In order to achieve higher energy efficiency for hydraulic systems the Load Sensing (LS) systems, i.e. a Variable Displacement Pump (VDP) with hydro-mechanical control system, can be considered as a state-of-the-art solution. However, as is well known, these traditional hydraulic LS-systems are usually characterized by difficulties in tuning, which can lead to system stability problems. In our previous studies, we have developed a high precision motion control for hydraulic manipulators with separate meter-in meter-out controlled hydraulic actuators. Our control approach was based on the Virtual Decomposition Control (VDC) approach that ensured high motion tracking performance while rigorously guaranteeing the system stability. In this paper, we propose both energy-efficient and high performance nonlinear model based motion control scheme that utilizes the developed servocontrolled Electric Load Sensing (ELS) system for hydraulic robotic manipulators. Experimental results are presented with the proposed ELS-controlled VDP and hydraulic manipulator lifting servoactuator that utilized a separate meter-in meter-out flow control scheme.


Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6566
Author(s):  
Konrad Johan Jensen ◽  
Morten Kjeld Ebbesen ◽  
Michael Rygaard Hansen

Self-contained hydraulic cylinders have gained popularity in the recent years but have not been implemented for high power articulated hydraulic manipulators. This paper presents a novel concept for an electro-hydrostatic actuator applicable to large hydraulic manipulators. The actuator is designed and analyzed to comply with requirements such as load holding, overload handling, and differential flow compensation. The system is analyzed during four quadrant operation to investigate energy efficiency and regenerative capabilities. Numerical simulation is carried out using path control and 2DOF anti-swing of a hydraulic crane as a load case to illustrate a real world scenario. A comparison with traditional valve-controlled actuators is conducted, showing significantly improved efficiency and with similar dynamic response, as well as the possibility for regenerating energy.


Machines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 57
Author(s):  
Lan Li ◽  
Ziying Lin ◽  
Yi Jiang ◽  
Cungui Yu ◽  
Jianyong Yao

In this paper, a novel nonlinear model and high-precision lifting motion control method of a hydraulic manipulator driven by a proportional valve are presented, with consideration of severe system nonlinearities, various uncertainties as well as valve backlash/deadzone input nonlinearities. To accomplish this mission, based on the independent valve orifice throttling process, a new comprehensive pressure-flow model is proposed to uniformly indicate both the backlash and deadzone effects on the flow characteristics. Furthermore, in the manipulator lifting dynamics, considering mechanism nonlinearity and utilizing a smooth LuGre friction model to describe the friction dynamics, a nonlinear state-space mathematical model of hydraulic manipulation system is then established. To suppress the adverse effects of severe nonlinearities and uncertainties in the system, a high precision adaptive robust control method is proposed via backstepping, in which a projection-type adaptive law in combination with a robust feedback term is conducted to attenuate various uncertainties and disturbances. Lyapunov stability analysis demonstrates that the proposed control scheme can acquire transient and steady-state close-loop stability, and the excellent tracking performance of the designed control law is verified by comparative simulation results.


1994 ◽  
Vol 116 (2) ◽  
pp. 232-240 ◽  
Author(s):  
N. Sepehri ◽  
P. D. Lawrence ◽  
F. Sassani ◽  
R. Frenette

This paper addresses the control problem for a class of heavy-duty hydraulic machines in order to achieve coordinated motion control of the implement. A model and sensor-based control algorithm is proposed which is applied in conjunction with closed-loop components. The algorithm is basically a feedforward load compensating scheme which uses the measured hydraulic line pressures along with the appropriate portion of the hydraulic model to control the joint velocities. The effects of nonlinear dynamic coupling between the links, loading, coupled actuation and power limitations are compensated in this technique. The closed-loop part consists of PD components. A knowledge of some hydraulic parameters is the only requirement of this control scheme. The proposed approach has been examined through simulation and is supported by experimental evidence. The experiments were performed on a Caterpillar 215B excavator. The control program is written in the C language, running on a computer system which is interfaced between the human operator and the machine.


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