This paper presents a non-model based control approach to reduce payload oscillations in hydraulic load handling machines. Hydraulic mobile machinery are subjected to different kinds of vibrations related to their actuation, which hamper productivity and safety. In particular, these oscillations can occur at the machine structure, at the operator cabin or at the payload. While several techniques have been proposed to specifically address the first two forms of vibrations, the problem of limiting payload oscillations has encountered less attention by researchers in the fluid power field. The particular control technique proposed in this work is pressure feedback, and utilizes pressure sensor which can be located in well protected areas of the hydraulic system of the machine. The control method is based on an online identification of the frequency of load oscillations and selectively reduces these oscillations by acting on the hydraulic actuators of the machine. With reference to a hydraulic crane installed at the authors’ research center, this paper details the methodology, particularly focusing on the technique utilized for the online identification of the nature of load oscillations. Experimental results are presented to show the effectiveness of the proposed method to reduce payload oscillations, and demonstrate its applicability for hydraulic load handling machines.
This paper presents an optimized control for independent metering hydraulic systems that integrates machine diagnostic features. The machine under study is a hydraulic crane for truck applications equipped with a post compensated Load Sensing Pressure Compensated (LSPC) independent metering valve. Control challenges of such hydraulic system pertain to the determination of the opening of the meter-out section under overrunning load conditions. In this work, the inlet actuator pressure was used as feedback for a PI control architecture. The gains of the PI regulator were defined through an Extremum Seeking (ES) optimization algorithm, which minimizes cost functions representative of energy consumption and occurrence of cavitation, to achieve optimal performance in different operating conditions. The control was tested on a simulation model of the reference machine developed in AMESim and validated against experimental results. The paper shows that the same cost functions used to define the controller parameters can be used as additional inputs, along with conventional sensors, to monitor the health status of the machine.
Vibrations in load handling machines can manifest at different levels: at the structure of the machine directly connected to the hydraulic actuators; at the cabin of the machine; or — for machines carrying payload not rigidly connected to the structure — at the payload. These oscillations negatively affect productivity, safety and operator comfort. Several techniques have been proposed to smooth the operation of the mechanical arms of hydraulic machines, but limited attention was so far dedicated specifically to the oscillations of the payload. This paper introduces a frequency-based approach to reduce payload oscillation applicable for load handling machines. The proposed controller generates proper signal to the flow control valves of the hydraulic system, on the basis on the frequency analysis of pressure sensors used as feedback. The controller is composed by a series of dynamic peak filters. A first stage of frequency transformation through the FFT identifies the payload frequency and adjusts the poles of the peak filter. Then, a modulation stage is used to select the proper harmonic suitable to quantify the payload oscillation. Another peak filter enables the generation of the control. This controller has a low computational cost and it is suitable for the implementation to industrial controllers. After describing the controller, the paper presents experimental results suitable to quantify the effectiveness of the proposed procedure, considering a particular truck mounting crane available at the authors’ research center.
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