Hydraulic load-sensitive systems (HLSS) are widely used for high power density and energy efficiency. This study introduces an adaptive, energy-efficient HLSS with a valve-controlled variable motor. The system faces challenges from non-linearities, including internal higher-order dynamics due to displacement changes and external unknown disturbances, which hinder precision applications. To address this issue, this study explores HLSS principles to develop an accurate system model. Subsequently, an adaptive robust motion control that considers displacement compensation (DCARC) is proposed using the established model. DCARC can learn unknown parameters online and compensate the model more accurately to improve control accuracy. Experiments show that considering the higher order dynamic effects caused by displacement in the system can improve model accuracy and effectively reduce the burden of parameter adaptation and robust feedback terms. High-precision and energy-efficient HLSS motion is verified and realized in the study. The control accuracy of DCARC is 19.4% higher than that of conventional adaptive robust control (ARC). Under experimental conditions, the proposed system can improve energy efficiency by up to five times compared to valve-controlled fixed displacement motor systems (VFDS).

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.isatra.2024.10.019DOI Listing

Publication Analysis

Top Keywords

adaptive robust
12
robust motion
8
motion control
8
energy efficiency
8
energy-efficient hlss
8
control accuracy
8
system improve
8
control
5
displacement
5
adaptive
4

Similar Publications

Mangrove-based carbon market projects: What stakeholders need to address during pre-feasibility assessment.

J Environ Manage

January 2025

Ecoresolve, San Francisco, CA, USA; Earth Observation Centre, Institute of Climate Change (IPI), Universiti Kebangsaan Malaysia, Bangi, 43600, Malaysia; Department of Civil Engineering, College of Engineering, American University of Sharjah (AUS), P.O. Box 26666, Sharjah, United Arab Emirates; Department of Geography, University of California-Berkeley, Berkeley, CA, 94709, USA. Electronic address:

Mangrove-based carbon market projects (MbCMP) aim to conserve, protect and restore mangrove habitats in order to generate high quality blue carbon credits via a crediting program, as a contribution to climate change mitigation/adaptation, biodiversity conservation, ecosystem services provision and local socio-economic development. The blue carbon credits generated are transferable, verifiable and sold through carbon markets to earn additional income for governments and local communities. The main aim of the paper is to provide important considerations for pre-field planning, that is, how challenges associated with fieldwork, project implementation, and monitoring reporting and verification (MRV) can be addressed with proper pre-field planning.

View Article and Find Full Text PDF

Background: The successful transition of stroke patients from hospital to home relies on the preparedness of caregivers. Assessing this preparedness is crucial, but existing tools need adaptation and validation for Iranian caregivers.

Objectives: This study aimed to translate, culturally adapt, and validate the Persian version of the "Preparedness Assessment for the Transition Home After Stroke" (PATH-s) for use among Iranian caregivers of stroke survivors.

View Article and Find Full Text PDF

Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival.

View Article and Find Full Text PDF

Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people.

View Article and Find Full Text PDF

WRKY transcription factors: Hubs for regulating plant growth and stress responses.

J Integr Plant Biol

January 2025

State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, 650500, China.

As sessile organisms, plants must directly face various stressors. Therefore, plants have evolved a powerful stress resistance system and can adjust their growth and development strategies appropriately in different stressful environments to adapt to complex and ever-changing conditions. Nevertheless, prioritizing defensive responses can hinder growth; this is a crucial factor for plant survival but is detrimental to crop production.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!