Electric Power Steering System Control Strategy Based on Robust H<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:math> Control for Electric Forklift

Jiang, Zhizheng; Xiao, Biao

doi:10.1155/2018/7614304

Cited by 6 publications

(6 citation statements)

References 29 publications

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“…The vertical self-returning torque caused by the vertical force around the kingpin is shown in formula (7):…”

Section: Rack and Pinion Steering Gear And Return Torquementioning

confidence: 99%

“…Disturbance suppression methods are usually divided into two categories: one is passive anti-disturbance control, including robust control, and sliding mode control. Jiang 7 takes the EPS of an electric forklift as the research object and proposes a robust controller optimized by a genetic algorithm. The designed controller has an obvious suppression effect on external disturbance.…”

Section: Introductionmentioning

confidence: 99%

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Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Zheng,

Wei

2023

Measurement and Control

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In response to the influence of motor interference, damping, friction, and other uncertain factors on the operation of electric power steering systems under extreme working conditions, this study proposes a control strategy for electric power steering systems based on an active disturbance rejection algorithm. In ADRC, the fastest tracking differentiator is used to arrange the transition process for the target signal, and the extended state observer compensates for the total disturbance in the system. Phase compensation has been performed on the monitoring torque by using the torque differentiation method. The Simulink/Carsim simulation results show that ADRC has significantly improved anti-disturbance performance compared to PID and fuzzy PID. When using ADRC, the tracking accuracy of the assisted current is enhanced by 45.8%–75.8%, and the current adjustment time is reduced by 35.6%–61.7%. After phase compensation, the monitoring torque overshoot is reduced by 83.3%. Therefore, the proposed control strategy improves EPS’s robustness and steering feel.

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“…The vertical self-returning torque caused by the vertical force around the kingpin is shown in formula (7):…”

Section: Rack and Pinion Steering Gear And Return Torquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Zheng,

Wei

2023

Measurement and Control

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“…Jiang, Zhizheng et al proposed a Robust H-based forklift control algorithm [ 17 ] to model the dynamics of an electric power steering (EPS) system of an electric forklift. The standard H control model of the EPS system is transformed to derive the generalized equation of state for the EPS of an electric forklift.…”

Section: Related Work and Backgroundmentioning

confidence: 99%

Deep Learning-Based Intelligent Forklift Cargo Accurate Transfer System

Ren

Pan

Yao

et al. 2022

Sensors

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In this research, we present an intelligent forklift cargo precision transfer system to address the issue of poor pallet docking accuracy and low recognition rate when using current techniques. The technology is primarily used to automatically check if there is any pallet that need to be transported. The intelligent forklift is then sent to the area of the target pallet after being recognized. Images of the pallets are then collected using the forklift’s camera, and a deep learning-based recognition algorithm is used to calculate the precise position of the pallets. Finally, the forklift is controlled by a high-precision control algorithm to insert the pallet in the exact location. This system creatively introduces the small target detection into the pallet target recognition system, which greatly improves the recognition rate of the system. The application of Yolov5 into the pallet positional calculation makes the coverage and recognition accuracy of the algorithm improved. In comparison with the prior approach, this system’s identification rate and accuracy are substantially higher, and it requires fewer sensors and indications to help with deployment. We have collected a significant amount of real data in order to confirm the system’s viability and stability. Among them, the accuracy of pallet docking is evaluated 1000 times, and the inaccuracy is kept to a maximum of 6 mm. The recognition rate of pallet recognition is above 99.5% in 7 days of continuous trials.

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“…Owing to the rapid growth of small warehouse logistics, electric forklift buyers have become increasingly demanding in terms of their service requirements. For example, electric forklifts are now required to support online purchasing, online maintenance, and delayed scrapping, and this has intensified the competitiveness amongst forklift manufacturers [51,52]. To obtain a warehouse logistics solution that satisfies all CV and economic objectives in the initial design phase, forklift manufacturers must evaluate the CV and economic value of their warehouse logistics solutions within the design phase, and then select an optimal conceptual solution.…”

Section: Case Studymentioning

confidence: 99%

Conceptual Solution Decision Based on Rough Sets and Shapley Value for Product-Service System: Customer Value-Economic Objective Trade-Off Perspective

Feng

Jiang

et al. 2021

Applied Sciences

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The product service system (PSS), as a design concept for integrated products and services, needs to be evaluated in the early design stage to maximize the value for stakeholders of the PSS concept, which is a crucial task for enterprises. However, existing methods focus on the ranking and value assessment of PSS evaluation criteria (e.g., quality, sustainability, cost), ignoring the needs conflict between customer value and economic objectives in PSS design, resulting in decision results that are not applicable to industrial enterprises. Furthermore, the influence of weight preference and uncertain information on solution evaluation is seldom considered when calculating the weight of each criterion. To fill this gap, integrating rough sets and the Shapley value decision approach for product-service system design considering customer value-economic objective trade-off is proposed, which mainly includes two parts: firstly, the best worst method (BWM) and the entropy weight method are integrated to obtain the comprehensive weight of evaluation criteria in the customer value and economic objectives; secondly, the Shapley value method in the coalition game is used to solve the optimal expectation allocation of the two objectives, so as to select the solution closest to the allocation, i.e., the optimal solution. In addition, rough set techniques are used to capture and integrate subjective assessment information originating from DMs under uncertainty. Finally, a case study of the electric forklift design is illustrated to verify the proposed decision model. The decision results show that this approach is more reliable through sensitivity and comparison analysis, and provide a valuable recommendation for enterprises to consider product service in forklift design.

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Electric Power Steering System Control Strategy Based on Robust H∞ Control for Electric Forklift

Cited by 6 publications

References 29 publications

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Deep Learning-Based Intelligent Forklift Cargo Accurate Transfer System

Conceptual Solution Decision Based on Rough Sets and Shapley Value for Product-Service System: Customer Value-Economic Objective Trade-Off Perspective

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