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A comparative study of the recursive least squares and fuzzy logic estimation methods for the measurement of road adhesion coefficient

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AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING 2023年第4期21卷 1230-1246页

作者： Qi, Gengxin Fan, Xiaobin Li, Hao Henan Polytech Univ Sch Mech & Power Engn Jiaozuo Henan Peoples R China

Vehicle active safety system is the hotspot of current research and development, and the road adhesion coefficient is one of the essential parameters in the development of automobile active safety system, which plays a pivotal role in automobile safety. To improve the real-time performance and accuracy of the road adhesion coefficient, this paper proposes different control methods and compares and analyzes them. To accurately estimate the road adhesion coefficient in real-time, an eight-degree-of-freedom vehicle model was adopted in this paper. According to the tire torque and wheel speed, the adhesion coefficient was estimated based on the second-order nonlinear extended state observer. The experimental data, such as slip rate, using the improved tire model, is based on the recursive least squares method with forgetting factor and fuzzy logic algorithm real-time of tire-road friction coefficient estimation. The results show that the observer can effectively observe utilisation adhesion coefficient, and both control algorithms can estimate the road adhesion coefficient in real-time, effectively and quickly. On different roads, the use of the recursive least squares algorithm resulted in higher estimation accuracy, better robustness, and better control effect than using a fuzzy logic algorithm.

关键词： Road adhesion coefficient Vehicle active safety system Extended state observer Utilisation adhesion coefficient Recursive least squares method fuzzy logic algorithm

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A fuzzy logic Approach on the Evaluation of Driving Styles and Investigation of Drivability Calibration Effects

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GAZI UNIVERSITY JOURNAL OF SCIENCE 2022年第2期35卷 668-680页

作者： Aksit, Samet Yavuz, Akif Sen, Osman Taha AVL Turkey Res & Engn TR-34885 Istanbul Turkey Istanbul Tech Univ Fac Mech Engn TR-34437 Istanbul Turkey

Increased customer expectations lead the automobile manufacturers to develop innovative solutions, such as mode selection functions that provide different performance and comfort settings for the drivers. Almost all brands have different types of driving modes installed on their vehicles, such as sport mode, economy mode, off-road mode, etc. In the current technology, the mode selection is manually done by the driver. Thus, no effort is taken to match the driver style with available driving modes. However, driving mode selection should be done through an intelligent system such as vehicle control unit, in order to optimize customer expectations related to vehicle performance, driving comfort, and fuel consumption. This can be achieved by the analysis of all drivability maneuvers during any driving cycle. Based on the results of these analyses, drivability calibration settings of the vehicle can be adjusted depending on driver behaviors. In addition, fuel consumption can be improved using suitable calibration for each driver type. In this study, an experimental investigation is carried out in which vehicle data is collected for eleven different drivers at three different drivability calibrations. Furthermore, fuzzy logic algorithms are utilized in order to distinguish the driver characteristics. First, data from nine drivers are used in order to train the fuzzy logic approach. Then, the trained fuzzy logic scheme is used to assess the characteristics of two other drivers, who were left out in the training data set. Hence, it is aimed to obtain an intelligent prediction procedure that can estimate the characteristics of a driver based on their driving styles.

关键词： Drivability calibration fuzzy logic algorithm Driver classification

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Grey-based fuzzy algorithm for the optimization of the ball burnishing process

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MATERIALS TESTING 2015年第7-8期57卷 666-673页

作者： Esme, Ugur Kulekci, Mustafa Kemal Ustun, Deniz Kahraman, Funda Kazancoglu, Yigit Mersin Univ Tarsus Technol Fac Dept Automot Engn TR-33400 Tarsus Mersin Turkey Mersin Univ Fac Tarsus Technol Engn Dept Automot Engn TR-33400 Tarsus Mersin Turkey Mersin Univ Elect & Elect Engn TR-33400 Tarsus Mersin Turkey Mersin Univ Dept Mechantron Engn Tarsus Technol Fac TR-33400 Tarsus Mersin Turkey Izmir Univ Econ Dept Business Adm Izmir Turkey

In the present study, Grey based fuzzy algorithm was used for the optimization of complex multiple performance characteristics of the ball burnishing process. Experiments have been planned according to Taguchi's L-16 orthogonal design matrix. Burnishing force, number of passes, feed rate and burnishing speed were selected as input parameters, whereas surface roughness and microhardness were selected as output responses. Using Grey relation analysis (GRA), Grey relational coefficient (GRC) and Grey relation grade (GRG) were obtained. Then, Grey-based fuzzy algorithm was applied to obtain Grey fuzzy reasoning grade (GFRG). Analysis of variance (ANOVA) was carried out to find the significance and contribution of parameters on multiple performance characteristics. Finally, a confirmation test was applied at the optimum level of GFRG to validate the results. The results also show the feasibility of the Grey-based fuzzy algorithm for continuous improvement in product quality in complex manufacturing processes.

关键词： Grey relation analysis fuzzy logic algorithm optimization burnishing process

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Study of Aircraft Icing Warning algorithm Based on Millimeter Wave Radar

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Journal of Meteorological Research 2017年第6期31卷 1034-1044页

作者： Jinhu WANG Junxiang GE Qilin ZHANG Pan FAN Ming WEI Xiangchao LI Collaborative Innovation Center on Forecast and Evaluation of MeteorologicalDisasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science&TechnologyNanjing 210044 Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science&TechnologyNanjing 210044 Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science&TechnologyNanjing 210044 National Demonstration Center for Experimental Atmospheric Science and Environmental Meteorology Education Nanjing University of information Science&TechnologyNanjing 210044

In order to avoid accidents due to aircraft icing, an algorithm for identifying supercooled water was studied. Specifically, a threshold method based on millimeter wave radar, lidar, and radiosonde was used to retrieve the coverage area of supercooled water and a fuzzy logic algorithm was used to classify the observed meteorological targets. The macrophysical characteristics of supercooled water could be accurately identified by combing the threshold method with the fuzzy logic algorithm. In order to acquire microphysical characteristics of supercooled water in a mixed phase, the unimodal spectral distribution of supercooled water was extracted from a bimodal or trimodal spectral distribution of a mixed phase cloud, which was then used to retrieve the effective radius and liquid water content of supercooled water by using an empirical formula. These retrieved macro- and micro-physical characteristics of supercooled water can be used to guide aircrafts during takeoff, flight, and landing to avoid dangerous areas.

关键词： supercooled water aircraft icing millimeter wave radar threshold method fuzzy logic algorithm power spectral density

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An improved analogy-rule based software effort estimation using HTRR-RNN in software project management

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 251卷

作者： Kumar, K. Harish Srinivas, K. Koneru Lakshmaiah Educ Fdn Deemed be Univ Dept Comp Sci & Engn Hyderabad 500075 India Mahatma Gandhi Univ Dept Comp Sci & Informat Nalgonda 508254 Telangana India

To complete a software project, the most realistic effort required is predicted by the process called Software Effort Estimation (SEE). Effort Estimation (EE) in software development is considered a complicated task owing to the variability of variables. Thus, numerous Software Development EE (SDEE) models have been developed;nevertheless, these models ' accuracy rates are not good enough, and the variations among software functionalities were not focused for SEE. Therefore, by considering it as the research gap in Software Project Management (SPM), an enhanced analogy-rule-centric SEE utilizing Hyperbolic Tangent Recurrent Radial - Recurrent Neural Networks (HTRR-RNN) algorithm is proposed in this work. Initially, regarding the project size, the projects are partitioned. Next, the highly vital features are extracted as of the separated projects. By employing Levy FlightRock Hyraxes Swarm (LH-RHS) optimization, the selective quantity of features is chosen from the extracted features. By deploying the Mamdani Method - fuzzy (MM-fuzzy) algorithm, the rules are created regarding the selected features. Lastly, the number of efforts needed for the software development process is determined by the classification algorithm regarding the rules being created. COCOMO81, MAXWELL, and China are the openly accessible datasets utilized in this methodology. Then, the proposed method ' s results are contrasted with the prevailing algorithms. As per the experimental results, the proposed methodology performs SEE with a better accuracy rate;thus, it surpassed the other existing methodologies.

关键词： Software Effort Estimation Recurrent neural network fuzzy logic algorithm Mamdani method Rock hyraxes swarm optimization

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Optimal μ-Estimation-Based Regenerative Braking Strategy for an AWD HEV

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IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION 2017年第1期3卷 249-258页

作者： Paul, Deepak Velenis, Efstathios Cao, Dongpu Dobo, Tamas Cranfield Univ Ctr Automot Engn Sch Transportat & Management Cranfield MK43 0AL Beds England Jaguar Land Rover Ltd Coventry CV4 4LF W Midlands England

Braking force distribution (BFD) for electrified vehicles with the aim of maximizing energy regeneration has been a challenging research topic, due to the complex operating conditions and tradeoff among different vehicle performance measures. It is known that the level of tire-road friction has a significant impact on the braking force boundaries that define the locking conditions of front and rear wheels, and therefore, on the allowable set of BFD's where the vehicle's stability and controllability are maintained. However, previously developed BFD strategies for regenerative braking have not considered the changing boundaries of braking limits due to varying tireroad friction levels and introduce conservative BFD constraints to ensure stability and controllability. This paper proposes a BFD strategy for an all-wheel-drive electrified vehicle with a single electric motor, based on the estimation of the tire-road friction coefficient (mu) using a fuzzy logic estimation approach. The proposed strategy takes into consideration the motor efficiency and available speed reduction ratios in order to find the optimal BFD, which maximizes the regenerative power during braking, for a given vehicle speed and deceleration demand. Simulation analyses demonstrate the effectiveness of the proposed tireroad friction estimation-based BFD optimization strategy that significantly improves braking energy recovery. Preliminary test results with a prototype vehicle provide additional validation of the benefits of the proposed method.

关键词： Braking force distribution (BFD) electrified vehicles fuzzy logic algorithm regenerative braking tire-road friction estimation

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Compensating time delay in semi-active control of a SDOF structure with MR damper using predictive control

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STRUCTURAL ENGINEERING AND MECHANICS 2022年第4期82卷 445-458页

作者： Bathaei, Akbar Zahrai, Seyed Mehdi Univ Tehran Coll Engn Sch Civil Engn POB 11155-4563 Tehran Iran Univ Ottawa Dept Civil Engn Ottawa ON Canada

Some of the control systems used in engineering structures that use sensors and decision systems have some time delay reducing efficiency of the control system or even might make it unstable. In this research, in addition to considering the effect of the time delay in vibration control process, predictive control is used to compensate the time delay. A semi-active vibration control approach with the help of magneto-rheological dampers is implemented. In addition to using fuzzy inference system to determine the appropriate control voltage for MR damper, structural behavior prediction system and specifying future responses are also used such that the time delays occurring within control process are overcome. For this purpose, determination of prediction horizon is conducted for one, five, and ten steps ahead for single degree of freedom structures with periods ranging from 0.1 to 4 seconds, subjected to twenty earthquake excitations. The amount of time delay applied to the control system is 0.1 seconds. The obtained results indicate that for 0.1 second time delay, average prediction error values compared to the case without time delay is 3.47 percent. Having 0.1 second time delay in a semi-active control system reduces its efficiency by 11.46 percent;while after providing the control system with structure behavior prediction, the difference in the results for the control system without time delay is just 1.35 percent on average;indicating a 10.11 percent performance improvement for the control system.

关键词： fuzzy logic algorithm magneto-rheological damper predictive control semi-active control time delay

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Construction of Rotor/AMB dynamic model applied for TMP using self-tuning Kalman Filter

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MECHATRONICS 2014年第2期24卷 158-167页

作者： Liu, Yu-Hsun Tsai, Nan-Chyuan Chiu, Hsin-Lin Natl Cheng Kung Univ Dept Mech Engn Tainan 70101 Taiwan

The main goal of this research is to identify the system parameters of the dynamics of Rotor/Active Magnetic Bearing (Rotor/AMB) system employed in turbo molecular pumps (TMPs). The identification approach adopted in this work is based on experimental analysis and the application of fuzzy logic Adaptive Control-Extended Kalman Filter (FLAC-EKF). The estimation error for either system state or system parameters can be gradually converged to zero via self-tuning of the design parameters of FLAC-EKF. The proposed algorithm has been verified by numerical simulations and intensive experiments. It is concluded that the FLAC-EKF can exhibit satisfactory performance in terms of estimation accuracy on the system parameters even under contamination of a certain degree of process disturbance and sensor noise. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Active Magnetic Bearing System identification Kalman Filter fuzzy logic algorithm

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Vibration control of an eleven-story structure with MR and TMD dampers using MAC predictive control, considering nonlinear behavior and time delay in the control system

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STRUCTURES 2024年 60卷

作者： Bathaei, Akbar Zahrai, Seyed Mehdi Univ Tehran Sch Civil Engn Tehran Iran Univ Tehran Coll Engn Sch Civil Engn POB 11155-4563 Tehran Iran

In the last two decades, model predictive control has made significant progress in research and industrial process control. This achievement is through the high ability of model predictive control to solve industrial process control problems in the time domain. It is applicable in many control systems, such as delayed systems, univariate and multivariable systems, non-minimum phase systems, and unstable systems. This strategy is essentially for controlling delayed systems. It is possible to create a time delay in transmitting structure movement data in the systems that use sensors and receivers of sensor-recorded data, which is a factor to reduce the efficiency of the control system and even the instability of the structure. In this study, to investigate and compensate the effect of time delay in the hybrid vibration control system, an 11-story structure with a tuned mass damper and an MR damper was used by model algorithmic control (MAC) and nonlinear behavior of the structure in the control process. The linear and nonlinear structural models are created in OpenSEES, the control system in MATLAB;and the TCP/IP connection method was used to connect two programs. The fuzzy decision system is based on accelerating and decelerating movement. The structure has been subjected to seven earthquakes with maximum accelerations of 0.1 g to 1.0 g with an incremental step of 0.1 g. According to the results of incremental dynamic analysis, the average percentage of the fuzzy control system performance reduction, considering the time delay, is 15.28% and 38.57% for the maximum displacement and base shear in the linear structure, and 8.04% and 5.97% for the nonlinear structure, respectively. The assumed time delays have been effectively overcome using the model algorithmic control system (MAC), determining the prediction horizon of the structural behavior, and optimizing the control force in the control horizon. The performance of the MAC control system has been better than the fu

关键词： Hybrid control Model algorithmic control Nonlinear structure fuzzy logic algorithm Predictive control

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Position regulator for spindle of milling machine by embedded magnetic bearings

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JOURNAL OF INTELLIGENT MANUFACTURING 2011年第4期22卷 563-574页

作者： Tsai, Nan-Chyuan Shih, Li-Wen Lee, Rong-Mao Natl Cheng Kung Univ Dept Mech Engn Tainan 70101 Taiwan

The goal of this work is to concurrently counter-balance the dynamic cutting force and regulate the spindle position deviation by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm and an adaptive self-tuning feedback loop. The mathematic model for cutting dynamics is constructed by experiments so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm. Once the cutting force can be real-time estimated, the corresponding compensation force can be exerted by the equipped AMB to counter-balance the cutting force (i.e., via inner-loop), in addition to the spindle position regulation by the feedback of spindle position (i.e., via outer-loop). At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.

关键词： Active magnetic bearing Cutting process fuzzy logic algorithm

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