مکانیک مواد پیشرفته و هوشمند
فصلنامه

طراحی کنترل‏گر فعال نیرو سیستم تعلیق صندلی راننده مجهز شده به میراگر هوشمند مگنتورئولوژیک

نوع مقاله : مقاله پژوهشی

نویسندگان

منا طهماسبی 1
محمد گهری 2
محمد مبارک آبادی 3

1 استادیار پژوهشی، بخش تحقیقات فنی و مهندسی کشاورزی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان مرکزی، سازمان تحقیقات، آموزش و ترویج کشاورزی، اراک، ایران

2 استادیار، گروه طراحی جامدات، دانشکده مهندسی مکانیک، دانشگاه صنعتی اراک، اراک، ایران

3 دانشجوی کارشناسی ارشد، گروه طراحی جامدات، دانشکده مهندسی مکانیک، دانشگاه صنعتی اراک، اراک، ایران

https://doi.org/10.52547/masm.1.2.175
چکیده
ارتعاشات انتقال‏یافته به بدن راننده در خودروهای غیر‏جاده‏ای سنگین که سیستم تعلیق اولیه ندارند باعث ایجاد مشکلات سلامتی در بلند مدت می‏گردد. معمولا در این‏گونه از وسایل‏نقلیه سیستم تعلیق ثانویه در صندلی راننده تعبیه می‏شود تا بتواند جداسازی ارتعاشی و جذب آن را انجام دهد و باعث جلوگیری از مشکلات سلامتی بخصوص در ستون فقرات شود. سیستم تعلیق غیرفعال صندلی به طور گسترده برای این منظور استفاده می‏شود، اما کارایی آنها پایین است. سیستم تعلیق صندلی فعال و سیستم تعلیق نیمه‏فعال عملکرد بهتری در جلوگیری از نوسانات ناخواسته دارند. یکی از میراگرهایی که اخیرا مورد توجه محققان قرار گرفته است میراگر نیمه‏فعال مجهز به سیال هوشمند مگنتورئولوژیک است که با ایجاد میدان مغناطیس گرانروی سیال تغییر می‏کند. بدین‏ترتیب سیستم تعلیق با استفاده کمی از جریان الکتریسیته می‏تواند با تغییر ضریب میرایی به‏صورت موثری انرژی ارتعاشی را مستهلک کند. در مقاله حاضر یک کنترل‏گر جدید هوشمند فعال نیرو مجهز به تخمین‏گر یادگیری تدریجی طراحی و شبیه‏سازی شده است. سیستم تعلیق به مدل ارتعاش بدن انسان کوپل شد و نتایج ارتعاش بدن راننده بدست آمد. نکته قابل توجه این است که کنترل فعال نیرو می‏تواند برای حذف اغتشاشات سرعت بالا نیز بکار رود. از آنجایی‏که ارتعاشات رخ داده در خودرو دارای سرعت تغییرات بالا هستند نتایج نشان داد که کنترل فعال نیرو مجهز به سامانه تخمین‏گر یادگیری تدریجی می‏تواند بطور موثری در کاهش ارتعاش انتقالی به راننده عمل کند بطوری‏که پیک‏های اول و دوم ارتعاش در حدود 60 درصد کاهش داشتند.

کلیدواژه‌ها

کنترل گر فعال نیرو
میراگر مگنتورئولوژیک
سیال هوشمند
الگوریتم یادگیری تدریجی
خودروی سنگین غیر‏جاده ای

عنوان مقاله English

Design of Active Force Controller for Off-Road Seat Suspension equipped to MR Damper

نویسندگان English

Mona Tahmasebi 1
mohammad gohari 2
mohammad mobarakabadi 3
1 Agricultural Engineering Research Department, Markazi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension, Organization (AREEO), Arak, Iran
2 Department of Mechanical Engineering, Arak University of Technology, Arak, Iran
3 Department of Mechanical Engineering, Arak University of Technology, Arak, Iran
چکیده English

Transmitted vibration to driver body (whole-body vibration) in heavy-duty Off-road vehicles without primary suspension leads to health problems in long term such as spine disorder, back pain, heart abnormal beating, vision disable, digestive problem, etc. Commonly, secondary seat suspension is used to isolate vibration and remove health problems, s especially in the spinal column. Passive seat suspension is widely employed for this purpose, but its efficiency is low. Active seat suspension and semi-active suspensions have better performance in blocking unwanted oscillation. Recently, semi-active magnetorheological dampers are focused on by researchers which can adjust their viscosity by electromagnetic flux. It is called smart fluid due to having controllable parameters such as damping ratio by electricity variations. Thus, suspension can dampen oscillation by low electricity current efficiently. The current paper introduces a novel active force control (AFC) equipped with an iterative learning estimator for seat suspension via MR damper. Results of simulations show that it can cancel vibration perfectly. The suspension was coupled to the human body vibration model, and the driver vibration results have been obtained. It is important to note that active force control can also be used to eliminate high-velocity disturbances. Since the vibrations that occur in the car have a high rate of change, the results indicated that active force control equipped with an iterative learning estimator system can be effective in reducing the transmission vibration to the driver so that the first and second vibration peaks was reduced by about 60%.

Methodology
At the first, a dynamic model of an off-road vehicle seat suspension which is equipped with an MR damper has been developed. After that, a PID controller has been designed for semi-active seat suspension. Next, the PID controller has been integrated into the AFC method. Lastly, utilizing the ILA in mass estimation for the AFC approach and simulation results of that has been discussed.
The simulation work has been developed employing MATLAB/Simulink software whereas passive suspension and semi-active suspension via the PID and AFCAIL controllers were simulated. To evaluate the performance of the control schemes, the seat suspension model was exposed to a number of various disturbances as road roughness listed as follows:
Results and Discussion
In this section, a comparison between passive suspension and all the control methods has been performed in time and frequency domains.
Conclusion

A novel controller called the active force control has been employed for vibration control of seat suspension equipped by a magnetorheological (MR) damper. The AFC method was integrated into the iterative learning algorithm to calculate the estimated mass of the system named AFC-IL . The designed controllers were simulated for the vibration canceling of an off-road vehicle seat suspension system. The AFC technique achieved to be uncomplicated in terms of calculation and change it suitable for real-time working conditions. Moreover, the AFC demonstrates high performance and produce robust and accurate response still in the presence of various disturbances. The simulation results express that for known parameters and situations, the proposed AFC-IL method efficiency enhanced in comparison to the popular PID controller. The results exemplify that the AFC-based scheme as an intelligent control technique has proper potential to eliminate the disturbances superiorly for the off-road vehicle seat suspension. Although complementary efforts should be accomplished to investigate the influences of other types of disturbances, parameters and uncertainties changes in real situations such as road trials. In continuing a test rig will be developed to evaluate the AFC scheme performance in real conditions in terms of the vibration attenuating and optimized parameters.

کلیدواژه‌ها English

Active Force control
Magnetorheological Damper
Smart Fluid
Iterative Learning Algorithm
Heavy Duty Off-Road Vehicle
[1] Frymoyer J W, Pope M H, Costanza M C, Rosen J C, Goggin J E, Wilder DG. Epidemiologic studies of lowback pain. Spine. 1980;5:419–423.
[2] Sandover J. Dynamic loading as a possible source of low-back disorders. Spine. 1983;8:652–658.
[3] Wilder D G, Woodworth B B, Frymoyer JW, Pope MH. Vibration and the human spine, Spine. 1982;7:243–254.
[4] Ahmadian M, Simon D E. An analytical and experimental evaluation of magneto-rheological suspensions for heavy trucks. Int J Veh Syst Dyn. 2003;37:38–49. [5] Ahmadian M. On the isolation properties of semiactive dampers. Journal of Vibration and Control. 1999;5(2):217-232.
[6] Ahmadian, M. Semiactive control of multiple degree of freedom systems. in Proceedings of the Sixteenth Biennial Conference on Mechanical Vibration, ASME Design Technical Conference, Sacramento, CA. 1997.
[7] Ahmadian M, Reichert B, Song X. Harmonic analysis of semiactive suspensions. Proceedings of the Sixteenth Biennial Conference on Mechanical Vibration, ASME Design Technical Conference, Sacramento, CA. 1997.
[8] Inman D J. Engineering Vibration, Prentice Hall, Englewood Cliffs, New Jersey. 1996.
[9] Tokhi M O, Hossain M A. Self-tuning active vibration control in flexible beam structures. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. 1994;208(4):263–278.
[10] Choi S B, Nam M H. Lee B K. Vibration Control of MR Seat Damper for Commercial Vehicles. Journal of Intelligent Material Systems and Structures. 2000;11(12):936–944.
[11] Carlson J D, Chrzan M J, Raleigh N C. Magnetorheological Fluid Damper. United States Patent No.5277281. 1994.
[12] Carlson J D, Weiss K D.. A Growing Attraction to Magnetic Fluids.Machine Design. 1994;61–66.
[13] Park C, Jeon D. Semiactive vibration control of a smart seat with an MR fluid damper considering its time delay. Journal of intelligent material systems and structures. 2002;13(7-8):521-524.
[14] Choi S B, Nam M H, Lee B K. Vibration control of a MR seatIntelligent Material Systems and Structures. 2000;11:936–944.
[15] Wang D H, Liao W H. Modeling and control of magnetorheological fluid dampers using neural networks. Smart Materials and Structures. 2005;14:111–126.
[16] Wang W Y, Chan M L, Hsu C C, Lee T T. H/sub/spl infin//tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 2002;32(4):483-492.
[17] Ali S F, Ramaswamy A. Hybrid structural control using magnetorheological dampers for base isolated structures. Smart Materials and Structure. 2009;18:055011.
[18] Do X P, Kruti S, Choi S B. Design of a new adaptive fuzzy controller and its implementation for the damping force control of a magnetorheological damper. Smart Materials and Structures. 2014;23:065012.
[19] Phu D X, Quoc N V, Park J H, Choi S B. (). Design of a novel adaptive fuzzy sliding mode controller and application for vibration control of magnetorheological mount. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 2014;228(13):2285-2302.
[20] Chang Y H, Chan W S. Adaptive dynamic surface control for uncertain nonlinear systems with interval type- 2 fuzzy neural networks. IEEE Transactions on Cybernetics. 2014;44(2):293–304.
[21] Do K S, Do X P, Choi S M, Choi S B. An adaptive fuzzy sliding mode control of magneto-rheological seat suspension with human body model. Journal of Intelligent Material Systems and Structures. 2016;27(7):925-934.
[22] Allen G. A critical look at biodynamic modeling in relation to specifications for human tolerance of vibration and shock. In Proceedings of AGRAD Conference. 1978.
[23] Spencer B F Jr., Dyke S J, Sain M K, Carlson J D. Phenomenological model for magnetorheological dampers. Journal of Engineering Mechanics. 1997;123:230–238.
[24] Wu C, Lin Y C, Hsu D S. Performance test and mathematical model simulation of MR damper. In The 14th World Conference on Earthquake Engineering. 2008;12-17.
[25] Mailah M, Hewit J R, Meeran S. Active force control applied to a rigid robot arm. Jurnal Mekanikal. 1996;2(2):52–68.
[26] Hewit J R, Burdess J S. Fast dynamic decoupled control for robotics using active force control. Transactions on Mechanism and Machine Theory. 1981;16(5):535–542.
[27] Mailah M, Priyandoko G. Simulation of a suspension system with adaptive fuzzy active force control. International Journal of Simulation Modelling. 2007;6:25–36.
[28] Jahanabadi H, Mailah M, Zain M M, Hooi H M. Active force with fuzzy logic control of a two-link arm driven by pneumatic artificial muscles. Journal of Bionic Engineering. 2011;8(4):474-484.
[29] Tahmasebi M, Rahman R A, Mailah M, Gohari M. Roll movement control of a spray boom structure using active force control with artificial neural network strategy. Journal of Low Frequency Noise, Vibration and Active Control. 2013;32(3):189–202.
[30] Tahmasebi M, Gohari M, Rahman R A, Mailah M. Self-tuning PD controller of a sprayer boom structure using neural network. 4th International Graduate Conference on Engineering, Science and Humanities. Universiti Teknologi Malaysia, Johor Bahru, Malaysia. 2013;16-17.
[31] Tahmasebi M, Rahman R A, Mailah M, Gohari M. Sprayer boom active suspension using intelligent active force control. Journal of World Academy of Science, Engineering and Technology. 2012;68:1277–1281.
[32] Kwek L C, Wong E K, Loo C K, Rao M V C. Application of active force control and iterative learning in a 5-link biped robot. Journal of Intelligent and Robotic Systems. 2003;37:143–162.
[33] Gohari M, Abd Rahman R, Raja R I, Tahmasebi M. Bus seat suspension modification for pregnant women. In 2012 International Conference on Biomedical Engineering (ICoBE). 2012;404-407. IEEE.
[34] Gohari M, Tahmasebi M. Active off-road seat suspension system using intelligent active force control. Journal of Low Frequency Noise, Vibration and Active Control. 2015;34(4):475-489.
[35] Gohari M, Tahmasebi M. Off-road vehicle seat suspension optimisation, Part II: Comparative study between meta-heuristic optimisation algorithms. Journal of Low Frequency Noise, Vibration and Active Control. 2014;33(4):443-454.
[36] Idres M S. Active Force Control on Active Suspension System (Doctoral dissertation, UMP). 2013.
[37] Rosli R, Mailah M, Priyandoko G. Active suspension system for passenger vehicle using active force control with iterative learning algorithm. WSEAS Trans. Syst. Control. 2014;9:120-129.
[38] Salim M A. Implementation of active force control to reduce vibration displacement in active mass damper during seismic activity. Journal of Instrument. 2011;2(1).
[39] Tahmasebi M, Gohari M, Mailah M, Abd Rahman R. Vibration suppression of sprayer boom structure using active torque control and iterative learning. Part II: Experimental implementation. Journal of Vibration and Control. 2018;24(20):4740-4750.
مکانیک مواد پیشرفته و هوشمند
دوره 1، شماره 2
زمستان 1400
صفحه 175-200

  • تاریخ دریافت 21 مهر 1400
  • تاریخ بازنگری 14 آذر 1400
  • تاریخ پذیرش 29 دی 1400

صفحه اصلی

راهنمای نویسندگان

ارسال مقاله

تماس با ما