Force tracking control for active suspensions-theory and experiments

Chantranuwathana, Supavut; Peng, Huei

doi:10.1109/cca.1999.806676

Cited by 22 publications

(16 citation statements)

References 11 publications

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“…References [16][17][18][19]). A solution is to use the ARC controller [10]. However, it is found from experience by the authors that the update law of the ARC controller usually gives diverging estimates in this force tracking application.…”

Section: Simulation and Experimental Resultsmentioning

confidence: 97%

“…In this section, the ARC and MARC techniques are applied to a force control problem for an active suspension system [10,15]. For the force control problem, the objective of the controller is to make the actual force follow the desired force generated by an outer-loop controller closely.…”

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…For details, please refer to Reference [10]. The ARC controller needs the signal ' F F d in its control law.…”

Section: Arc Controllermentioning

confidence: 99%

“…For a class of SISO nonlinear systems in a 'semi-strict' feedback form, assuming that bounds of parametric uncertainties are known, the ARC technique guarantees steady-state tracking accuracy and transient tracking accuracy (desirable properties of DRC) and allows asymptotic tracking at the absence of generalized uncertainties using only a continuous control law (a desirable property of AC). The ARC technique has a number of successful applications and general procedures for constructing ARC controllers can be found in several papers published in the late 1990s [1][2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Modular adaptive robust control of SISO nonlinear systems in a semi‐strict feedback form

Chantranuwathana

Peng

2004

Intl J Robust & Nonlinear

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SUMMARYIn this paper, a modular modification of the adaptive robust control (ARC) technique is presented. The modular design has all of the original ARC properties with an estimation-based update law instead of a Lyapunov-based update law. In this design, the controller is divided into two modules: a control module and an identification module. A key new idea is to set a priori bounds on the time derivatives of the estimates to be maintained by the update law. As a result, their effects on the system tracking accuracy can be dominated by the control law. A modification is proposed for the standard gradient and least-square update laws to guarantee the bounds. This modification also makes the controller robust against the generalized (unparameterized) uncertainties considered in the ARC formulation while allowing asymptotic output tracking without the generalized uncertainties. Both the ARC and the modular ARC techniques are applied to a force control problem for an active suspension system. Simulations and experimental results are provided to show that the update law of the modular design is less sensitive to measurement noise which results in smaller force tracking error and smaller control gain.

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Section: Simulation and Experimental Resultsmentioning

confidence: 97%

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…For details, please refer to Reference [10]. The ARC controller needs the signal ' F F d in its control law.…”

Section: Arc Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modular adaptive robust control of SISO nonlinear systems in a semi‐strict feedback form

Chantranuwathana

Peng

2004

Intl J Robust & Nonlinear

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“…Untuk model suspensi semi aktif dalam rangka memperkecil osilasi yang terjadi pada kendaraan, telah banyak usaha yang dilakukan para ahli dibidang otomotif seperti yang dilakukan oleh Supaput Chantranuwathana dan Huei Peng [1] Andrew Allyene [2]. Kihong Park dan Seung Jin Heo melakukan studi suspensi semi aktif model seperempat kenderaan dengan menerapkan beberapa model pengendalian redaman dengan fokus pada jenis jalan Bump.…”

Section: Pendahuluanunclassified

Sistem Identifikasi Hybrid Dengan Metode Arx Dan Fast Fourier Transform Pada Aplikasi Suspensi Semi Aktif Seperempat Kendaraan

Lysbetti¹,

Rajagukguk²

2010

MST

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AbstrakDalam permasalahan pada sistem pengontrolan, mekanisme sistem identifikasi merupakan suatu hal yang mutlak, khususnya pada kasus pengontrolan yang beradaptasi terhadap perubahan gangguan. Untuk itu dibutuhkan suatu metode identifikasi yang mampu mengidentifikasi perubahan gangguan pada sistem. Tujuan dari penelitian ini untuk memberikan alternatif dalam pengidentifikasian system yang bersifat gabungan antara ARX dan Fast Fourier Transform (FFT). Oleh karena itu, dibutuhkan suatu rancangan algoritma untuk proses identifikasi. Dalam hal ini, algoritma yang dirancang diwujudkan dalam suatu software yang bekerja berbasis Matlab. Hasil pengujian dengan massa mobil 500Kg pada waktu pencuplikan detik ketujuh, gangguan jalan pertama merupakan frekuensi terbesar yang terjadi pada saat ini. Besarnya frekuensi operasi 27,4889Hz, magnitude model estimasi = 1,3431E-006, dan phasa model estimasi = -86,8307. Hasil pengujian dengan massa mobil 1000Kg pada waktu pencuplikan detik kelimabelas, adalah gangguan jalan kedua merupakan frekuensi terbesar yang terjadi. Pada saat ini besarnya frekuensi operasi 3,9270Hz, besar magnitudo model estimasi= 1.1780E-006 dan phasa model estimasi = 131,5950. Hal ini menunjukkan semakin ringan massa kendaaran saat terjadi gangguan yang diakibatkan permukaan jalan, maka semakin besar frekuensi operasi yang terjadi. Abstract Hybrid Identification System with ARX and Fast Fourier Transform in Application of a Quarter of Vehicle HalfActive Suspension. In a control system problem, identification system mechanism is a absolute thing, especially in adaptation controlling to disturbance changing. For that case, is needed an identification method which can identify the changing of disturbance in that system. The aim of this research is to give an alternative in system/plant identification which is a combination (hybrid) of ARX and Fast Fourier Transform. So, it is needed an algorithm design for identification process. In this case, the designed algorithm will be implemented in software that works based on Matlab. The result of car mass 500Kg in seventh second with first way disturbance is the biggest frequency at this time. Operation frequency produced is 27.4889Hz, estimation model magnitude is 1.3431E-006 and estimation model phase is -86.8307. The result of car mass 1000Kg in 15 th -second, with second way disturbance is the biggest frequency at this time. Operation frequency produced is 3.9270Hz, estimation model magnitude is 1.1780E-006 and estimation model phase is 131,5950. These results show that as lighter car mass when disturbance happened by road surface, as bigger the operation frequency happen.

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Robust impedance control of a hydraulic suspension system

Fateh¹

2009

Intl J Robust & Nonlinear

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SUMMARYA novel robust impedance control approach is developed to control dynamic behavior of a vehicle subject to road disturbances. This behavior is predetermined as an impedance rule to achieve passenger comfort and vehicle handling by the use of a hydraulically actuated suspension system. Impedance control law is simple, free of model and efficient to apply for a broad range of road conditions. Moreover, it relates comfort to handling. This control approach can provide a desired comfort when passing a bump, and both desired comfort and handling after passing a bump. Robust position and force controls are used to implement the robust impedance control with the presence of uncertainties. A transformed proportional-integral-derivative control is proposed to perform the robust control. The system stability is analyzed and analytical results are confirmed by simulations. A quarter-car model of suspension system and a nonlinear model of hydraulic actuator are used to simulate the control system.

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Force tracking control for active suspensions-theory and experiments

Cited by 22 publications

References 11 publications

Modular adaptive robust control of SISO nonlinear systems in a semi‐strict feedback form

Modular adaptive robust control of SISO nonlinear systems in a semi‐strict feedback form

Sistem Identifikasi Hybrid Dengan Metode Arx Dan Fast Fourier Transform Pada Aplikasi Suspensi Semi Aktif Seperempat Kendaraan

Robust impedance control of a hydraulic suspension system

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