Robust two degree-of-freedom add-on controller design for automatic steering

Güvenç, Bilin Aksun; Güvenç, Levent

doi:10.1109/87.974347

Cited by 57 publications

(24 citation statements)

References 13 publications

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“…Note that the system (17) can be regarded as a perturbed system ofη = Aη 0η − a 0 Bρ(η 1 , τ σ ), which in turn can be regarded as a linear system with a time varying memoryless feedback, namelỹ η = Aη 0η + a 0 Bu † , y † = Cη, u † = −ρ(y † , τ σ ) (18) Note that y † (s)/u † (s) = G(s) where G(s) is given in (10). Moreover, ρ(η 1 , τ σ ) belongs to the sector [g − /ḡ, g + /ḡ] with respect toη 1 because ρ(0, τ σ ) = 0 and (9) and Assumption 3). Thus, with the coefficients of G(s) chosen in Section 3.1, the circle criterion [21] holds.…”

Section: Lemma 2: Let T > 0 and Suppose That Z(t) ∈ Z And [Z(t); X(t)mentioning

confidence: 97%

Reduced‐order implementation of disturbance observers for robust tracking of non‐linear systems

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Shim

2014

IET Control Theory & Applications

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The disturbance-observer-based control (DOBC) is a well-known robust control scheme and recently its non-linear version has been developed. Observing that two components (so-called Q-filters) in the conventional DOBC structure have the same transfer function, the authors propose a reduced-order DOBC for uncertain non-linear systems. It is shown that the proposed controller also guarantees the same robust transient response as those developed before. Numerical simulations using a magnetic levitation system are included to illustrate the detailed design procedure and validate the performance of the proposed controller.

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Section: Lemma 2: Let T > 0 and Suppose That Z(t) ∈ Z And [Z(t); X(t)mentioning

confidence: 97%

Reduced‐order implementation of disturbance observers for robust tracking of non‐linear systems

Back

Shim

2014

IET Control Theory & Applications

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“…The yaw stability controller used here is based on the model regulator architecture [6][7][8]. The block diagram of the model regulator based yaw stability controller is shown in Figure 5.…”

Section: Model Regulator Based Yaw Stability Controlmentioning

confidence: 99%

“…Tire side slip and longitudinal slip are computed as in reference [4] and used in the Dugoff tire model as [5] xi ICxis I f1C yi (8) The coefficientJ, in (8) is determined using…”

Section: Vehicle Models Usedmentioning

confidence: 99%

Robust Velocity Scheduled Yaw Stability Control of a Light Commercial Vehicle

Karaman

Oncui

Guiven

et al. 2006

2006 IEEE Intelligent Vehicles Symposium

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This paper is on the design and analysis of a velocity scheduled robust yaw stability controller for a light commercial vehicle. The considered light commercial vehicle is fitted with a proof-of-concept active steering system controlled by a separate generic electronic control unit. Single and double track models of the vehicle are used for controller design and simulation testing, respectively. A robust control method based on mapping frequency domain specifications into a chosen controller parameter plane is used. A toolbox with an interactive graphical user interface designed for this method is adapted for use with the model regulator architecture. The underlying steering control actuator is a velocity scheduled model regulator. The designed controllers are tested for steering model regulation and yaw moment disturbance rejection using maneuvers like double lane change. Details of the experimental vehicle with active steering, built to test the concepts developed in the paper is also presented.

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“…As recent advance in automatic steering, researches on lane keeping control have been carried out extensively in the field of automated vehicles [1][2]. Automatic steering is practically important for future automated vehicles on high speed lane keeping manoeuvre and for highway automation [3]. In recent decades, this problem has been investigated worldwide by many research groups, especially in the U.S., Japan, and Europe [4].…”

Section: Introductionmentioning

confidence: 99%

Simulation and experiment of automatic steering control for lane keeping manoeuvre

Ping

Swee

2012

2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012)

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This paper presents a 9-Degree of Freedom (9-DOF) vehicle model combined with a closed-loop driver model for the purpose of developing automatic steering control. The driver model was developed to control the steering angle and uses a lookup table path as a reference for the control input. The proposed driver model for the outer-loop controllers are combination of Proportional-Integral (PI) control with a yaw effect adaptive fuzzy logic control. A stepper motor model, rack and pinion model, and kinematic model of steering system are also introduced as an inner-loop subsystem for Stepper Motor Actuated Steering (SMAS) system. The outer-loop and inner-loop controllers were evaluated by simulation using predefined lane keeping path at 80 km/h constant speed. The Software-in-the-Loop Simulation (SILS) results were validated using an instrumented automatic steering test rig through the Hardware-in-the-Loop Simulation (HILS). The SILS and HILS results show that the proposed automatic steering control is capable of reducing lateral path error and improving lateral path manoeuvre significantly.

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Robust two degree-of-freedom add-on controller design for automatic steering

Cited by 57 publications

References 13 publications

Reduced‐order implementation of disturbance observers for robust tracking of non‐linear systems

Reduced‐order implementation of disturbance observers for robust tracking of non‐linear systems

Robust Velocity Scheduled Yaw Stability Control of a Light Commercial Vehicle

Simulation and experiment of automatic steering control for lane keeping manoeuvre

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