Preview-based techniques for vehicle suspension control: a state-of-the-art review

Theunissen, Johan; Tota, Antonio; Gruber, Patrick; Dhaens, Miguel; Sorniotti, Aldo

doi:10.1016/j.arcontrol.2021.03.010

Cited by 95 publications

(58 citation statements)

References 103 publications

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“…With those definitions, (3) is rewritten as (6). The state vector of the QC model is defined as (7). With the definitions of new matrices as given in (8), the state-space equation for QC model is obtained as (9).…”

Section: Controller Design With Quarter-car Modelmentioning

confidence: 99%

“…However, the FC model is so complex that it is not easy to implement a controller for active suspension. Several methodologies such as linear optimal control, H∞ control, nonlinear control, and adaptive control theories have been applied in designing an active suspension controller [3][4][5][6][7][8]. Among these methodologies, linear quadratic regulator (LQR) has been widely adopted with 2-DOF QC and 7-DOF FC models because it can provide a systematic way to design a controller for active suspension.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, there have been a lot of studies on active suspension control. Comprehensive surveys on active suspension control can also be found in [3][4][5][6][7]. Recent advances for the last decade in active suspension control are summarized in [8].…”

Section: Introductionmentioning

confidence: 99%

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Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

Park

Yim

2021

Energies

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This paper presents a method to design active suspension controllers for a 7-Degree-of-Freedom (DOF) full-car (FC) model from controllers designed with a 2-DOF quarter-car (QC) one. A linear quadratic regulator (LQR) with 7-DOF FC model has been widely used for active suspension control. However, it is too hard to implement the LQR in real vehicles because it requires so many state variables to be precisely measured and has so many elements to be implemented in the gain matrix of the LQR. To cope with the problem, a 2-DOF QC model describing vertical motions of sprung and unsprung masses is adopted for controller design. LQR designed with the QC model has a simpler structure and much smaller number of gain elements than that designed with the FC one. In this paper, several controllers for the FC model are derived from LQR designed with the QC model. These controllers can give equivalent or better performance than that designed with the FC model in terms of ride comfort. In order to use available sensor signals instead of using full-state feedback for active suspension control, LQ static output feedback (SOF) and linear quadratic Gaussian (LQG) controllers are designed with the QC model. From these controllers, observer-based controllers for the FC model are also derived. To verify the performance of the controllers for the FC model derived from LQR and LQ SOF ones designed with the QC model, frequency domain analysis is undertaken. From the analysis, it is confirmed that the controllers for the FC model derived from LQ and LQ SOF ones designed with the QC model can give equivalent performance to those designed with the FC one in terms of ride comfort.

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Section: Controller Design With Quarter-car Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

Park

Yim

2021

Energies

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“…Regarding the actuators used to generate active force, hydraulic actuators and electric motors have been applied [9,10,14,15,17,19,21]. Comprehensive surveys of active suspension control methods, including those related to dynamic models, controller designs, and actuators, can be found in the literature [1,4,[22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Design of Static Output Feedback Controllers for an Active Suspension System

et al. 2022

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This paper presents a method by which to design linear quadratic (LQ) static output feedback (SOF) controllers with a 2-DOF quarter-car model for an active suspension system. Generally, it is challenging to implement linear quadratic regulator (LQR), designed with a full-car model, in actual vehicles because doing so requires 14 state variables to be precisely measured. For this reason, LQR has been designed with a quarter-car model and then applied to a full-car model. Although this requires far fewer state variables, some of them are still difficult to measure. Thus, it is necessary to design a LQ SOF controller which uses available sensor signals that are relatively easily measured in real vehicles. In this paper, a LQ SOF controller is designed with a quarter-car model and applied to a full-car model for ride comfort. To design the controller, an optimization problem is formulated and solved by a heuristic optimization method. A frequency domain analysis and a simulation with a simulation package show that the proposed LQ SOF controllers effectively improve the ride comfort with an active suspension system.INDEX TERMS active suspension control, static output feedback control, 2-DOF quarter-car model, 7-DOF full-car model, linear quadratic regulator

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“…Meanwhile, the performance trade-off between the ride comfort and driving safety is the most fundamental requirement of the process of designing the reasonable vibration controller [18]. Recently, many advanced optimal control theories, combined with disturbance rejection, have been developed for vehicle active suspension, such as stochastic optimal control for delayed vehicle active suspension [19], approximation optimal vibration control for nonlinear vehicle active suspension [20], preview-based technique for vehicle active suspension control [21], linear-quadratic-regulator-based control for vehicle active suspension [22], and so on. In general, while discussing the optimal vibration control problem with the network-induced time delay and packet dropout in CAN, the two-point boundary value (TPBV) problem with time-delay and time-advance items will be encountered, which makes it difficult to obtain the optimal analytic solution.…”

Section: Introductionmentioning

confidence: 99%

CAN-Based Vibration Control for Networked Vehicle Active Suspension with Both Network-Induced Delays and Packet-Dropouts

et al. 2022

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Ride comfort and driving safety are highly vulnerable to the undesirable excessive vibrations caused by road surface irregularities and the imperfect in-vehicle network (IVN). The main contribution of this paper consists of proposing a near-optimal vibration control approach for networked vehicle active suspension under irregular road excitations in a discrete-time domain, in which the uncertain time delay and packet dropout in CAN are taken into consideration. More specially, by virtue of two buffers of the sensor-to-controller network channel and the controller-to-actuator network channel in CAN, by introducing a designed state-transformation-based method, the original vibration control problem under the constraints of the irregular road excitations and imperfect CAN is transformed into a two-point boundary value (TPBV) problem without advanced and delayed items. After that, the near-optimal vibration control approach is presented to isolate the vehicle body from the road excitations and compensate the time delay and packet dropout from CAN synchronously. The stability condition of the networked vehicle active suspension under the proposed vibration controller is obtained based on the Lyapunov function. In numerous scenarios with different road roughnesses and network-induced time delays and packet dropouts, the simulation results illustrate the effectiveness and superiority of the proposed near-optimal vibration controller.

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Preview-based techniques for vehicle suspension control: a state-of-the-art review

Cited by 95 publications

References 103 publications

Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

Design of Static Output Feedback Controllers for an Active Suspension System

CAN-Based Vibration Control for Networked Vehicle Active Suspension with Both Network-Induced Delays and Packet-Dropouts

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