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Explicit model predictive control for active suspension systems with preview.

Theunissen, Johan (2019) Explicit model predictive control for active suspension systems with preview. Doctoral thesis, University of Surrey.

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Latest advances in road profile sensors make the implementation of pre-emptive suspension control a viable option for production vehicles. From the control side, model predictive control (MPC) in combination with preview is a powerful solution for this application. However, the significant computational load associated with conventional implicit model predictive controllers (i-MPCs) is one of the limiting factors to the widespread industrial adoption of MPC. As an alternative, the authors of this study propose an explicit model predictive controller (e-MPC) for an active suspension system with preview. The MPC optimization problem is an mp-QP problem and is run offline. The online controller is reduced to a function evaluation. To overcome the increased memory requirements of e-MPC, the presented controller uses the recently developed regionless e-MPC approach. The controller was assessed through simulations and experiments on a sport utility vehicle (SUV) demonstrator with controllable hydraulic suspension actuators. For frequencies <4 Hz, the experimental results with the regionless e-MPC without preview show a ~10% reduction of the root mean square (RMS) value of the vertical acceleration of the sprung mass with respect to the same vehicle with a skyhook controller. The addition of preview improves the performance by a further 8% to 21% depending on the test.

Item Type: Thesis (Doctoral)
Divisions : Theses
Authors : Theunissen, Johan
Date : 28 June 2019
Funders : Tenneco Automotive Europe bvba
DOI : 10.15126/thesis.00851885
Contributors :
Uncontrolled Keywords : Active suspension; Regionless explicit model predictive control; Preview; Ride comfort
Depositing User : Johan Theunissen
Date Deposited : 03 Jul 2019 09:01
Last Modified : 03 Jul 2019 09:01

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