The safety of driving two-wheel vehicles, such as motorcycles, can be significantly improved through electronic control of the their stability properties. This will also allow for precise path following and capability for dexterous maneuvering. In this article, a nonlinear optimal control method is developed for solving the stabilization and path following problem of autonomous motorcycles. The joint kinematic and dynamic model of the motorcycle undergoes approximate linearization around a temporary operating point which is recomputed at each iteration of the control algorithm. The linearization takes place using Taylor series series expansion and the computation of the Jacobian matrices of the system's states-space model. For the approximately linearized model of the motorcycle an H-infinity feedback controller is designed. The computation of the feedback gain of the controller requires the repetitive solution of an algebraic Riccati equation, taking again place at each time-step of the control method. The concept of the control method is that at each time instant the system's state vector is made to converge to the temporary equilibrium, while this equilibrium is shifted towards the reference trajectory. Thus, asymptotically the state vector of the motorcycle converges to the reference setpoints. Through Lyapunov stability analysis the global asymptotic stability properties of the control method are proven.

A nonlinear optimal control approach for autonomous motorcycles

Rigatos, G.;Siano, P.;
2018-01-01

Abstract

The safety of driving two-wheel vehicles, such as motorcycles, can be significantly improved through electronic control of the their stability properties. This will also allow for precise path following and capability for dexterous maneuvering. In this article, a nonlinear optimal control method is developed for solving the stabilization and path following problem of autonomous motorcycles. The joint kinematic and dynamic model of the motorcycle undergoes approximate linearization around a temporary operating point which is recomputed at each iteration of the control algorithm. The linearization takes place using Taylor series series expansion and the computation of the Jacobian matrices of the system's states-space model. For the approximately linearized model of the motorcycle an H-infinity feedback controller is designed. The computation of the feedback gain of the controller requires the repetitive solution of an algebraic Riccati equation, taking again place at each time-step of the control method. The concept of the control method is that at each time instant the system's state vector is made to converge to the temporary equilibrium, while this equilibrium is shifted towards the reference trajectory. Thus, asymptotically the state vector of the motorcycle converges to the reference setpoints. Through Lyapunov stability analysis the global asymptotic stability properties of the control method are proven.
2018
9781538654286
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4720053
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact