Direct Method Based Control System for an Autonomous Quadrotor

Cowling, Ian D.; Yakimenko, Oleg A.; Whidborne, James F.; Cooke, Alastair

doi:10.1007/s10846-010-9416-9

Cited by 74 publications

(41 citation statements)

References 31 publications

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“…R is the rotation matrix from body-fixed frame to inertial frame. Because the first rotation about the axis of thrust can simplify the equations of motion, rotation matrix R in the order of z − x − y is used in this paper (Cowling et al, 2010). R zxy is given by The external force F and torque M are composed of two parts: one is the control force F 0 and torque M 0 generated by the four rotors; and another is the lumped disturbance force F d and torque M d originated from other force and torque contributions such as wind turbulences and parameter uncertainties.…”

Section: Quadrotor Modellingmentioning

confidence: 99%

“…Stabilising system (8) at the operating point is a regulation problem. In order to achieve tracking, the actual control signal is constructed as (Cowling et al, 2010;Raptis, Valavanis, & Vachtsevanos, 2012):…”

Section: Assumptionmentioning

confidence: 99%

“…Solving a nonlinear optimisation problem with constraints is computationally intensive, which is the main obstacle that blocks the real-time application of MPC to nonlinear systems. To reduce the computational burden of online optimisation, the differential flatness property has been exploited in many trajectory planning algorithms which are actually MPC problems (Berry, Howitt, Gu, & Postlethwaite, 2011;Cowling, Yakimenko, Whidborne, & Cooke, 2010;Faulwasser, Hagenmeyer, & Findeisen, 2014;Flores & Milam, 2006;Mahadevan, Agrawal, & Doyle, 2001;Prodan et al, 2013;Suryawan, De Don, & Seron, 2012). Loosely speaking, the differential flatness means that the flat system can be completely characterised by flat outputs and their higher order derivatives (Fliess, Lvine, Martin, & Rouchon, 1995).…”

Section: Introductionmentioning

confidence: 99%

“…Thus, an infinite dimensional dynamic optimal control problem can be cast into a finite dimensional static one on the condition that the flat outputs are parametrised in terms of polynomials. As a result, for example, the optimisation problem reduces to a tractable nonlinear programming (NLP) problem (Cowling et al, 2010) or even a simpler quadratic programming (QP) problem (Suryawan et al, 2012). Although the reduction in calculation time of the optimisation can bring a great increase to the updated rate of MPC, this kind of nonlinear constrained optimal control may still result in a degraded performance due to the disturbances and uncertainties existing in practical application process, especially for the sophisticated systems with relatively fast dynamics like aircraft.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Constrained anti-disturbance control for a quadrotor based on differential flatness

Lü

Liu

Guo

et al. 2016

International Journal of Systems Science

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The classical control design based on linearised model is widely used in practice even to those inherently nonlinear systems. Although linear design techniques are relatively mature and enjoy the simple structure in implementations, they can be prone to misbehaviour and failure when the system state is far away from the operating point. To avoid the drawbacks and exploit the advantages of linear design methods while tackling the system nonlinearity, a hybrid control structure is developed in this paper. First, the model predictive control is used to impose states and inputs constraints on the linearised model, which makes the linearisation satisfy the small-perturbation requirement and reduces the bound of linearisation error. On the other hand, a combination of disturbance observer based control and H∞ control, called composite hierarchical anti-disturbance control, is constructed for the linear model to provide robustness against multiple disturbances. The constrained reference states and inputs generated by the outer-loop model predictive controller are asymptotically tracked by the inner-loop composite anti-disturbance controller. To demonstrate the performance of the proposed framework, a case study on quadrotor is conducted.

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Section: Quadrotor Modellingmentioning

confidence: 99%

Section: Assumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Constrained anti-disturbance control for a quadrotor based on differential flatness

Lü

Liu

Guo

et al. 2016

International Journal of Systems Science

View full text Add to dashboard Cite

show abstract

“…This paper formulates the TPBVP for the underwater docking problem and then employs the well-known direct method, inverse dynamics in the virtual domain (IDVD) method, to develop and test a real-time trajectory generator for realization on board of an AUV that is currently under the development at the Flinders University. This method has already been implemented on aerial [16,[18][19][20][21][22], maritime [4] and space vehicles [23,24], and is now evaluated for the AUV dynamic model featuring seven states and three controls. The IDVD's effectiveness stems from several important properties…”

Section: Introductionmentioning

confidence: 99%