Automatic Landing System Design using Feedback Linearization Method

Prasad, B. Biju; Pradeep, S.

doi:10.2514/6.2007-2733

Cited by 29 publications

(17 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Putting together equations (5), (13), and (15), the following equation is obtained: (16) To proof that, in steady regime, the forms of z 1 = θ and z 2 = u are the same with the ones in equations (13) and (16), we used the expansion of z = [ z 1 z 2 ] T as function of x and u; for u 0 = 0, we have successively obtained the following equations:…”

Section: Design Of the H 2 /H ∞ Control Lawmentioning

confidence: 99%

“…Feed-forward neural networks with back propagation learning algorithm have also been used [8], the main drawback of such systems being that the neural networks require a priori training on normal and faulty operating data. In [16] the feedback linearization method has been used for nonlinear control in the design of an automatic landing system; unfortunately, the paper presents limited insight into the performance of simulations of this controller and no tests are performed outside of these simulations. In the work of Singh and Padhi [4] a nonlinear control has been designed using the dynamic inversion approach for the automatic landing of unmanned aerial vehicles along with associated path planning.…”

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Application of H 2 /H ∞ and dynamic inversion techniques to aircraft landing control

Lungu

2015

Aerospace Science and Technology

View full text Add to dashboard Cite

Section: Design Of the H 2 /H ∞ Control Lawmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Application of H 2 /H ∞ and dynamic inversion techniques to aircraft landing control

Lungu

2015

Aerospace Science and Technology

View full text Add to dashboard Cite

“…controller was designed based on the linearized model of longitudinal mode [6]. Feedback linearization technique was used to design for autonomous landing system [7]. Adaptive back stepping control was used for path tracking [8,9].…”

Section: Introductionmentioning

confidence: 99%

Adaptive internal model control research in autonomous landing phase for a fixed-wing UAV

Jiu-zhou

Jia

2016

CEAS Aeronaut J

View full text Add to dashboard Cite

Autonomous landing is a very complex phase of flight for unmanned aerial vehicle (UAV). Adaptive internal model control (AIMC) is proposed and applied on autonomous landing control system in this paper. Controllers are designed based on the decoupled and linearized models of a sample UAV. Estimation of process model is carried out to enhance system robustness, and filter parameter adjustment is proposed to achieve a good dynamic performance. Control effects are compared and analyzed between IMC and AIMC in different wind conditions which demonstrate that AIMC has better performances than IMC. At last, Monte Carlo simulations prove the system stability.

show abstract

“…This method has several advantages, like simplicity in the control structure, ease of implementation, global exponential stability of the tracking error etc. Note that a feedback linearization technique has been successfully demonstrated through simulation for automatic landing of a high performance aircraft [1]. The control implemented for the UAV in this paper has inner loop and outer loop structure.…”

Section: Introductionmentioning

confidence: 99%

“…Landing trajectories of aerial vehicles typically consists of approach, glideslope and flare [1]. A successful landing would depend upon the good selection of landing trajectory and closely following it.…”

Section: Introductionmentioning

confidence: 99%

Automatic path planning and control design for autonomous landing of UAVs using dynamic inversion

Singh

Padhi

2009

2009 American Control Conference

View full text Add to dashboard Cite

Abstract-In this paper a nonlinear control has been designed using the dynamic inversion approach for automatic landing of unmanned aerial vehicles (UAVs), along with associated path planning. This is a difficult problem because of light weight of UAVs and strong coupling between longitudinal and lateral modes. The landing maneuver of the UAV is divided into approach, glideslope and flare. In the approach UAV aligns with the centerline of the runway by heading angle correction. In glideslope and flare the UAV follows straight line and exponential curves respectively in the pitch plane with no lateral deviations. The glideslope and flare path are scheduled as a function of approach distance from runway. The trajectory parameters are calculated such that the sink rate at touchdown remains within specified bounds. It is also ensured that the transition from the glideslope to flare path is smooth by ensuring C 1 continuity at the transition. In the outer loop, the roll rate command is generated by assuring a coordinated turn in the alignment segment and by assuring zero bank angle in the glideslope and flare segments. The pitch rate command is generated from the error in altitude to control the deviations from the landing trajectory. The yaw rate command is generated from the required heading correction. In the inner loop, the aileron, elevator and rudder deflections are computed together to track the required body rate commands. Moreover, it is also ensured that the forward velocity of the UAV at the touch down remains close to a desired value by manipulating the thrust of the vehicle. A nonlinear six-DOF model, which has been developed from extensive wind-tunnel testing, is used both for control design as well as to validate it.

show abstract

Automatic Landing System Design using Feedback Linearization Method

Cited by 29 publications

References 4 publications

Application of H 2 /H ∞ and dynamic inversion techniques to aircraft landing control

Application of H 2 /H ∞ and dynamic inversion techniques to aircraft landing control

Adaptive internal model control research in autonomous landing phase for a fixed-wing UAV

Automatic path planning and control design for autonomous landing of UAVs using dynamic inversion

Contact Info

Product

Resources

About