Relative dynamic modeling and formation control of multiple unmanned helicopters

Σχετικά έγγραφα
ER-Tree (Extended R*-Tree)

Motion analysis and simulation of a stratospheric airship

Trajectory tracking of quadrotor based on disturbance rejection control

High order interpolation function for surface contact problem

Correction of chromatic aberration for human eyes with diffractive-refractive hybrid elements

A Method of Trajectory Tracking Control for Nonminimum Phase Continuous Time Systems

VSC STEADY2STATE MOD EL AND ITS NONL INEAR CONTROL OF VSC2HVDC SYSTEM VSC (1. , ; 2. , )

The straight-line navigation control of an agricultural tractor subject to input saturation

Resilient static output feedback robust H control for controlled positive systems

Estimation of stability region for a class of switched linear systems with multiple equilibrium points

Vol. 31,No JOURNAL OF CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY Feb

MOTROL. COMMISSION OF MOTORIZATION AND ENERGETICS IN AGRICULTURE 2014, Vol. 16, No. 5,

Quick algorithm f or computing core attribute

Study on the Strengthen Method of Masonry Structure by Steel Truss for Collapse Prevention

Control Theory & Applications PID (, )

2 ~ 8 Hz Hz. Blondet 1 Trombetti 2-4 Symans 5. = - M p. M p. s 2 x p. s 2 x t x t. + C p. sx p. + K p. x p. C p. s 2. x tp x t.

Research on model of early2warning of enterprise crisis based on entropy

Adaptive compensation control for a piezoelectric actuator exhibiting rate-dependent hysteresis Y. Ueda, F. Fujii (Yamaguchi Univ.

Schedulability Analysis Algorithm for Timing Constraint Workflow Models

J. of Math. (PRC) Banach, , X = N(T ) R(T + ), Y = R(T ) N(T + ). Vol. 37 ( 2017 ) No. 5

No. 7 Modular Machine Tool & Automatic Manufacturing Technique. Jul TH166 TG659 A

CorV CVAC. CorV TU317. 1

A summation formula ramified with hypergeometric function and involving recurrence relation

2.153 Adaptive Control Lecture 7 Adaptive PID Control

Development of the Nursing Program for Rehabilitation of Woman Diagnosed with Breast Cancer

UAV. UAV Unmanned Aerial Vehicle LED Light Emitting Diodes LQR Linear Quadratic Regulator

= f(0) + f dt. = f. O 2 (x, u) x=(x 1,x 2,,x n ) T, f(x) =(f 1 (x), f 2 (x),, f n (x)) T. f x = A = f

A research on the influence of dummy activity on float in an AOA network and its amendments

An Advanced Manipulation for Space Redundant Macro-Micro Manipulator System

IL - 13 /IL - 18 ELISA PCR RT - PCR. IL - 13 IL - 18 mrna. 13 IL - 18 mrna IL - 13 /IL Th1 /Th2

Π Ο Λ Ι Τ Ι Κ Α Κ Α Ι Σ Τ Ρ Α Τ Ι Ω Τ Ι Κ Α Γ Ε Γ Ο Ν Ο Τ Α

Q L -BFGS. Method of Q through full waveform inversion based on L -BFGS algorithm. SUN Hui-qiu HAN Li-guo XU Yang-yang GAO Han ZHOU Yan ZHANG Pan

Adaptive grouping difference variation wolf pack algorithm

J. of Math. (PRC) 6 n (nt ) + n V = 0, (1.1) n t + div. div(n T ) = n τ (T L(x) T ), (1.2) n)xx (nt ) x + nv x = J 0, (1.4) n. 6 n

Buried Markov Model Pairwise

Autonomous navigation control for mobile robots based on emotion and environment cognition

Optimization, PSO) DE [1, 2, 3, 4] PSO [5, 6, 7, 8, 9, 10, 11] (P)

Journal of South China University of Technology Natural Science Edition. ADAMS-Matlab /Simulink . 1. f θ = v fsin γ + l rγ

supporting phase aerial phase supporting phase z 2 z T z 1 p G quardic curve curve f 2, n 2 f 1, n 1 lift-off touch-down p Z

ROBOT. Design and Realization of a Control System for Laparoscopic Robot

Feasible Regions Defined by Stability Constraints Based on the Argument Principle

Nov Journal of Zhengzhou University Engineering Science Vol. 36 No FCM. A doi /j. issn

Study of In-vehicle Sound Field Creation by Simultaneous Equation Method

ΔΙΠΛΩΜΑΤΙΚΕΣ ΕΡΓΑΣΙΕΣ

HDD. Point to Point. Fig. 1: Difference of time response by location of zero.

1 (forward modeling) 2 (data-driven modeling) e- Quest EnergyPlus DeST 1.1. {X t } ARMA. S.Sp. Pappas [4]

Fragility analysis for control systems

2002 Journal of Software

Study on Re-adhesion control by monitoring excessive angular momentum in electric railway traction

ΒΙΟΓΡΑΦΙΚΟ ΣΗΜΕΙΩΜΑ ΣΤΥΛΙΑΝΗΣ Κ. ΣΟΦΙΑΝΟΠΟΥΛΟΥ Αναπληρώτρια Καθηγήτρια. Τµήµα Τεχνολογίας & Συστηµάτων Παραγωγής.

A System Dynamics Model on Multiple2Echelon Control

Re-Pair n. Re-Pair. Re-Pair. Re-Pair. Re-Pair. (Re-Merge) Re-Merge. Sekine [4, 5, 8] (highly repetitive text) [2] Re-Pair. Blocked-Repair-VF [7]

ACTA MATHEMATICAE APPLICATAE SINICA Nov., ( µ ) ( (

Stress Relaxation Test and Constitutive Equation of Saturated Soft Soil

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems

Gain self-tuning of PI controller and parameter optimum for PMSM drives

3: A convolution-pooling layer in PS-CNN 1: Partially Shared Deep Neural Network 2.2 Partially Shared Convolutional Neural Network 2: A hidden layer o

( ) , ) , ; kg 1) 80 % kg. Vol. 28,No. 1 Jan.,2006 RESOURCES SCIENCE : (2006) ,2 ,,,, ; ;

Prey-Taxis Holling-Tanner

Optimization Investment of Football Lottery Game Online Combinatorial Optimization

Δυσκολίες που συναντούν οι μαθητές της Στ Δημοτικού στην κατανόηση της λειτουργίας του Συγκεντρωτικού Φακού

Arbitrage Analysis of Futures Market with Frictions

: Monte Carlo EM 313, Louis (1982) EM, EM Newton-Raphson, /. EM, 2 Monte Carlo EM Newton-Raphson, Monte Carlo EM, Monte Carlo EM, /. 3, Monte Carlo EM

Research on Economics and Management

Ó³ Ÿ , º 2(131).. 105Ä ƒ. ± Ï,.. ÊÉ ±μ,.. Šμ ² ±μ,.. Œ Ì ²μ. Ñ Ò É ÉÊÉ Ö ÒÌ ² μ, Ê

Reading Order Detection for Text Layout Excluded by Image

ROBOT. Dynamic Model Based Motor Control for Wheeled Mobile Robots

Probabilistic Approach to Robust Optimization

Table of Contents 1 Supplementary Data MCD

Real time mobile robot control with a multiresolution map representation

ΕΥΡΕΣΗ ΤΟΥ ΔΙΑΝΥΣΜΑΤΟΣ ΘΕΣΗΣ ΚΙΝΟΥΜΕΝΟΥ ΡΟΜΠΟΤ ΜΕ ΜΟΝΟΦΘΑΛΜΟ ΣΥΣΤΗΜΑ ΟΡΑΣΗΣ

Approximation Expressions for the Temperature Integral

The optimization of EV powertrain s efficiency control strategy under dynamic operation condition

CAP A CAP

DOI /J. 1SSN

Research on vehicle routing problem with stochastic demand and PSO2DP algorithm with Inver2over operator

Table S1. Summary of data collections and structure refinements for crystals 1Rb-1h, 1Rb-2h, and 1Rb-4h.

Computational study of the structure, UV-vis absorption spectra and conductivity of biphenylene-based polymers and their boron nitride analogues

Resurvey of Possible Seismic Fissures in the Old-Edo River in Tokyo

ΚΑΤΑΣΚΕΥΑΣΤΙΚΟΣ ΤΟΜΕΑΣ

Optimization Investment of Football Lottery Game Online Combinatorial Optimization

Gro wth Properties of Typical Water Bloom Algae in Reclaimed Water

Experimental Study of Dielectric Properties on Human Lung Tissue

New conditions for exponential stability of sampled-data systems under aperiodic sampling

Exact linearization control scheme of DFIG

Research on real-time inverse kinematics algorithms for 6R robots

n 1 n 3 choice node (shelf) choice node (rough group) choice node (representative candidate)

Vol. 38 No Journal of Jiangxi Normal University Natural Science Nov. 2014

Multi-GPU numerical simulation of electromagnetic waves

Ηλεκτρονικοί Υπολογιστές IV

Congruence Classes of Invertible Matrices of Order 3 over F 2

Accounts receivable LTV ratio optimization based on supply chain credit

Evolution of Novel Studies on Thermofluid Dynamics with Combustion

Προσωποποιημένη πλοήγηση σε εξωτερικούς χώρους: ανασκόπηση αλγορίθμων και μεθόδων επιλογής μονοπατιού

Position control of the planar switched reluctance motor based on model reference adaptive regulator

Α Ρ Ι Θ Μ Ο Σ : 6.913

Σχολή Εφαρμοσμένων Μαθηματικών και Φυσικών Επιστημών. Εθνικό Μετσόβιο Πολυτεχνείο. Thales Workshop, 1-3 July 2015

Bundle Adjustment for 3-D Reconstruction: Implementation and Evaluation

2002 Journal of Software

Dynamic Torque Control Strategy of Engine Clutch in Hybrid Electric Vehicle

Transcript:

28 1 2011 1 : 1000 8152(2011)01 0108 05 Control Theory & Applications Vol. 28 No. 1 Jan. 2011 1, 2, 2 (1., 110016; 2., 110016) :,. 6..,. : ; ; : TP273 : A Relative dynamic modeling and ormation control o multiple unmanned helicopters WANG Zheng 1, HE Yu-qing 2, HAN Jian-da 2 (1. Graduate school o Chinese Academy o Sciences, Shenyang Liaoning 110016, China; 2. State Key Laboratory o Robotics,Shenyang Institute o Automation, Chinese Academy o Sciences, Shenyang Liaoning 110016, China) Abstract: Based on the concept o relative dynamics and leader-ollower ormation strategy, a new ormation control algorithm is developed to partially solve the ormation problem. Firstly, the relative dynamics is derived by combining the 6-DOF rigid body relative dynamics with the individual unmanned helicopter dynamics. Secondly, with the cascade control structure which includes inner and outer loops, a tracking controller is designed by using the techniques o approximate eedback linearization and the extended high gain observer. Finally, simulations o the proposed method with two unmanned helicopter systems are conducted to test the desired tracking perormance and easible disturbance rejection. Key words: unmanned helicopter; ormation control; relative dynamics 1 (Introduction) ( ),. (L-F) [1] [2]., ( ),., Follower ; U.C. Berkeley Aerobot Team Mesh,, [3].,.,, [4]. [5],.,. : 1) ; 2). 2 (Problems statement) (leader) (ollower). oxyz 1.,,.,., p l oxyz, p l x y z., p l, p l R 3. : 2009 11 13; : 2010 05 07. : (RLZ200806).

1 : 109 (L-F), : ẋ l = (x l, u, u l l). (1) : x l L-F, u F, u l l L. : F L u l l. (1), F u, ul l., L 6 ( 3 (5)). : 1) p L-F, L-F ; 2) p u i = κ i (x li) (i = 1, 2,, p) p. 3 (Relative dynamics o unmanned helicopters)., : / 3 [7]. θ m θ t T m T t ; / T m, T t a 1, b 1 6 i i, τ i i ; 6,, 2. / [7] i i = [ 1] T u 4 + ε(u 1, u 2, u 3 ), (2) τi i = [u 1 u 2 u 3 ] T. 1 Fig. 1 Coordinates o leader-ollowing unmanned helicopters : 0 ε 2 0 u 1 ε(u 1, u 2, u 3 ) = ε 1 0 ε 3 u 2, 0 u 3 ε 4 (u 4 ) u 1 = z mr T m b 1, ε 1 = 1/z mr, u 2 = z mr T m a 1, ε 2 = 1/z mr, u 3 = (k 0 + k T T 1.5 m + x tr T t ), ε 3 = 1/x tr, u 4 = T m, ε 4 (T m )=k 0 +k T T 1.5 m. T m, T t. a 1, b 1,. z mr z, x tr x, 1. k 0, k T,. 1 L-F [6] : ( ) Leader, Leader,, Leader,, L-F. Leader L-F [6]., L-F. [2]. 2 Fig. 2 Structure o unmanned helicopters relative dynamics, 6 / 3, 2

110 28., 6, Leader l l τ l l. ( 1), L-F : p l = R T (p l p ), (3) Rl = R T R l. p l L F, R l L x ly l z l F x y z. (3), ṗ l = R T υ l R T υ Ω(ω )p l, (4) Θ l = ψ 1 ωl l ψ 2 ω. : ωi i, ωi i Ω(ωi) 3 i 3, ωi i u = Ω(ωi)u, i i = l or ; Θl L F. R T υ l R T υ L-F ; Ω(ω )p l ; ψ 1 ωl l ψ 2ω L-F ; ψ 1 ψ 2 Ṙi = R i Ω(ωi), i : 1 sϕ lsθl /cθl sθl cθl /cϕ l ψ 1 = 0 cϕ l sϕ l, 0 sϕ l/cθl cϕ l/cθl cφ l/cθl sφ l/cθl 0 ψ 2 = sφ l cφ l 0. sθl cφ l/cθl sθl sφ l/cθl 1 (5)(6) L-F. 3 1 x = [p l υ l Θ l ω ] T ; F 4 u = [u 1 u 2 u 3 u 4 ] T ; L 6 w = [ l l /m l ω l l] T. : (x)= ẋ = (x) + g 1 (x)w + g 2 (x)u, (7) υ l Ω 2 (ω )p l Ω(p l)(j ) 1 Ω(ω )J ω 2Ω(ω )υ l ψ 2 ω, (J ) 1 Ω(ω )J ω R g 1 (x) = l/m l 0 0 ψ 1, I 3 3 /m Ω(p g 2 (x) = l)(j ) 1. 0 (J ) 1 4 (Formation control),,, 3. (4) 1 (4) 2, p l = Rl l l /m l /m Ω 2 (ω )p l Ω( ω )p l 2Ω(ω )ṗ l, (5) Θ l = ψ 1 ωl l ψ 2 ω, ω = (J ) 1 (τ Ω(ω )J ω ). R l l l /m l /m L-F ; Ω 2 (ω )p l Ω( ω )p l L- F ; Ω(ω )ṗ l ; m i J i i ; i i τ i i. 6 (5) (2)., Follower / = [ 1] T u 4 + ε(u 1, u 2, u 3 ), (6) τ = [u 1 u 2 u 3 ] T, 3 Fig. 3 Structure o tracking control ϕ l θ l,. ϕ l θ l, ϕ l θ l.,, ϕ l, θ l u = [u 1 u 2 u 3 u 4 ] T 6. (7) 2 Θ l = ψ 2 ω +ψ 2 (J ) 1 Ω(ω )J ω ψ 2 (J ) 1 u i,,

1 : 111 u i = J ψ 1 2 [(K 1 e Θ + K 2 ė Θ ) + ψ 2 ω ˆp l = ˆυ l + H 1 (ε)(p l ˆp l), ψ 2 (J ) 1 Ω(ω )J ω ], (8) ˆυ l = ẑl + H 2 (ε)(p l ˆp l), ẑ l = ˆσ + ˆβ(ˆx o, η) + ˆα(ˆx o, η)u o + (11). e Θ = Θ l d Θ l, ė Θ = Θ l d Θ H 3 (ε)(p l, l ˆp l), ˆσ = H 4 (ε)(p l ˆp l). Θ l d Θ l d. K 1 K 2,. (7) ( ),., ϕ l, θ l u 4, u o = [ ϕ l θ l u 4 ] T, 3,, ω, τ φ l. l l [ 0] T, (7) Rl, ϕ l θ l. ŵ l l /m l, Rl( l l /m l ŵ).,, ε(u 1, u 2, u 3 ), [8]., ε(u 1, u 2, u 3 ) Rl( l l /m l ŵ), : p l = Ω 2 (ω )p l Ω(p l)(j ) 1 Ω(ω )J ω 2Ω(ω )ṗ l + Ω(p l)(j ) 1 τ + R lŵ + 1 m (0, 0, 1) T u 4 + δ, ϕ l = u o1, θ l = u o2, u 4 = u o3. (9) : u o = [u o1 u o2 u o3 ] T. δ = R l( l l /m l ŵ) + ε(u 1, u 2, u 3 )., u o = α 1 (x o, η)[k 3 (p l d p l) + K 4 (ṗ l d ṗ l) + K 5 ( p l d p l) β(x o, η)], (10) x o = [p l ṗ l] T, η = [φ l τ ω ] T, β(x o, η)= Ω 2 (ω )ṗ l +Ω[(J ) 1 Ω(ω )J ω ]ṗ l 2Ω(ω ) p l Ω[(J ) 1 τ ]ṗ l, 0 α(x o, η) = Rl ŵ R l ŵ 0 ϕ l θl 1, m K 3, K 4 K 5., ϕ l θ l ϕ l d θ l d, 3.,, : ˆp l ˆυ l, ẑl ˆυ l. α i /ε i H i (ε) = α i /ε i, i = 1,, 4. α i /ε i α i s 4 + α 1 s 3 + α 2 s 2 + α 3 s 1 + α 4 Hurwitz. ε > 0. ˆα( ) ˆβ( ),,, ˆα( ) = α( ), ˆβ( ) = β( ). ˆσ. (11), H i (ε)(p l ˆp l). (9), u o = ˆα 1 (ˆx o, η)[κ(ˆx o ) ˆσ ˆβ(ˆx o, η)], (12) κ(ˆx o ) (10), κ(ˆx o ) = K 3 (p l d ˆp l) + K 4 (ṗ l d ˆυ l ) + K 5 ( p l d ẑ l ), (13).,,. u o =satˆα 1 (ˆx o, η)[κ(ˆx o ) ˆσ ˆβ(ˆx o, η)]}. (14) : sat( ), sat(x) = min1, M}sgn x, : M, ±M. [9]. 5 (Simulation), L-F p l0 = (5, 5, 5) T Θl0 = (0, 0, 0.1) T. p l d = (2, 2, 2) T, Θl d = (0, 0, 0) T. K 1 = 5 I 3 3, K 2 = 10 I 3 3, K 3 = I 3 3, K 4 = 2 I 3 3, K 5 = 2 I 3 3, ε = 0.01, M = 10 3, α 1 = 4, α 2 = 6, α 3 = 4, α 4 = 1, I., 10 s L, F,

112 28 l l /m = ŵ = (0, 0, 9.8) T, ω l l = ˆω l l = (0, 0, 0) T. 10 s, L, l l /m = (1, 1, 9.8) T,, ŵ = (0, 0, 9.8) T,., L-F 4, L, F 10 s 10 s. 5. : 10 sf, 10 sf L. 4 L-F Fig. 4 Leader and ollower s trajectories... (Reerences): [1] CHEN XP, SERRANI A, OZBAY H. Control o leader-ollower ormations o terrestrial UAVs[C] //Proceedings o the 42nd IEEE Conerence on Decision and Control. Maui, HI: IEEE, 2003: 498 503. [2] SHAW E, HEDRICK J K. Controller design or string stable heterogeneous vehicle strings[c] //Proceedings o the 46th IEEE Conerence on Decision and Control. New Orleans, LA: IEEE, 2007: 6157 6164. [3] SHAW E, CHUNG H, HEDRICK JK, et al. Unmanned helicopter ormation light experiment or the study o mesh stability[m] //Lecture Notes in Economics and Mathematical Systems. Berlin/Heidelberg: Springer, 2007, 588: 37 56. [4] VIDAL R, SHAKERNIA O, SASTRY S. Distributed ormation control with omnidirectional vision-based motion segmentation and visual servoing[j]. Robotics and Automation Magazine, 2004, 11(4): 14 20. [5] WONG H, KAPILA V, SPARKS A G. Adaptive output eedback tracking control o spacecrat ormation[j]. International Journal o Robust and Nonlinear Control, 2002, 12(2): 117 139. [6] HE Y Q, HAN J D. Decentralized receding horizon control or multiple unmanned helicopters considering dynamics model[c] //Proceedings o the 48th IEEE Conerence on Decision and Control. Shanghai: IEEE, 2009: 8351 8356. [7] BEJAR M, OLLERO A, CUESTA F. Modeling and control o autonomous helicopters[m] //Lecture Notes in Control and Inormation Sciences. Berlin/Heidelberg: Springer, 2007, 353: 1 29. [8] KOO TJ, SASTRY S, Output tracking control design o a helicopter model based on approximate linearization[c] //Proceedings o the 37th IEEE Conerence on Decision and Control. Tampa, FL: IEEE, 1998: 3635 3640. [9] FREIDOVICH L B, KHALIL H K, Robust eedback linearization using extended high-gain observers[c] //Proceedings o the 45th IEEE Conerence on Decision and Control. San Diego, CA: IEEE, 2006: 983 988. : 5 Fig. 5 Relative positions and relative velocities 6 (Conclusion).,. (1982 ),,,, E-mail: wzheng@sia.cn; (1980 ),,,,, E-mail: heyuqing@sia.cn; (1968 ),,,,, / /, E-mail: jdhan@sia.cn.