Design and Control of Novel Tri-rotor UAV
|
|
- Marian Whitehead
- 5 years ago
- Views:
Transcription
1 Design and Control of Noel Tri-rotor UAV Mohamed Kara Mohamed School of Electrical and Electronic Engineering The Uniersity of Manchester Manchester, UK, M 9PL Mohamed.KaraMohamed@postgrad.manchester.ac.uk Alexander Lanzon School of Electrical and Electronic Engineering The Uniersity of Manchester Manchester, UK, M 9PL Alexander.Lanzon@manchester.ac.uk Abstract Tri-rotor UAVs are more efficient compared to quadrotors in regard to their size and power requirement, yet, they are more challenging in terms of control and stability. In this paper, we propose the design and control of a noel tri-rotor UAV. The proposed platform is designed to achiee six degree of freedom using a thrust ectoring technique with the highest leel of flexibility, manoeurability and minimum requirement of power. The proposed tri-rotor has a triangular shape of three arms at the end of each arm, a fixed pitch propeller is drien by a DC motor. A tilting mechanism is employed to tilt the motor-propeller assembly and produce thrust in the desired direction. The three propellers can be tilted independently to achiee full authority of torque and force ectoring. A feedback linearization associated with H loop shaping design is used to synthesize a controller for the system. The results are erified ia simulation. I. BACKGROUND AND MOTIVATION In recent decades, Unmanned Aerial Vehicles (UAVs) hae attracted growing attention in research due to their wide applications and large potential [], []. Aiming for more efficiency in term of size, autonomy, payload capacity and maneuerability among other factors, arious conentional and non-conentional structure designs and configurations of UAV systems are proposed [], [4] and the literature therein. One such design that attracts increasing interest is the ertical-takeoff-and-landing (VTOL) tri-rotor configuration. Tri-rotor ehicles are systems with three rotors arrangement. This configuration has been proposed as less-expensie with more flexibility and great agility [4], [5]. Compared to quadrotors, tri-rotor UAVs are smaller in size, less complex, less costly and hae longer flight time due to the reduction in number of motors [6], which makes tri-rotor ehicles ideal for deployment in arious research projects and missions [7]. Thrust ectoring has been used in designs to maximize the capability of UAVs [8]. Thrust ectoring is of significant benefit in some applications to arbitrarily orient the ehicle body with respect to the ehicle acceleration ector, e.g., for aircrafts carrying directional sensors that hae to be pointed at targets in the earth reference frame [9]. In addition, thrust ectoring mechanism is used to gie UAVs the capability of taking-off and landing in ery narrow areas []. In small aircrafts and UAVs, a simple technique of tilt-rotor mechanism can be used to obtain thrust ectoring, propulsion units are inclined in certain angles using an additional control motor to get the desired thrust in different directions. In tri-rotor systems, tilt-rotor mechanism is used to control the horizontal forces and yaw torque of the ehicle. Attitude control of these ehicles is more challenging compared to quadrotor systems due to gyroscopic and coriolis terms. Typically, one rotor only, referred to as the tail rotor, has the ability to tilt to control the yaw moment of the ehicle, see for example [7], [5]. In [], the attitude of tri-rotor UAVs is controlled by using differential thrust concept. In [4], all rotors of the proposed tri-rotor system are tilting simultaneously by the same angle to attain yaw control. The UAV in [] controls the yaw angle by differentially tilting the two main rotors in the plane of symmetry. In this reference, a fixed up-right propeller is used at the tail to control the pitch moment. Few researchers hae identified the structure of tri-rotor UAV combined with full independent tilt-rotor capability. In this paper, we propose a noel tri-rotor platform, herein referred to as the Tri-rotor UAV, and then we discuss the design and control of the proposed system. The proposed ehicle can achiee full authority of torque and force ectoring by employing three rotors and three seros for tilt-rotor mechanism. This structure gies the ehicle high leel of maneuerability and flexibility for translational motion as well as attitude control. The rest of the paper is organized as follows. In Section II, a functional description of the ehicle and its design is discussed. A mathematical model that captures the dynamics of the UAV and goern the behaiour of the system is deried in Section III. The control system design is presented in Section IV and the simulation results is shown in Section V. The paper ends by conclusion in Section VI. II. SYSTEM STRUCTURE AND DESIGN The structure of the proposed Tri-rotor UAV is depicted in Figure. The ehicle has a triangular structure of three arms and at the end of each arm, a force generating unit is mounted to produce part of the required controlling force/torque. All three arms are identical of length l and the three force generating units are also identical. Each force generating unit consists of a fixed pitch propeller drien by a Brushless DC (BLDC) motor to generate thrust. The three motors can be powered by a single battery pack or three separate packs located at the center of the body. The propeller-motor assembly is attached to the body arm ia a sero motor that can rotate in a ertical plane to tilt the propeller-motor assembly with an angle α si in
2 Z b Y b Z e X b l Y e Figure. The design of the Tri-rotor UAV (D iew). X e the range π α si π, i,, to produce a horizontal component of the generated force, see Figure. All three propellers can be tilted independently to gie full authority of thrust ectoring. The system has six degree of freedom in which all moements can be achieed independently and directly by changing the norm of the generated thrust and the tilting angles. This configuration enables the ehicle body to stay aligned in the required direction regardless of the moement the UAV makes. Figure. Coordinate systems used to deelop the UAV dynamic model. X l Z l f α s Y l α s Z l f Y l Z l X l α s f - + α s i Xl Y l Figure 4. Local coordinate systems at the three propulsion units. Figure. Front iew of one arm. III. MATHEMATICAL MODELING To deelop the dynamic model of the UAV, we consider the following right hand coordinate systems shown in Figure : e: the generalized earth coordinate system of axes X e, Y e, Z e. b: the body fixed coordinate system in which the origin coincides with the centre of mass of the UAV. The axes of frame b are denoted by X b, Y b, Z b. In addition, we choose three right hand coordinate systems l i of axes X li, Y li, Z li with i,,. These coordinate systems are termed as local coordinate systems and located at the locations of the three propellers, see Figure 4. The origin of each local coordinate system coincides with the joining point between the UAV arm and the propulsion unit X li is extended outside the i th arm of the UAV and Z li is along the BLDC motor shaft axis when the tilting angle is zero. The rotation matrices between the defined coordinate systems are denoted by: R b e: the rotational matrix from frame e to frame b. R b l i : the rotational matrix from coordinate system l i to coordinate system b, i,,. In the sequel, we use superscript b, e and l i to denote the coordinate system in which ectors are expressed. The subscript i refers to the i th BLDC motor, sero motor or propeller as applies i,,. In order to obtain the dynamic equations of the UAV, we need to obtain forces and torques acting on the ehicle. We assume ery fast actuators and therefore the dynamics of the actuators are neglected. Forces There are two main forces acting on the UAV which are the propulsie force and the graitational force. The propulsie force: The total propulsie force F pσ is equal to the algebraic sum of the three indiidual propulsie forces generated from propellers. The indiidual propulsie forces of the three propellers expressed in the local coordinate systems can be written F l i p i k f ωm i sin(α si ), i,,. () k f ωm i cos(α si )
3 k f is the thrust to speed constant of the propeller and it is identical for all three propellers, ω mi is the rotational speed of the i th BLDC motor (the rotational speed of the motor equals the rotational speed of the propeller) and α si is the tilting angle of the i th Sero motor. In the body coordinate system, the indiidual propulsie forces are gien by: F b p i R b l i F l i P i, i,,. () From Figure 4, we can obtain the rotation matrices from the local coordinate systems l, l and l to the body coordinate system b R b l, () R b l, (4) R b l. (5) Using Equations () - (5), the total propulsie force is: and F b p Σ F b p + F b p + F b p (6) k f H f ρ. (7) H f, (8) ω m sin(α s ) ωm sin(α s ) ρ ω m sin(α s ) ωm cos(α s ). (9) ω m cos(α s ) ωm cos(α s ) The graity force: The graitational force in the generalized earth coordinate system is gien F e g. () g g is the graitational acceleration and is the total mass of the UAV. In the body coordinate system, we hae: F b g R b ef e g. () Using the general notation of rotation angles for the UAV attitude: Roll φ, Pitch θ and Yaw ψ around the axes X e, Y e and Z e respectiely, the graity force in the body system is gien by: F b g g H g () sin(θ ) H g sin(φ )cos(θ ). () cos(φ )cos(θ ) Now, the total force acting on the UAV and expressed in the body coordinate system is: Torques F b F b p Σ + F b g (4) k f H f ρ + g H g. (5) The two main torques acting on the UAV are the propulsie torque and the drag torque. The propulsie torque: The propulsie torque is the torque resulting from the generated propulsie force around the center of mass of the ehicle. For the case of the Tri-rotor UAV, we hae three identical arms and then the components of the propulsie torque are: τ b p i l b i F b p i, i,,. (6) l i b is the ector of the i th arm between the center of mass of the UAV and the propulsion unit expressed in the body coordinate system. Fb b i is obtained from Eq. (). Now, the total propulsie torque expressed in the body coordinate system is: τ b p Σ τ b p + τ b p + τ b p (7) k f H t ρ (8) H t l, (9) l is the length of the ehicle s arm ector measured between the center of mass of the UAV and the propulsion unit (identical for the three arms) and ρ is defined in Eq. (9). The drag torque: The drag torque is defined as the torque resulting from the aerodynamic drag forces exerted by the ambient fluid (air) on the propeller. Drag torque is in the opposite direction to the direction of rotation. In our case, the resulting drag torque on the i th propeller can be approximated by τ di k t ωm i we consider the BLDC motors dries the propeller directly and k t is the drag torque to speed constant resulting from the rotation of the propeller. In the local coordinate systems l i, the drag torque can be written τ l i d i k t ωm i sin(α si ), i,,. () k t ωm i cos(α si ) In the body coordinate system, the indiidual drag torques can be represented τ b d i R b l i τ l i d i, ()
4 Using definitions () - (5), the total drag torque in the body system is gien by: τ b d Σ τ b d + τ b d + τ b d () k t H f ρ, () H f and ρ are defined in (8) and (9) respectiely. Now, the total torque acting on the Tri-rotor and expressed in the body coordinate system is: τ b τ b p Σ + τ b d Σ (4) ( k f H t k t H f ) ρ. (5) Dynamic Model: Assuming that the Tri-rotor UAV is a rigid body of fixed mass, the ehicle s motion can be described by the Newton-Euler second s law in the body coordinate system for translational motion: ( ) F b υ b + S(ω b )υ b (6) for rotational motion: τ b I b ωb + S(ω b )I b ω b (7) υ b is translational elocity of the UAV, ω b is the angular elocity of the UAV, S(ω b ) is the skew matrix of the ector ω b and I b is the inertia matrix of the UAV all with respect to the fixed body coordinate system. Assuming no mass change oer time, I b is fixed. Now, Substituting F b and τ b from (5) and (5) gies: ( ) k f H f ρ + g H g υ b + S(ω b )υ b (8) (k f H t k t H f )ρ I b ωb + S(ω b )I b ω b (9) Let η and e be the attitude ector and the position ector of the UAV related to the earth coordinate system and defined η φ θ, e x y. () ψ z To fully describe the dynamic equations of the UAV, we hae the following relations from []: η Ψω b () e (R b e) υ b () Ψ is the rotational matrix between the angular elocity expressed in the body coordinate system ω b and the angular elocity in the earth coordinate system η. Ψ is gien in [] Ψ sin(φ )tan(θ ) cos(φ )tan(θ ) cos(φ ) sin(φ ), π < θ < π. sin(φ )sec(θ ) cos(φ )sec(θ ) () From the properties of the rotation matrix we hae: (R b e) R e b. (4) R e b is the rotation matrix from the body coordinate system b to the earth coordinate system e. Finally, from Equations (8) - (4), the dynamic model of the UAV can be written υ b gh g S(ω b )υ b + k f H f ρ (5) ω b (I b ) S(ω b )I b ω b + (I b ) (k f H t k t H f )ρ (6) η Ψω b (7) e R e b υb (8) This model of the UAV is written in the compact form in which eery state ariable is a ector of three components, i.e., x R, : υ b u, ω b p q, η φ θ, e x. w r ψ Equations (5) - (8) show a nonlinear model with coupling between the translational and rotational dynamics of the UAV. Moreoer, there is coupling between inputs and output channels in which all inputs act on all outputs. The system coupling along with the nonlinearity of the system makes the control design of the proposed Tri-rotor UAV a real challenge compared with other UAV configurations. On the other hand, if we consider the control problem of the UAV to be position tracking with attitude regulating, then the system is square in which we hae six actuators (three BLDC motor speeds and three sero angles) and six outputs (D position and three attitude angles). This highlights the positie aspect of the proposed configuration in terms of controller design compared to other UAV systems that are in general underactuated systems such as quadrotors. IV. CONTROL SYSTEM DESIGN In this section, we synthesize a controller for the Tri-rotor UAV. The system is linearized using input-output feedback method and then an H controller is designed for the linearized plant. For simplicity of expression, the superscript b and e as well as the subscript are not written unless it is necessary to aoid ambiguity. We consider the ector ρ as the input ector for the UAV system, i.e., u ρ, and we choose the output η y (9) and To implement input-output feedback linearization, we hae: ẏ y () Ψω η R e b υ (4) Ψω ÿ y () + Ψ ω (R e b )υ + Re b υ y z (4) From the general properties of the rotation matrix, we hae: R e b Re b S(ωb ) (4)
5 and then we write: Ψω y () + Ψ(I S(ω)Iω + I (k f H t k t H f )ρ) R e b S(ω)υ + Re b (gh g S(ω)υ + k f H f ρ) [( Ψ ΨI S(ω)I ) ] [ ω ΨI ( )] k f H t k t H f gr e b H + k f g R e b H ρ f (4) Ψ Ψ φ + Ψ θ (44) φ θ and φ, θ are obtained from Eq. (7) φ η θ Ψω b. (45) ψ We define the matrix β(x) [ ΨI ( )] k f H t k t H f β(x) k f R e b H f (46) We hae det[β(x)] and the inerse β (x) exists always for all x R x represents the states of the system in the compact form: x [ υ ω η ] T The relatie degree of the system in the compact form is r r +r + 4 which is equal to the number of states in the compact form of the dynamic equations, and there is no zero dynamics. Choosing any other set of outputs will generate zero dynamics and this justifies the selection of the output set y [ η ] T. To [ linearize ] the system, we choose a new ϑ control input ϑ, and we write our desired linearized dynamics ϑ y () ϑ. (47) From Eq. (4) we can write the feedback linearisation law [( Ψ u β (ϑ ΨI S(ω)I ) ]) ω gr e b H. (48) g The centralized input-output feedback linearization handles the coupling without the need for strict assumption on operating point to decouple the system. The linearized model in the compact form is gien ζ ζ + ϑ (49) y ζ (5) It is always assumed that π/ θ π/. η ζ η R, y η R 6, ϑ [ ϑ ϑ ] R 6. The linearized plant is a double integrator representing single degree of freedom for transitional and rotational motion. The H loop-shaping design is inoked to synthesize a controller for the linearized system. For selection of weights to shape the linearized plant, we consider the following control design specifications: high loop-gain at low frequency for good reference tracking and disturbance rejection. low loop-gain at high frequency for robustness against unmodeled dynamics and output measurement noise. reasonable bandwidth for fast response. An algorithm proposed in [4] is inoked to simultaneously optimize the synthesis of loop-shaping weights and a stabilizing controller. This algorithm captures the design specification listed aboe in a systematic manner while trying to maximize the robust stability margin of the closed-loop system. We fix the post-compensator weight to a low-pass filter on all channels and use the algorithm to optimize the pre-compensator weights for all channels. The optimized precompensator for each channel is w 4/(s + 5), W w I 6. The achieed robust stability margin is.75 which means a tolerance of approximately 7.5% of coprime factor uncertainty. V. SIMULATION RESULTS To demonstrate numerical results, we simulate the Tri-rotor UAV along with the designed controller in Simulink. Figure 5 depicts the block digram for the simulation T η r r is the desired reference attitude and position respectiely. Figure 5. UAV. η r H Loop r + ϑ Feedback u Shaping Linearization Controller Law - ω, η Tri-rotor UAV η Simulation block diagram for the control design of the Tri-rotor Figure 6 shows the singular alues of the linearized plant, the shaped plant and the synthesized controller. Figure 7 depicts the performance of the UAV for a scenario of horizontal hoering at 5 m height. The ehicle was at nonzero initial position and initial attitude as shown. The speed of the BLDC motors and the angles of the sero motors to stabilize the ehicle and track the reference signals are shown in Figure 8. The controller shows good performance with tracking in all channels. The seros and BLDC motors are not saturated and operate within their physical limits of ±9 for the seros and rpm for the BLDC motors.
6 Singular Values (db) Frequency (rad/sec) Linearized system Shaped plant Controller Figure 6. Singular alue plots for the linearized system, the shaped system and the controller. x (m) y (m) z (m) φ (deg) θ (deg) ψ (deg) Figure 7. Simulation plots of the UAV position and attitude using the synthesized controller of H loop shaping control associated with classical feedback linearization. Sero Angles (Deg) Motors speed (RPM) Figure 8. The performance of the actuators (seros and BLDC motors) to track the specified reference input of (,,) deg for attitude, and (,,5) m for position coming from non-zero initial point. α s α s α s ω m ω m ω m VI. CONCLUSION In this paper, a noel tri-rotor UAV is proposed. The proposed UAV has six actuators with full authority of thrust and torque ectoring. The mathematical model of the proposed design is non-linear and it indicates coupling between translational and rotational motion. The nonlinear model of the UAV is linearized by input-output feedback linearization. This procedure cancels the nonlinearity of all channels simultaneously without further conditions for specific operating point which is the case when we handle channels indiidually. The linearized plant is a double integrator that is controlled using H loop-design procedure. The result is erified ia simulations. More complex feedback linearization techniques (such as robust feedback linearization in [5]) can be used in the same manner to aoid linearizing the system to a double integrator. REFERENCES [] A. Das, K. Subbarao, and F. lewis, Dynamic inersion with zerodynamics stabilisation for quadrotor contrl, IET Control Theory and Applications, ol., pp. 4, 9. [] D. J. Pines and F. Bohorquez, Challenges facing future micro-airehicle deelopment, Journal of Aircraft, ol. 4, p. 9 5, 6. [] K. P. Valaanis, Ed., Adances in Unmanned Aerial Vehicles: State of the Art and the Road to Autonomy, ser. International Series on Intelligent Systems, Control, and Automation: Science and Engineering. Springer, 7, ol.. [4] J. Escareno, A. Sanchez, O. Garcia, and R. Lozano, Triple tilting rotor mini-uav: Modeling and embedded control of the attitude, in American Control Conference, 8, pp [5] S. Salazar-Cruz, R. Lozano, and J. Escareño, Stabilization and nonlinear control for a noel trirotor mini-aircraft, Control Engineering Practice, ol. 7, no. 8, pp , August 9. [6] R. Huang, Y. Liu, and J. J. Zhu, Guidance, naigation, and control system design for tripropeller ertical-takeoff-and-landing unmanned air ehicle, Journal of Aircraft, ol. 46, no. 6, pp , Noember- December 9. [7] D.-W. Yoo, H.-D. Oh, D.-Y. Won, and M.-J. Tahk, Dynamic modeling and stabilization technique for tri-rotor unmanned aerial ehicles. International Journal of Aeronautical and Space Science., ol., pp ,. [8] P. Vanblyenburgh, UAVs: An Oeriew, Air & Space Europe, ol., no. 5-6, pp. 4 47, September 999. [9] B. Crowther, A. Lanzon, M. Maya-Gonzalez, and D. Langkamp, Kinematic analysis and control design for a non planar multirotor ehicle, Journal of Guidance, Control, and Dynamics, ol. 4, no. 4, pp. 57 7,. [] F. Lin, W. Zhang, and R. D. Brandt, Robust hoering control of a PVTOL aircraft, Control Systems Technology, IEEE Transactions on, ol. 7, no., pp. 4 5, August. [] P. Fan, X. Wang, and K.-Y. Cai, Design and control of a tri-rotor aircraft, in Control and Automation (ICCA), 8th IEEE International Conference on, June, pp [] Z. Prime, J. Sherwood, M. Smith, and A. Stabile, Remote control (rc) ertical take-off and landing (tol) model aircraft, LeelIV Honours Project Final Report, Uniersity of Adelaide, Adelaide, Australia, October 5. [] G. D. Padfield, Helicopter Flight Dynamics: The Theory and Application of Flying Qualities and Simulation Modeling, ser. Education Series. AIAA, 996. [4] A. Lanzon, Weight optimisation in H loop-shaping, Automatica, ol. 4, no. 7, pp. 8, 5. [5] A. L. D. Franco, H. Bourlès, E. R. De-Pieri, and H. Guillard, Robust nonlinear control associating robust feedback linearization and H control, IEEE Transactions on Automatic Control, ol. 5, no. 7, pp. 6, 6.
Design and Control of Novel Tri-rotor UAV
UKACC International Conference on Control Cardiff, UK, -5 September Design and Control of Novel Tri-rotor UAV Mohamed Kara Mohamed School of Electrical and Electronic Engineering The University of Manchester
More informationDynamic Modeling and Stabilization Techniques for Tri-Rotor Unmanned Aerial Vehicles
Technical Paper Int l J. of Aeronautical & Space Sci. 11(3), 167 174 (010) DOI:10.5139/IJASS.010.11.3.167 Dynamic Modeling and Stabilization Techniques for Tri-Rotor Unmanned Aerial Vehicles Dong-Wan Yoo*,
More informationMathematical Modelling and Dynamics Analysis of Flat Multirotor Configurations
Mathematical Modelling and Dynamics Analysis of Flat Multirotor Configurations DENIS KOTARSKI, Department of Mechanical Engineering, Karlovac University of Applied Sciences, J.J. Strossmayera 9, Karlovac,
More informationDesign and Control of a Novel Unmanned Ground Vehicle
Design and Control of a Novel Unmanned Ground Vehicle M. Osinuga and A. Lanzon Control Systems Centre, School of Electrical and Electronic Engineering, The University of Manchester, Sackville Street, Manchester,
More informationThree-dimensional Guidance Law for Formation Flight of UAV
ICCAS25 Three-dimensional Guidance aw for Formation Flight of UAV Byoung-Mun Min * and Min-Jea Tahk ** * Department of Aerospace Engineering KAIST Daejeon Korea (Tel : 82-42-869-3789; E-mail: bmmin@fdcl.kaist.ac.kr)
More informationNonlinear Disturbance Decoupling for a Mobile Robotic Manipulator over Uneven Terrain
Nonlinear Disturbance Decoupling for a Mobile Robotic Manipulator oer Uneen Terrain Joel Jimenez-Lozano Bill Goodwine Department of Aerospace and Mechanical Engineering Uniersity of Noe Dame Noe Dame IN
More informationChapter 2 Review of Linear and Nonlinear Controller Designs
Chapter 2 Review of Linear and Nonlinear Controller Designs This Chapter reviews several flight controller designs for unmanned rotorcraft. 1 Flight control systems have been proposed and tested on a wide
More informationRealization of Hull Stability Control System for Continuous Track Vehicle with the Robot Arm
Adanced Science and Technology Letters Vol.86 (Ubiquitous Science and Engineering 05), pp.96-0 http://dx.doi.org/0.457/astl.05.86.0 Realization of Hull Stability Control System for Continuous Track Vehicle
More informationResearch on Balance of Unmanned Aerial Vehicle with Intelligent Algorithms for Optimizing Four-Rotor Differential Control
2019 2nd International Conference on Computer Science and Advanced Materials (CSAM 2019) Research on Balance of Unmanned Aerial Vehicle with Intelligent Algorithms for Optimizing Four-Rotor Differential
More informationQuadcopter Dynamics 1
Quadcopter Dynamics 1 Bréguet Richet Gyroplane No. 1 1907 Brothers Louis Bréguet and Jacques Bréguet Guidance of Professor Charles Richet The first flight demonstration of Gyroplane No. 1 with no control
More informationModelling of Opposed Lateral and Longitudinal Tilting Dual-Fan Unmanned Aerial Vehicle
Modelling of Opposed Lateral and Longitudinal Tilting Dual-Fan Unmanned Aerial Vehicle N. Amiri A. Ramirez-Serrano R. Davies Electrical Engineering Department, University of Calgary, Canada (e-mail: namiri@ucalgary.ca).
More informationMathematical Modelling of Multirotor UAV
Mathematical Modelling of Multirotor UAV DENIS KOTARSKI, Mechanical Engineering, Karlovac University of Applied Sciences Trg J.J. Strossmayera 9, CROATIA, denis.kotarski@vuka.hr PETAR PILJEK, Faculty of
More informationDynamic modeling and control system design for tri-rotor UAV
Loughborough University Institutional Repository Dynamic modeling and control system design for tri-rotor UAV This item was submitted to Loughborough University's Institutional Repository by the/an author.
More informationNonlinear Landing Control for Quadrotor UAVs
Nonlinear Landing Control for Quadrotor UAVs Holger Voos University of Applied Sciences Ravensburg-Weingarten, Mobile Robotics Lab, D-88241 Weingarten Abstract. Quadrotor UAVs are one of the most preferred
More informationPosition in the xy plane y position x position
Robust Control of an Underactuated Surface Vessel with Thruster Dynamics K. Y. Pettersen and O. Egeland Department of Engineering Cybernetics Norwegian Uniersity of Science and Technology N- Trondheim,
More informationThe PVTOL Aircraft. 2.1 Introduction
2 The PVTOL Aircraft 2.1 Introduction We introduce in this chapter the well-known Planar Vertical Take-Off and Landing (PVTOL) aircraft problem. The PVTOL represents a challenging nonlinear systems control
More informationTriple Tilting Rotor mini-uav: Modeling and Embedded Control of the Attitude
28 American Control Conference Westin Seattle Hotel, Seattle, Washington, USA June -3, 28 ThC6.4 Triple Tilting Rotor mini-uav: Modeling and Embedded Control of the Attitude J. Escareño, A. Sanchez, O.
More informationA Comparison of Closed-Loop Performance of Multirotor Configurations Using Non-Linear Dynamic Inversion Control
Aerospace 2015, 2, 325-352; doi:10.3390/aerospace2020325 OPEN ACCESS aerospace ISSN 2226-4310 www.mdpi.com/journal/aerospace Article A Comparison of Closed-Loop Performance of Multirotor Configurations
More informationInvestigation of the Dynamics and Modeling of a Triangular Quadrotor Configuration
Investigation of the Dynamics and Modeling of a Triangular Quadrotor Configuration TONI AXELSSON Master s Thesis at Aerospace Engineering Supervisor: Arne Karlsson Examiner: Arne Karlsson ISSN 1651-7660
More informationAdaptive Robust Control (ARC) for an Altitude Control of a Quadrotor Type UAV Carrying an Unknown Payloads
2 th International Conference on Control, Automation and Systems Oct. 26-29, 2 in KINTEX, Gyeonggi-do, Korea Adaptive Robust Control (ARC) for an Altitude Control of a Quadrotor Type UAV Carrying an Unknown
More informationAerial Robotics. Vision-based control for Vertical Take-Off and Landing UAVs. Toulouse, October, 2 nd, Henry de Plinval (Onera - DCSD)
Aerial Robotics Vision-based control for Vertical Take-Off and Landing UAVs Toulouse, October, 2 nd, 2014 Henry de Plinval (Onera - DCSD) collaborations with P. Morin (UPMC-ISIR), P. Mouyon (Onera), T.
More informationFurther results on global stabilization of the PVTOL aircraft
Further results on global stabilization of the PVTOL aircraft Ahmad Hably, Farid Kendoul 2, Nicolas Marchand, and Pedro Castillo 2 Laboratoire d Automatique de Grenoble, ENSIEG BP 46, 3842 Saint Martin
More informationNonlinear Control of a Quadrotor Micro-UAV using Feedback-Linearization
Proceedings of the 2009 IEEE International Conference on Mechatronics. Malaga, Spain, April 2009. Nonlinear Control of a Quadrotor Micro-UAV using Feedback-Linearization Holger Voos University of Applied
More informationDesign and Control of UAV Systems: A Tri-Rotor UAV Case Study
Design and Control of UAV Systems: A Tri-Rotor UAV Case Study A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences
More informationModelling, Design and Simulation of a Quadrotor with Tilting Rotors Actuated by a Memory Shape Wire
Modelling, Design and Simulation of a Quadrotor with Tilting Rotors Actuated by a Memory Shape Wire Henrique Bezerra Diogenes, hbd.ita@gmail.com 1 Davi Antonio dos Santos, davists@ita.br 1 1 Instituto
More informationNonlinear Trajectory Tracking for Fixed Wing UAVs via Backstepping and Parameter Adaptation. Wei Ren
AIAA Guidance, Naigation, and Control Conference and Exhibit 5-8 August 25, San Francisco, California AIAA 25-696 Nonlinear Trajectory Tracking for Fixed Wing UAVs ia Backstepping and Parameter Adaptation
More informationQUADROTOR: FULL DYNAMIC MODELING, NONLINEAR SIMULATION AND CONTROL OF ATTITUDES
QUADROTOR: FULL DYNAMIC MODELING, NONLINEAR SIMULATION AND CONTROL OF ATTITUDES Somayeh Norouzi Ghazbi,a, Ali Akbar Akbari 2,a, Mohammad Reza Gharib 3,a Somaye_noroozi@yahoo.com, 2 Akbari@um.ac.ir, 3 mech_gharib@yahoo.com
More informationSimulation of Backstepping-based Nonlinear Control for Quadrotor Helicopter
APPLICATIONS OF MODELLING AND SIMULATION http://amsjournal.ams-mss.org eissn 2680-8084 VOL 2, NO. 1, 2018, 34-40 Simulation of Backstepping-based Nonlinear Control for Quadrotor Helicopter M.A.M. Basri*,
More informationDesign and modelling of an airship station holding controller for low cost satellite operations
AIAA Guidance, Navigation, and Control Conference and Exhibit 15-18 August 25, San Francisco, California AIAA 25-62 Design and modelling of an airship station holding controller for low cost satellite
More informationENHANCED PROPORTIONAL-DERIVATIVE CONTROL OF A MICRO QUADCOPTER
ENHANCED PROPORTIONAL-DERIVATIVE CONTROL OF A MICRO QUADCOPTER Norman L. Johnson and Kam K. Leang Department of Mechanical Engineering University of Nevada, Reno Reno, Nevada 897-312, USA ABSTRACT This
More informationUAV Coordinate Frames and Rigid Body Dynamics
Brigham Young University BYU ScholarsArchive All Faculty Publications 24-- UAV oordinate Frames and Rigid Body Dynamics Randal Beard beard@byu.edu Follow this and additional works at: https://scholarsarchive.byu.edu/facpub
More informationMulti-layer Flight Control Synthesis and Analysis of a Small-scale UAV Helicopter
Multi-layer Flight Control Synthesis and Analysis of a Small-scale UAV Helicopter Ali Karimoddini, Guowei Cai, Ben M. Chen, Hai Lin and Tong H. Lee Graduate School for Integrative Sciences and Engineering,
More informationDynamic Modeling of Fixed-Wing UAVs
Autonomous Systems Laboratory Dynamic Modeling of Fixed-Wing UAVs (Fixed-Wing Unmanned Aerial Vehicles) A. Noth, S. Bouabdallah and R. Siegwart Version.0 1/006 1 Introduction Dynamic modeling is an important
More informationHover Control for Helicopter Using Neural Network-Based Model Reference Adaptive Controller
Vol.13 No.1, 217 مجلد 13 العدد 217 1 Hover Control for Helicopter Using Neural Network-Based Model Reference Adaptive Controller Abdul-Basset A. Al-Hussein Electrical Engineering Department Basrah University
More informationQuadrotor Modeling and Control
16-311 Introduction to Robotics Guest Lecture on Aerial Robotics Quadrotor Modeling and Control Nathan Michael February 05, 2014 Lecture Outline Modeling: Dynamic model from first principles Propeller
More informationCDS 101/110a: Lecture 8-1 Frequency Domain Design
CDS 11/11a: Lecture 8-1 Frequency Domain Design Richard M. Murray 17 November 28 Goals: Describe canonical control design problem and standard performance measures Show how to use loop shaping to achieve
More informationTrajectory-tracking control of a planar 3-RRR parallel manipulator
Trajectory-tracking control of a planar 3-RRR parallel manipulator Chaman Nasa and Sandipan Bandyopadhyay Department of Engineering Design Indian Institute of Technology Madras Chennai, India Abstract
More information(a) Taking the derivative of the position vector with respect to time, we have, in SI units (m/s),
Chapter 4 Student Solutions Manual. We apply Eq. 4- and Eq. 4-6. (a) Taking the deriatie of the position ector with respect to time, we hae, in SI units (m/s), d ˆ = (i + 4t ˆj + tk) ˆ = 8tˆj + k ˆ. dt
More informationDesign and Implementation of an Unmanned Tail-sitter
1 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Congress Center Hamburg Sept 8 - Oct, 1. Hamburg, Germany Design and Implementation of an Unmanned Tail-sitter Roman Bapst,
More informationCS491/691: Introduction to Aerial Robotics
CS491/691: Introduction to Aerial Robotics Topic: Midterm Preparation Dr. Kostas Alexis (CSE) Areas of Focus Coordinate system transformations (CST) MAV Dynamics (MAVD) Navigation Sensors (NS) State Estimation
More informationChapter 2 Coordinate Systems and Transformations
Chapter 2 Coordinate Systems and Transformations 2.1 Coordinate Systems This chapter describes the coordinate systems used in depicting the position and orientation (pose) of the aerial robot and its manipulator
More informationA Nonlinear Control Law for Hover to Level Flight for the Quad Tilt-rotor UAV
Preprints of the 19th World Congress The International Federation of Automatic Control A Nonlinear Control Law for Hover to Level Flight for the Quad Tilt-rotor UAV Gerardo R. Flores-Colunga Rogelio Lozano-Leal
More informationImproving Leader-Follower Formation Control Performance for Quadrotors. By Wesam M. Jasim Alrawi
Improving Leader-Follower Formation Control Performance for Quadrotors By Wesam M. Jasim Alrawi A thesis submitted for the degree of Doctor of Philosophy School of Computer Science and Electronic Engineering
More informationImproved Quadcopter Disturbance Rejection Using Added Angular Momentum
Improved Quadcopter Disturbance Rejection Using Added Angular Momentum Nathan Bucki and Mark W. Mueller Abstract This paper presents a novel quadcopter design with an added momentum wheel for enhanced
More informationLinear Momentum and Collisions Conservation of linear momentum
Unit 4 Linear omentum and Collisions 4.. Conseration of linear momentum 4. Collisions 4.3 Impulse 4.4 Coefficient of restitution (e) 4.. Conseration of linear momentum m m u u m = u = u m Before Collision
More informationCHAPTER 1. Introduction
CHAPTER 1 Introduction Linear geometric control theory was initiated in the beginning of the 1970 s, see for example, [1, 7]. A good summary of the subject is the book by Wonham [17]. The term geometric
More informationNonlinear Attitude and Position Control of a Micro Quadrotor using Sliding Mode and Backstepping Techniques
3rd US-European Competition and Workshop on Micro Air Vehicle Systems (MAV7 & European Micro Air Vehicle Conference and light Competition (EMAV27, 17-21 September 27, Toulouse, rance Nonlinear Attitude
More informationDifferent Approaches of PID Control UAV Type Quadrotor
Different Approaches of PD Control UAV ype Quadrotor G. Szafranski, R. Czyba Silesian University of echnology, Akademicka St 6, Gliwice, Poland ABSRAC n this paper we focus on the different control strategies
More informationAutonomous Mobile Robot Design
Autonomous Mobile Robot Design Topic: Micro Aerial Vehicle Dynamics Dr. Kostas Alexis (CSE) Goal of this lecture The goal of this lecture is to derive the equations of motion that describe the motion of
More informationDigital Passive Attitude and Altitude Control Schemes for Quadrotor Aircraft
Institute for Software Integrated Systems Vanderbilt University Nashville, Tennessee, 37235 Digital Passive Attitude and Altitude Control Schemes for Quadrotor Aircraft Nicholas Kottenstette, and Joseph
More informationAdaptive Trim and Trajectory Following for a Tilt-Rotor Tricopter Ahmad Ansari, Anna Prach, and Dennis S. Bernstein
7 American Control Conference Sheraton Seattle Hotel May 4 6, 7, Seattle, USA Adaptive Trim and Trajectory Following for a Tilt-Rotor Tricopter Ahmad Ansari, Anna Prach, and Dennis S. Bernstein Abstract
More informationExperiments on Stabilization of the Hanging Equilibrium of a 3D Asymmetric Rigid Pendulum
Proceedings of the 25 IEEE Conference on Control Applications Toronto, Canada, August 28-3, 25 MB4.5 Experiments on Stabilization of the Hanging Equilibrium of a 3D Asymmetric Rigid Pendulum Mario A. Santillo,
More informationRobust Nonlinear Real-time Control Strategy to Stabilize a PVTOL Aircraft in Crosswind
The IEEE/RSJ International Conference on Intelligent Robots and Systems October 8-,, Taipei, Taiwan Robust Nonlinear Real-time Control Strategy to Stabilize a PVTOL Aircraft in Crosswind Laura E. Muñoz
More informationModel Reference Adaptive Control of Underwater Robotic Vehicle in Plane Motion
Proceedings of the 11th WSEAS International Conference on SSTEMS Agios ikolaos Crete Island Greece July 23-25 27 38 Model Reference Adaptive Control of Underwater Robotic Vehicle in Plane Motion j.garus@amw.gdynia.pl
More informationModeling and Sliding Mode Control of a Quadrotor Unmanned Aerial Vehicle
Modeling and Sliding Mode Control of a Quadrotor Unmanned Aerial Vehicle Nour BEN AMMAR, Soufiene BOUALLÈGUE and Joseph HAGGÈGE Research Laboratory in Automatic Control LA.R.A), National Engineering School
More informationAn Introduction to Three-Dimensional, Rigid Body Dynamics. James W. Kamman, PhD. Volume II: Kinetics. Unit 3
Summary An Introduction to hree-dimensional, igid ody Dynamics James W. Kamman, PhD Volume II: Kinetics Unit Degrees of Freedom, Partial Velocities and Generalized Forces his unit defines the concepts
More informationModeling and Control Strategy for the Transition of a Convertible Tail-sitter UAV
Modeling and Control Strategy for the Transition of a Convertible Tail-sitter UAV J. Escareño, R.H. Stone, A. Sanchez and R. Lozano Abstract This paper addresses the problem of the transition between rotary-wing
More informationNonlinear and Neural Network-based Control of a Small Four-Rotor Aerial Robot
Nonlinear and Neural Network-based Control of a Small Four-Rotor Aerial Robot Holger Voos Abstract Small four-rotor aerial robots, so called quadrotor UAVs, have an enormous potential for all kind of neararea
More informationQuaternion-Based Tracking Control Law Design For Tracking Mode
A. M. Elbeltagy Egyptian Armed forces Conference on small satellites. 2016 Logan, Utah, USA Paper objectives Introduction Presentation Agenda Spacecraft combined nonlinear model Proposed RW nonlinear attitude
More informationChapter 1: Kinematics of Particles
Chapter 1: Kinematics of Particles 1.1 INTRODUCTION Mechanics the state of rest of motion of bodies subjected to the action of forces Static equilibrium of a body that is either at rest or moes with constant
More informationA. unchanged increased B. unchanged unchanged C. increased increased D. increased unchanged
IB PHYSICS Name: DEVIL PHYSICS Period: Date: BADDEST CLASS ON CAMPUS CHAPTER B TEST REVIEW. A rocket is fired ertically. At its highest point, it explodes. Which one of the following describes what happens
More informationControl of a Quadrotor Mini-Helicopter via Full State Backstepping Technique
Proceedings of the 45th IEEE Conference on Decision & Control Manchester Grand Hyatt Hotel San Diego, CA, USA, December 3-5, 006 Control of a Quadrotor Mini-Helicopter via Full State Backstepping Technique
More informationTrajectory Estimation for Tactical Ballistic Missiles in Terminal Phase Using On-line Input Estimator
Proc. Natl. Sci. Counc. ROC(A) Vol. 23, No. 5, 1999. pp. 644-653 Trajectory Estimation for Tactical Ballistic Missiles in Terminal Phase Using On-line Input Estimator SOU-CHEN LEE, YU-CHAO HUANG, AND CHENG-YU
More informationAutonomous Mobile Robot Design
Autonomous Mobile Robot Design Topic: Guidance and Control Introduction and PID Loops Dr. Kostas Alexis (CSE) Autonomous Robot Challenges How do I control where to go? Autonomous Mobile Robot Design Topic:
More informationTracking Control for Robot Manipulators with Kinematic and Dynamic Uncertainty
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seille, Spain, December 2-5, 2005 WeB3.3 Tracking Control for Robot Manipulators with Kinematic
More informationEstimation and Control of a Quadrotor Attitude
Estimation and Control of a Quadrotor Attitude Bernardo Sousa Machado Henriques Mechanical Engineering Department, Instituto Superior Técnico, Lisboa, Portugal E-mail: henriquesbernardo@gmail.com Abstract
More informationReversal in time order of interactive events: Collision of inclined rods
Reersal in time order of interactie eents: Collision of inclined rods Published in The European Journal of Physics Eur. J. Phys. 27 819-824 http://www.iop.org/ej/abstract/0143-0807/27/4/013 Chandru Iyer
More informationMAE 142 Homework #5 Due Friday, March 13, 2009
MAE 142 Homework #5 Due Friday, March 13, 2009 Please read through the entire homework set before beginning. Also, please label clearly your answers and summarize your findings as concisely as possible.
More informationAN INTEGRATOR BACKSTEPPING CONTROLLER FOR A STANDARD HELICOPTER YITAO LIU THESIS
AN INEGRAOR BACKSEPPING CONROLLER FOR A SANDARD HELICOPER BY YIAO LIU HESIS Submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Computer Engineering
More informationarxiv: v1 [cs.ro] 15 Oct 2018
Towards Efficient Full Pose Omnidirectionality with Overactuated MAVs Karen Bodie, Zachary Taylor, Mina Kamel, and Roland Siegwart Autonomous Systems Lab, ETH Zürich, Switzerland arxiv:8.68v [cs.ro] Oct
More informationModeling the 3-DOF Dynamics of an Electrodynamic Maglev Suspension System with a Passive Sled
Modeling the 3-DOF Dynamics of an Electrodynamic Maglev Suspension System with a Passive Sled Jeroen de Boeij 3, Héctor Gutiérrez *1, Rahul Agarwal 2 and Maarten Steinbuch 3 1 Department of Mechanical
More informationRobot Control Basics CS 685
Robot Control Basics CS 685 Control basics Use some concepts from control theory to understand and learn how to control robots Control Theory general field studies control and understanding of behavior
More informationMulticopter Design Optimization and Validation
Modeling, Identification and Control, Vol 36, No 2, 2015, pp 67 79, ISSN 1890 1328 Multicopter Design Optimization and Validation Øyvind Magnussen Morten Ottestad Geir Hovland University of Agder, Faculty
More informationNonlinear Robust Tracking Control of a Quadrotor UAV on SE(3)
22 American Control Conference Fairmont Queen Elizabeth Montréal Canada June 27-June 29 22 Nonlinear Robust Tracking Control of a Quadrotor UAV on SE(3) Taeyoung Lee Melvin Leok and N. Harris McClamroch
More informationChapter 4 The Equations of Motion
Chapter 4 The Equations of Motion Flight Mechanics and Control AEM 4303 Bérénice Mettler University of Minnesota Feb. 20-27, 2013 (v. 2/26/13) Bérénice Mettler (University of Minnesota) Chapter 4 The Equations
More informationOPTIMAL TRAJECTORY PLANNING AND LQR CONTROL FOR A QUADROTOR UAV. Ian D. Cowling James F. Whidborne Alastair K. Cooke
OPTIMAL TRAJECTORY PLANNING AND LQR CONTROL FOR A QUADROTOR UAV Ian D. Cowling James F. Whidborne Alastair K. Cooke Department of Aerospace Sciences, Cranfield University, Bedfordshire, MK43 AL, U.K Abstract:
More informationPosition Control for a Class of Vehicles in SE(3)
Position Control for a Class of Vehicles in SE(3) Ashton Roza, Manfredi Maggiore Abstract A hierarchical design framework is presented to control the position of a class of vehicles in SE(3) that are propelled
More informationRevised Propeller Dynamics and Energy-Optimal Hovering in a Monospinner
Proceedings of the 4 th International Conference of Control, Dynamic Systems, and Robotics (CDSR'17) Toronto, Canada August 21 23, 2017 Paper No. 135 DOI: 10.11159/cdsr17.135 Revised Propeller Dynamics
More informationTrajectory tracking & Path-following control
Cooperative Control of Multiple Robotic Vehicles: Theory and Practice Trajectory tracking & Path-following control EECI Graduate School on Control Supélec, Feb. 21-25, 2011 A word about T Tracking and
More informationQuadrotors Flight Formation Control Using a Leader-Follower Approach*
23 European Conference (ECC) July 7-9, 23, Zürich, Switzerland. Quadrotors Flight Formation Using a Leader-Follower Approach* D. A. Mercado, R. Castro and R. Lozano 2 Abstract In this paper it is presented
More informationRobot Dynamics - Rotary Wing UAS: Control of a Quadrotor
Robot Dynamics Rotary Wing AS: Control of a Quadrotor 5-85- V Marco Hutter, Roland Siegwart and Thomas Stastny Robot Dynamics - Rotary Wing AS: Control of a Quadrotor 7..6 Contents Rotary Wing AS. Introduction
More information3D Pendulum Experimental Setup for Earth-based Testing of the Attitude Dynamics of an Orbiting Spacecraft
3D Pendulum Experimental Setup for Earth-based Testing of the Attitude Dynamics of an Orbiting Spacecraft Mario A. Santillo, Nalin A. Chaturvedi, N. Harris McClamroch, Dennis S. Bernstein Department of
More informationA Model-Free Control System Based on the Sliding Mode Control Method with Applications to Multi-Input-Multi-Output Systems
Proceedings of the 4 th International Conference of Control, Dynamic Systems, and Robotics (CDSR'17) Toronto, Canada August 21 23, 2017 Paper No. 119 DOI: 10.11159/cdsr17.119 A Model-Free Control System
More informationTTK4190 Guidance and Control Exam Suggested Solution Spring 2011
TTK4190 Guidance and Control Exam Suggested Solution Spring 011 Problem 1 A) The weight and buoyancy of the vehicle can be found as follows: W = mg = 15 9.81 = 16.3 N (1) B = 106 4 ( ) 0.6 3 3 π 9.81 =
More informationBackstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor
Proceedings of the 2005 IEEE International Conference on Robotics and Automation Barcelona, Spain, April 2005 Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor Samir Bouabdallah
More informationModeling and Control of mini UAV
Modeling and Control of mini UAV Gerardo Ramon Flores Colunga, A. Guerrero, Juan Antonio Escareño, Rogelio Lozano To cite this version: Gerardo Ramon Flores Colunga, A. Guerrero, Juan Antonio Escareño,
More informationStatement: This paper will also be published during the 2017 AUTOREG conference.
Model Predictie Control for Autonomous Lateral Vehicle Guidance M. Sc. Jochen Prof. Dr.-Ing. Steffen Müller TU Berlin, Institute of Automotie Engineering Germany Statement: This paper will also be published
More informationROBUST SECOND ORDER SLIDING MODE CONTROL
ROBUST SECOND ORDER SLIDING MODE CONTROL FOR A QUADROTOR CONSIDERING MOTOR DYNAMICS Nader Jamali Soufi Amlashi 1, Mohammad Rezaei 2, Hossein Bolandi 2 and Ali Khaki Sedigh 3 1 Department of Control Engineering,
More information3. What is the minimum work needed to push a 950-kg car 310 m up along a 9.0 incline? Ignore friction. Make sure you draw a free body diagram!
Wor Problems Wor and Energy HW#. How much wor is done by the graitational force when a 280-g pile drier falls 2.80 m? W G = G d cos θ W = (mg)d cos θ W = (280)(9.8)(2.80) cos(0) W = 7683.2 W 7.7 0 3 Mr.
More informationUNDERSTAND MOTION IN ONE AND TWO DIMENSIONS
SUBAREA I. COMPETENCY 1.0 UNDERSTAND MOTION IN ONE AND TWO DIMENSIONS MECHANICS Skill 1.1 Calculating displacement, aerage elocity, instantaneous elocity, and acceleration in a gien frame of reference
More informationADAPTIVE SLIDING MODE CONTROL OF UNMANNED FOUR ROTOR FLYING VEHICLE
International Journal of Robotics and Automation, Vol. 30, No. 2, 205 ADAPTIVE SLIDING MODE CONTROL OF UNMANNED FOUR ROTOR FLYING VEHICLE Shafiqul Islam, Xiaoping P. Liu, and Abdulmotaleb El Saddik Abstract
More informationSpace Probe and Relative Motion of Orbiting Bodies
Space robe and Relatie Motion of Orbiting Bodies Eugene I. Butiko Saint etersburg State Uniersity, Saint etersburg, Russia E-mail: e.butiko@phys.spbu.ru bstract. Seeral possibilities to launch a space
More informationMini coaxial rocket-helicopter: aerodynamic modeling, hover control, and implementation
Mini coaxial rocket-helicopter: aerodynamic modeling, hover control, and implementation E. S. Espinoza,2, O. Garcia, R. Lozano,3, and A. Malo Laboratoire Franco-Mexicain d Informatique et Automatique,
More informationENGINEERING COUNCIL DYNAMICS OF MECHANICAL SYSTEMS D225 TUTORIAL 3 CENTRIPETAL FORCE
ENGINEERING COUNCIL DYNAMICS OF MECHANICAL SYSTEMS D5 TUTORIAL CENTRIPETAL FORCE This tutorial examines the relationship between inertia and acceleration. On completion of this tutorial you should be able
More informationDynamic Model and Control of Quadrotor in the Presence of Uncertainties
University of South Carolina Scholar Commons Theses and Dissertations 5-2017 Dynamic Model and Control of Quadrotor in the Presence of Uncertainties Courage Agho University of South Carolina Follow this
More information1 Introduction. Control 2:
Introduction Kinematics of Wheeled Mobile Robots (No legs here. They ork like arms. We e seen arms already) For control purposes, the kinematics of heeled mobile robots (WMRs) that e care about are the
More informationVISUAL PHYSICS ONLINE RECTLINEAR MOTION: UNIFORM ACCELERATION
VISUAL PHYSICS ONLINE RECTLINEAR MOTION: UNIFORM ACCELERATION Predict Obsere Explain Exercise 1 Take an A4 sheet of paper and a heay object (cricket ball, basketball, brick, book, etc). Predict what will
More informationWhy does Saturn have many tiny rings?
2004 Thierry De Mees hy does Saturn hae many tiny rings? or Cassini-Huygens Mission: New eidence for the Graitational Theory with Dual Vector Field T. De Mees - thierrydemees @ pandora.be Abstract This
More informationResearch Article On the Dynamics of the Furuta Pendulum
Control Science and Engineering Volume, Article ID 583, 8 pages doi:.55//583 Research Article On the Dynamics of the Furuta Pendulum Benjamin Seth Cazzolato and Zebb Prime School of Mechanical Engineering,
More informationProblem 1: Ship Path-Following Control System (35%)
Problem 1: Ship Path-Following Control System (35%) Consider the kinematic equations: Figure 1: NTNU s research vessel, R/V Gunnerus, and Nomoto model: T ṙ + r = Kδ (1) with T = 22.0 s and K = 0.1 s 1.
More information