Horizontal Flight Dynamics Simulations using a Simplified Airplane Model and Considering Wind Perturbation

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Horizontal Flight Dynamics Simulations using a Simplified Airplane Model and Considering Wind Perturbation Dan N. DUMITRIU*,1,2, Andrei CRAIFALEANU 2, Ion STROE 2 *Corresponding author *,1 SIMULTEC INGINERIE S.R.L., Str. Prof. Grigore Cobalcescu, 41, sect 1, Bucharest, Romania, dumitriu.dan.n@gmail.com 2 University POLITEHNICA of Bucharest, Faculty of Biotechnical Systems Engineering, Department of Mechanics, 313 Splaiul Independentei, Bucharest 060042, Romania, ycraif@yahoo.com, ion.stroe@gmail.com DOI: 10.13111/2066-8201.2018.10.4.6 Received: 03 November 2018/ Accepted: 08 November 2018/ Published: December 2018 Copyright 2018. Published by INCAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) International Conference of Aerospace Sciences AEROSPATIAL 2018 25-26 October 2018, Bucharest, Romania, (held at INCAS, B-dul Iuliu Maniu 220, sector 6) Section 2 Flight Mechanics Abstract: An in-house method of Newton-Euler inverse dynamics guidance based on a simplified airplane model in horizontal flight was proposed in a previous paper presented at NMAS 2018 workshop [1]. The goal was to guide the airplane between two locations situated at 100 km distance in the horizontal plane, considering some simplifying assumptions: the airplane was considered a material point (no motion equations involving torques are considered here); the thrust was constant in magnitude during the entire motion; the airplane is inclined at time t with the rolling angle (t); the main parameter for controlling the flight path was considered to be the sideslip angle (angle between the thrust vector and the velocity vector); the lift force balanced the weight, the centrifugal force and the wind perturbation lateral force; the wind perturbation was considered linear by pieces of 10 km distance. So, the horizontal flight guidance parameter is the sideslip angle, while the rolling angle is determined from the condition that the flight remains in the horizontal plane, which has to be permanently fulfilled. This paper presents several simulations validating the proposed inverse dynamics guidance tool for airplane horizontal flight. Various wind perturbation possibilities have been tested, considering this wind perturbation as linear by pieces during the horizontal flight. In conclusion, this guidance method worked well for the simplified horizontal flight case study. Key Words: guidance method, horizontal flight, inverse dynamics, simplified airplane motion, rolling angle, sideslip angle 1. PROBLEM Since airplanes are omnipresent in human life for more than a century, elaborate aircraft dynamics complete 3D models can be found in the literature [2,3]. Interesting studies have been carried out also concerning optimal flight paths and speeds [4]. Even if the airplane flight in horizontal plane represents a very simplified motion, it is always useful to dispose, pp. 61 69 (P) ISSN 2066-8201, (E) ISSN 2247-4528

Dan N. DUMITRIU, Andrei CRAIFALEANU, Ion STROE 62 of an in-house simulation tool for this simplified horizontal flight, considering wind perturbation. For this purpose, a simplified model for flight dynamics in horizontal plane with wind perturbation was considered, as proposed by several authors [5,6]. The simulations performed so far validate the proposed numerical guidance algorithm based on this simplified model [1]. Figure 1 shows a vertical view of the horizontal flight and airplane model, illustrating two of the three flight angles used by the simplified model: the yaw angle abs (angle between aircraft absolute velocity vector V abs and x axis) and the sideslip angle abs (angle between the thrust vector T and the absolute velocity vector V abs). The other flight angles involved in this simplified flight dynamics model are: the flight path angle γ = 0 (for the horizontal flight) and the rolling angle, i.e., angle between the vertical plane and the plane of symmetry of the airplane. Let us remark that the absolute velocity vector V abs designates the velocity relative to the ground, i.e., with respect to the inertial frame (O; x,y), being written as the vector sum of the velocity of the airplane relative to the atmosphere V and the velocity of the atmosphere relative to the ground w (wind velocity): V abs = V + w (1) The flight dynamics equations below involve the velocity of the airplane relative to the atmosphere V, also the sideslip angle and the yaw angle are the ones relative to the atmosphere. Fig. 1 Vertical view of the airplane flight [1] The goal of the airplane flight is to move from point A(0,0) to point B(100 km, 0), starting from the initial speed V(t 0 = 0) = 500 km/h. The airplane is subject to wind blowing with velocity w, defined in the inertial frame (O; x,y): w = w x i + w y j. 2. SIMPLIFIED FLIGHT DYNAMICS MODEL FOR AIRPLANE HORIZONTAL FLIGHT, CONSIDERING WIND PERTURBATION To model the aircraft dynamics in the horizontal plane, we have considered the simplifying assumption that the aircraft mass m is constant, considering a relatively short segment of the flight path (100 km flight distance on x axis) [5]. The condition that the flight remains permanently in the horizontal plane is the flight path angle being null: γ = 0. In this particular case, the motion of the aircraft is characterized by the following 6 kinematic parameters: the x and y position coordinates in the horizontal plane, the aircraft velocity V relative to the atmosphere, the relative yaw angle, the rolling angle and the relative sideslip angle. Then, the horizontal flight equations are [5,6]:

63 Horizontal Flight Dynamics Simulations using a Simplified Airplane Model and Considering Wind Perturbation where [6]: { dx dt = V cos + w x dy dt = V sin + w y dv dt = 1 m (T cos β D) (w x cos + w y sin ) d dt = 1 mv (L + T sin β) sin + 1 V (w x sin w y cos ) dγ dt = 0 = 1 [(L + T sin β) cos G] mv (2) w x = w x x (V cos + w x) + w x y (V sin + w y) w y = w y x (V cos + w x) + w y y (V sin + w y) Let us recall here that V is the value of the velocity of the airplane relative to the atmosphere, given by (1): V = V abs w. The thrust T is considered constant during the flight, while drag force D and lift force L depend on the relative speed V, following the classical expressions below: (3) D = 1 2 ρv2 SC D (4) L = 1 2 ρv2 SC L (5) 3. NUMERICAL CASE STUDY The aircraft of mass m = 10 t = 10000 kg flies in an horizontal plane from point A(0,0) to point B(100km, 0), starting from the initial speed V(t 0 = 0) = 500 km/h. The complete initial conditions are as follows: { x 0 = x(t 0 = 0) = 0, y 0 = x(0) = 0, V 0 = V(0) = 500 km h, 0 = (t 0 = 0) = 0, 0 = (0) = 0, β 0 = β(0) = 0. (6) In the absence of wind, the aircraft will normally fly from point A(0,0) to point B(100 km, 0), in t F = 100 km 500 km/h = 0.2 h = 12 min = 720 s. But there is wind in the flight horizontal plane, more precisely w = w x i + w y j, thus the aircraft will be deviated. In this case study, the wind speed components w x and w y are considered to vary linearly by pieces of 10 km on the x-axis abscissa, as shown in the results section below. The following values have been considered here for the coefficients and constants involved in expressions (4) and (5) of the drag and lift forces: = 1.22 kg/m 3 (air), wing area S = 54.5 m 2, drag coefficient C D = 0.0418, lift coefficient C L = 0.239. The value of

Dan N. DUMITRIU, Andrei CRAIFALEANU, Ion STROE 64 the constant thrust during the flight is calculated for our numerical case study as: T = 17.15 kn. Let us recall the unknowns of the flight equations system (1): x, y, V,, and. 4. GUIDANCE ALGORITHM The guidance algorithm used to attend the desired final position B(100 km, 0) is a simplistic inverse dynamics guidance [1]. The flight dynamics equations (2) are integrated in time, from t 0 = 0 until the estimated t estimate F = 720 s (or updated value). A constant time step t = 0.1 s is used here. estimate The estimated flight time t F is computed for a constant aircraft speed V 0, but in fact the speed will slightly vary during the flight. The estimated number of constant time step integrations is N estimate = t F estimate = 7200. t So, the simplified horizontal flight dynamics system comprises: 6 unknown parameters: x, y, V,, and ; 5 scalar dynamics equations (2), from which the first 4 are differential equations, while the last one is transformed in an algebraic equation by imposing the horizontal flight condition γ = 0 dγ = 0. dt it results that there will be 6 5=1 free variables, i.e., the flight control parameter. Naturally, this flight control parameter will be either the sideslip angle, or the rolling angle, or still a combination of and. The simplistic idea of our (inverse dynamics) guidance iterative algorithm is as follows: Step 1) we start from the initial conditions (6); Step 2) for each t i [0, t estimate F ], with i = 0,, N estimate, the yaw angle is i, but we want it to move towards desired guidance i = i computed by the following simplistic/rudimentary guidance algorithm: Let us consider the first two equations from the flight dynamics system (2) at intermediary time t i, by roughly approximating dx = x dt t Let us use the following rough approximations: { { dy and = y : dt t ( x t ) = V i cos i + v x,i i ( y (7) t ) = V i sin i + v y,i i ( x t ) = x final x i i t estimate = 100km x i F t i t estimate F t i ( y t ) = y final y i 0 y i i t estimate = F t i t estimate F t i By dividing the first and the second equation (7) and replacing the rough guidance approximations (8), one obtains: tan i guidance = 100km x i y i (8) i guidance = atan ( x i 100km y i ) (9a)

65 Horizontal Flight Dynamics Simulations using a Simplified Airplane Model and Considering Wind Perturbation As usual, the inverse tangent function must be carefully numerically handled. There is also possible to avoid using the inverse tangent function, by means of the following alternative expression: guidance 1 y i guidance sin i = ( V i t estimate v y,i ) F t i i = asin [ 1 y i ( V i t estimate + v y,i )] F t i Step 3) Still at the intermediary time t i, let us compute the necessary variation of i so that to change (to be guided) from i to the desired i guidance : guidance i (9b) i t = i (10) guidance t i where i guidance is given by (9) and the guidance maneuver time can be considered either the time until the final position t i guidance = tf estimate t i, or less. Taking into account the guidance formula (10), the last two scalar equations from expressions (2) become, at t i : { (L i + T i sin β i+1 ) sin i+1 = mv i i t m(w x,isin i w y,i cos i ) (L i + T i sin β i+1 ) cos i+1 = G (11) with w x,i and w y,i given by (3). From equations (11), one easily obtains the explicit expressions of the rolling angle and the sideslip angle at t i : { guidance 1 β i+1 = asin G 2 + (mv i i i m(w guidance x,isin i w y,i cos i )) T i t i { [ L i ]} i+1 = asin mv i i guidance i t i guidance m(w x,isin i w y,i cos i ) L i + T i sin β i+1 Once computed β i+1 and i+1, the first 3 scalar differential equations in (2) are easily integrated using finite differences integration, computing x i+1, y i+1 and V i+1. Steps 2) and 3) of this guidance algorithm are iteratively applied until x i = x final = 100 km. Let us recall that the value of thrust T is maintained constant during the flight, while the sideslip angle is the main variable control parameter and the rolling angle is imposed by the condition of flight in the horizontal plane. 2 (12)

Dan N. DUMITRIU, Andrei CRAIFALEANU, Ion STROE 66 5. RESULTS VALIDATING THE HORIZONTAL FLIGHT DYNAMICS SIMULATION TOOL For the case study presented above, simulations results are obtained using the in-house horizontal flight dynamics simulation tool based on the simplistic guidance algorithm from previous section. Three tests are presented, all succeeding to bring the airplane close to the final desired destination point B(100km, 0). As mentioned, the wind velocity w = w x i + w y j was considered in the horizontal plane, deviating the aircraft from the initial straight-line trajectory. The wind velocity components w x and w y are considered here to vary linearly by pieces of 10 km on the x-axis abscissa, as shown in the three case studies below. These wind profiles were chosen randomly, for testing purposes. Figure 2 shows the x and y-axis components of the wind velocity for the first case study. The two components of the wind velocity vary linearly by pieces of 10 km on the x-axis abscissa, their intermediate values being randomly chosen in order to test as much as possible the reliability of the proposed guidance algorithm. Fig. 2 x and y-axis components of the wind velocity for the first case study For this first case study corresponding to the wind velocity shown in Figure 2, the flight path in the x-y plane from point A(0,0) to point B(100 km, 0), obtained using the simplistic guidance algorithm proposed in previous section, is presented in Figure 3. The variation of flight angles for the flight path from Figure 3 is shown in Figure 4, the main flight control parameter being the sideslip angle, while the yaw angle is imposed by our simplistic guidance algorithm and the rolling angle is imposed by the condition of flight in the horizontal plane. Fig. 3 x-y plane flight path from point A(0,0) to point B(100 km, 0), obtained using the proposed simplistic guidance algorithm, for the first case study, i.e., for the wind velocity evolution shown in Figure 2

67 Horizontal Flight Dynamics Simulations using a Simplified Airplane Model and Considering Wind Perturbation Fig. 4 Variation of the flight angles (yaw angle, sideslip angle and rolling angle ) for the flight path from Figure 3 (first case study), where is the main flight control parameter As can be observed on Figures 4, 7 and 10, limitations have been considered in what concerns the control angle, more precisely the absolute value of the sideslip angle was imposed to be less than 10 ( β < 10 ). The second case study corresponds to the x and y- axis components of the wind velocity which vary linearly by pieces of 10 km as shown in Figure 5. Fig. 5 x and y-axis components of the wind velocity for the second case study For this second case study corresponding to the wind velocity shown in Figure 5, the flight path in the x-y plane from A(0,0) to B(100 km, 0), obtained using the simplistic guidance algorithm proposed in previous section, is presented in Figure 6. Figure 7 shows the corresponding variation of flight angles, and. Fig. 6 x-y plane flight path from point A(0,0) to point B(100 km, 0), obtained using the proposed simplistic guidance algorithm, for the second case study, i.e., for the wind velocity evolution shown in Figure 5

Dan N. DUMITRIU, Andrei CRAIFALEANU, Ion STROE 68 Fig. 7 Variation of the flight angles (yaw angle, sideslip angle and rolling angle ) for the flight path from Figure 6 (second case study), where is the main flight control parameter The third case study corresponds to the x and y-axis components of the wind velocity which vary linearly by pieces of 10 km as shown in Figure 8. Fig. 8 x and y-axis components of the wind velocity for the third case study For this third case study corresponding to the wind velocity shown in Figure 8, the flight path in the x-y plane from point A(0,0) to point B(100 km, 0), obtained using the simplistic guidance algorithm proposed in previous section, is presented in Figure 9. Figure 10 shows the corresponding variation of flight angles and, while the evolution of the yaw angle is provided by our simplistic guidance algorithm. Fig. 9 x-y plane flight path from point A(0,0) to point B(100 km, 0), obtained using the proposed simplistic guidance algorithm, for the third case study, i.e., for the wind velocity evolution shown in Figure 8

69 Horizontal Flight Dynamics Simulations using a Simplified Airplane Model and Considering Wind Perturbation Fig. 10 Variation of the flight angles (yaw angle, sideslip angle and rolling angle ) for the flight path from Figure 9 (third case study), where is the main flight control parameter 6. CONCLUSIONS AND FURTHER WORK The three case studies show a good performance of the proposed guidance algorithm based on some simplistic approximations. The airplane arrives in all three cases close to the final desired destination point B(100 km, 0). Some appropriate adjustments must be performed to improve the precision of the guidance algorithm in the final part of the flight path; a more appropriate guidance strategy must be applied to cope with the wind deviation on the last 10 km flight path piece. Further work will try to solve this issue, searching for a more elaborated guidance and control algorithm in order to reduce the error in attaining the final position in horizontal flight and trying to obtain a trajectory closer to the straight-line one. Further simulations will also consider more realistic wind profiles. Another more ambitious future work will be to extend the current horizontal flight dynamics simplified model to a simplified model of 3D flight dynamics, with a similar goal of guiding the airplane for an initial to a final position, considering wind perturbation. REFERENCES [1] D. N. Dumitriu, R. A. Petre, A. Craifaleanu, I. Stroe, Inverse dynamics guidance of a simplified airplane model in horizontal flight with wind perturbation, 6 th International Workshop on Numerical Modelling in Aerospace Sciences NMAS 2018, May 16-17, 2018, Bucharest, Romania. [2] B. Etkin, Dynamics of atmospheric flight, Dover Publications, Inc., Mineola, New York, 2012 (originally published: Wiley, New York, 1972. [3] M. V. Cook, Flight dynamics principles: a linear systems approach to aircraft stability and control (3rd edition), Butterworth-Heinemann Elsevier Ltd, 2012. [4] A. Hedenström, T. Alerstam, Skylark optimal flight speeds for flying nowhere and somewhere, Behavioral Ecology, vol. 7, no. 2, pp. 121-126, 1996. [5] I. K. Nikolos, L. Doitsidis, V. N. Christopoulos, N. Tsourveloudis, Roll control of unmanned aerial vehicles using fuzzy logic, 2009, https://www.researchgate.net/publication/228888232_roll_control_of_unmanned_aerial_vehicles_using_ fuzzy_logic [6] D. G. Hull, Fundamentals of Airplane Flight Mechanics, Springer, 2007.