Abstract
The proposed guidance law is used for guiding a missile against a maneuvering target while satisfying a circular no-fly zone (NFZ) constraint. It consists of two parts: virtual-target guidance (VTG) and boundary-constraint handling scheme (BCHS). In order that the missile avoids the NFZ, VTG first maps the actual target to a virtual one, then obtains the relative motion between the virtual target and missile, and finally uses proportional navigation to steer the missile to the virtual target. The missile also hits the actual target when it hits the virtual target because the virtual and actual targets are coincident at this moment. In some cases, especially when the initial velocity vector of the missile points toward the center of the NFZ, if the evasive action taken by VTG is found to be insufficient, then BCHS will be enabled to keep the missile from entering the NFZ unless the target enters the NFZ.
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References
Denton, R. V., Jones, J. E., Froeberg, P. L.: A new technique for terrain following/terrain avoidance guidance command generation. AGARD paper AGARD-CP-387 (1985)
Menon, P.K.A., Kim, E., Cheng, V.H.L.: Optimal trajectory synthesis for terrain-following flight. J. Guid. Control Dyn. 14(4), 807–813 (1991)
Malaek, S.M., Kosari, A.R.: Dynamic based cost functions for TF/TA flights. IEEE Trans. Aerosp. Electron. Syst. 48(1), 44–63 (2012)
Bryson, A.E., Ho, Y.C.: Applied Optimal Control. Blaisdell, Waltham (1969)
Stryk, O.V., Bulirsch, R.: Direct and indirect methods for trajectory optimization. Ann. Oper. Res. 37(1), 357–373 (1992)
Jorris, T.R., Cobb, R.G.: Three-dimensional trajectory optimization satisfying waypoint and no-fly zone constraints. J. Guid. Control Dyn. 32(2), 551–572 (2009)
Benson, D. A.: A gauss pseudospectral transcription for optimal control. Ph.D. Dissertation, MIT (2004)
Duleba, I., Sasiadek, J.Z.: Nonholonomic motion planning based on Newton algorithm with energy optimization. IEEE Trans. Control Syst. Technol. 11(3), 355–363 (2003)
Zhang, L., et al.: Multi-objective global optimal parafoil homing trajectory optimization via Gauss pseudospectral method. Nonlinear Dyn. 72, 1–8 (2013)
Frazzoli, E. M., Dahleh, A., and Feron, E.: Real-Time Motion Planning for Agile Autonomous. AIAA Paper 2000–4056, August (2000)
Mattei, M., Blasi, L.: Smooth flight trajectory planning in the presence of no-fly zones and obstacles. J. Guid. Control Dyn. 33(2), 454–464 (2010)
Min, C., Yuan, J.: The determination of safe corridor and reference path in route planning. Flight Dyn. 17(2), 13–18 (1999)
Jun, M., Andrea, R.: Path planning for unmanned aerial vehicles in uncertain and adversarial environments. Coop. Control Models Appl. Algorithms 1, 95–110 (2003)
Yang, H.I., Zhao, Y.J.: Trajectory planning for autonomous aerospace vehicles amid known obstacles and conflicts. J. Guid. Control Dyn. 27(6), 997–1008 (2004)
Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. in Proc. IEEE Int. Conf Robotics Automat. (St. Louis, MO), Mar (1985)
Hwang, Y.K., Ahuja, N.: A potential field approach to path planning. IEEE Trans. Robot. Autom. 8(1), 23–32 (1992)
Korayem, M.H.: Optimal motion planning of non-linear dynamic systems in the presence of obstacles and moving boundaries using SDRE: application on cable-suspended robot. Nonlinear Dyn. 76, 1423–1441 (2014)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1, 269–271 (1959)
Bellman, R.: The Theory of Dynamic Programming. Annual Summer Meeting of the American Mathematical Society, Wyoming (1954)
Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100–107 (1968)
Yuan, C.L.: Homing and navigation courses of automatic target-seeking devices. J. Appl. Phys. 19, 1122–1128 (1948)
Adler, F.P.: Missile guidance by three-dimensional proportional navigation. J. Appl. Phys. 27, 500–507 (1956)
Zarchan, P.: Tactical and Strategic Missile Guidance, 5th edn. AIAA Progress in Aeronautics and Astronautics, Virginia (2007)
Garber, V.: Optimum intercept laws for accelerating targets. AIAA J. 6(11), 2196–2198 (1968)
Cottrell, R.G.: Optimal intercept guidance for short-range tactical missiles. AIAA J. 9, 1414–1415 (1971)
Ben-Asher, J.Z., Yaesh, I.: Advances in Missile Guidance Theory. AIAA Progress in Astronautics and Aeronautics, Reston (1998)
Cherry, G. W.: A General, Explicit Optimal Guidance Law for Rocket-Propelled Spacecraft. presented at the AIAA/ION Astrodynamics Guidance and Control Conference 1964, Los Angeles, California (1964)
Ohlmeyer, E.J., Phillips, C.A.: Generalized vector explicit guidance. J. Guid. Control Dyn. 29(2), 261–268 (2006)
Zhang, Y., Sun, M., Chen, Z.: Finite-time convergent guidance law with impact angle constraint based on sliding-mode control. Nonlinear Dyn. 70(1), 619–625 (2012)
Kim, M., Grider, K.V.: Terminal guidance for impact attitude angle constrained flight trajectories. IEEE Trans. Aerosp. Electron. Syst. 9(6), 852–859 (1973)
Ryoo, C.K., Cho, H., Tahk, M.J.: Time-to-go weighted optimal guidance with impact angle constraints. IEEE Trans. Control Syst. Technol. 14(3), 483–492 (2006)
Rudin, W.: Principles of Mathematical Analysis, 3rd edn. McGraw-Hill Inc, New York (1976)
Slotine, J.E., Li, W.P.: Applied Nonlinear Control. Prentice Hall, New Jersey (1991)
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Appendix
Appendix
Proposition 1
If \(H_0 >0,\sigma _0 \in [-\pi /2,\;\pi /2]\), and the system S1 described by Eqs. (57–58) is under the control of BCHS described by Eqs. (59–61), then the trajectory (\(H\), \(\sigma \)) of the system S1 converges to the stable node \((0, 0)\) while satisfying that \(H\ge 0.\)
Proof
From Eqs. (57–59), we get a closed-loop system S2 described by
The polar coordinates of the system S2 are
The time derivatives of \(r \) and \(\theta \) are
Now Proposition 1 is proved in two steps:
Step 1: Prove that \(H(t)\ge 0\)for every \( t \ge t_{0}\).
We need to prove that the following sub-proposition is true first.
Sub-proposition 1
The Area \(\Omega _1 \) described by the following inequalities is an invariant set of the autonomous system S2.
Note that the line
is parallel to one of the eigenvectors of the Jacobian matrix of the system S2 at the origin. Let’s observe the movements of the trajectories starting from the four sides of \(\Omega _1 \):
When \(H\ge 0\) and \(\sigma =\pi /2\), from Eq. (88), we get
When \(H=0\) and \(0\le \sigma \le \pi /2\), from Eq. (87), we get
When \(0<H\le {\pi V_M }/{[2(\sqrt{\xi ^{2}-1}+\xi )\omega _n ]}\) and \(\sigma ={-(\sqrt{\xi ^{2}-1}+\xi )\omega _n H}/{V_M }\), by substituting \(H={-V_M \sigma }/{[(\sqrt{\xi ^{2}-1}+\xi )\omega _n ]}\) into Eq. (92), we can obtain
Observe the function \(f(\sigma )=\sin (\sigma )-\sigma \cos (\sigma )\) defined for \(-\pi /2\le \sigma <0\). The derivative of \(f(\sigma )\) is
So \(f(\sigma )\) is an increasing function of \(\sigma \), and then we have that \(f(\sigma )<f(0)=0\). Therefore, we have that \(\dot{\theta }>0\).
When \(H>{\pi V_M }/{[2(\sqrt{\xi ^{2}-1}+\xi )\omega _n ]}\) and \(\sigma =-\pi /2\), from Eq. (88), we get
From the above analysis, it can be concluded that all trajectories starting from the boundary of \(\Omega _1 \) move into the area \(\Omega _1 \). So, if the initial point \((H_0 ,\;\sigma _0 )\in \Omega _1 \), then the corresponding phase trajectory will remain in the area \(\Omega _1 \), i.e., \((H(t),\;\sigma (t))\in \Omega _1 \)for every \(t \ge t_{0}\). Thus, Sub-proposition 1 has already been proved.
Now we need to prove that \((H_0 ,\;\sigma _0 )\in \Omega _1 \). Since \(H_0 >0\) and \(\sigma _0 \in [-\pi /2,\;\pi /2]\) are the conditions of Proposition 1, we only need to prove that \((H_0 ,\;\sigma _0 )\) satisfies the third inequality of Eq. (93). Equation (61) can be converted into
Then
Thus, we have that \((H_0 ,\;\sigma _0 )\in \Omega _1 \). From the above analysis, it can be deduced that \(H(t)\ge 0\) for every \(t \ge t_{0}\).
Step 2: Prove that if \((H_0 ,\;\sigma _0 )\in \Omega _1 \), then \((H,\;\sigma )\) converges to (0, 0).
\(\Omega _2 \) represents an area on the phase plane, and is determined by
where it is obvious that \(\Omega _2 \subset \Omega _1 \). Now we need to prove that the following sub-proposition is true.
Sub-proposition 2
If \((H_0 ,\;\sigma _0 )\in \Omega _2 \), then \((H,\;\sigma )\) converges to (0, 0).
Since two sides of \(\Omega _2 \) are the same as that of \(\Omega _1 \), we only need to observe the movements of the trajectories starting from the points satisfying that\(H\ge 0\) and \(\sigma =0\). When \(H\ge 0\) and \(\sigma =0\), from Eq. (88), we get
Thus, \(\Omega _2 \) is also an invariant set of the autonomous system S2. Define a differentiable function \(V(H,\;\sigma )\) as
When \((H,\;\sigma )\in \Omega _2 \), \(V(H,\;\sigma )\ge 0\) with equality if and only if \(H=\sigma =0\). From Eq. (89), the equivalent propositions will result: when \((H,\;\sigma )\in \Omega _2 \), \(r\rightarrow \infty \Leftrightarrow H\rightarrow \infty \Leftrightarrow V(H,\sigma )\rightarrow \infty \). The time derivative of \(V(H,\;\sigma )\) is
When \((H,\;\sigma )\in \Omega _2 \), \(\dot{V}\le 0\) with equality if and only if \(\sigma =0\). If \((H_0 ,\;\sigma _0 )\in \Omega _2 \), then \((H,\;\sigma )\in \Omega _2 \) for \(t\ge t_0 \) since \(\Omega _2 \) is an invariant set. Then \(V\ge 0\) and \(\dot{V}\le 0\) for every \(t\ge t_0 \), and then from [32], it can be concluded that \(V\) has a finite limit as \(t\rightarrow \infty \). Taking time derivative of Eq. (105) yields
Then
When \((H,\;\sigma )\in \Omega _2 \), from Eq. (87), it is clear that \(\dot{H}\le 0\). Thus, if \(t\ge t_0 \), then \(0\le H\le H_0 \). Then we get
It can be seen that for \(t\ge t_0 \),\(\ddot{V}(t)\) is bounded, and thereby \(\dot{V}(t)\) is uniformly continuous. Now we need to use Barbalat Lemma [33] as follows
Barbalat Lemma
If the differentiable function \(f(t)\) has a finite limit as \(t\rightarrow \infty \), and if \(\dot{f}\) is uniformly continuous, then \(\dot{f}(t)\rightarrow 0\) as \(t\rightarrow \infty .\)
According to Barbalat Lemma, since \(V(t)\) has a finite limit as \(t\rightarrow \infty \) and \(\dot{V}(t)\) is uniformly continuous, it can be concluded that \(\dot{V}(t)\rightarrow 0\) as \(t\rightarrow \infty \). The set of all points in \(\Omega _2 \) such that \(\dot{V}=0\) is {\((H, \sigma ){\vert }\sigma =0\) and \(H\ge 0\)}. However no trajectory can converge to the point satisfying that \(H>0\) and \(\sigma =0\) because \(\dot{\sigma }<0\). Therefore, as \(t\rightarrow \infty \), all trajectories starting from the points in \(\Omega _2 \) converge to the origin where \(\dot{H}=0\) and \(\dot{\sigma }=0\). Hence, Sub-proposition 2 has been proved.
Define \(\Omega _3 \) as the relative complement of \(\Omega _2 \) in \(\Omega _1 \). \(\Omega _3 \) is determined by
Now we need to prove that the Sub-proposition 3 is true.
Sub-proposition 3
If \((H_0 ,\;\sigma _0 )\in \Omega _3 \) , the corresponding phase trajectory will enter \(\Omega _2 \) in finite time.
From Eqs. (87–88), when \((H,\;\sigma )\in \Omega _3 \), we get that \(\dot{H}>0\) and \(\dot{\sigma }<0\). So there must exist a time \(t_1 >t_0 \) such that \(H_1 >H_0 \ge 0\) and \(0<\sigma _1 <\sigma _0 \le \pi /2\). Here \(H_1 \) and \(\sigma _1 \) are the states at the time \(t_{1}\). Before the phase trajectory enters \(\Omega _2 \), we have that if \(t>t_1 \), then \(H>H_1 >0\) and \(0<\sigma <\sigma _1 <\pi /2\). Hence, from Eq. (88), we get
So there must exists a time \(t_{2}\) such that \(\sigma _2 =0\). From Eq. (110), we get
Thus, it is proved that Sub-proposition 3 is true. By combining Sub-propositions 2 and 3 together, it is proved that if \((H_0 ,\;\sigma _0 )\in \Omega _1 \), then \((H,\;\sigma )\) converges to (0, 0) as time goes to infinity. So Proposition 1 has been proved.
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Yu, W., Chen, W. Guidance law with circular no-fly zone constraint. Nonlinear Dyn 78, 1953–1971 (2014). https://doi.org/10.1007/s11071-014-1571-2
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DOI: https://doi.org/10.1007/s11071-014-1571-2