Abstract

This paper extends the recently developed quasi-spectral model predictive static programming (QS-MPSP) to include state and control path-constraints and yet retain its computational efficiency. This is achieved by (i) formulating the entire problem in the control variables alone by (a) converting the system dynamics to an equivalent algebraic constraint and (b) converting the state constraints to equivalent control constraints, both of which is done by manipulating the system dynamics, (ii) representing the control variables in Quasi-spectral form, which makes the number of free-variables independent of time-grids and (iii) using a computationally efficient optimization algorithm to solve this low-dimensional problem. This generic computationally efficient technique is utilized next as an effective lead angle, and lateral acceleration constrained optimal missile guidance to intercept incoming high-speed ballistic targets with high precision successfully. Both of these constraints, as well as near-zero miss-distance, are of high practical significance for this challenging problem. Extensive three-dimensional simulation studies show the effectiveness of the newly proposed constrained QS-MPSP guidance algorithm. Six degrees-of-freedom simulation studies have also been carried out using autopilot in the loop to validate the results more realistically.

References

1.
Kirk
,
D. E.
,
1970
,
Optimal Control Theory: An Introduction
,
Prentice Hall
,
Upper Saddle River, NJ
.
2.
Sage
,
A.
,
1968
,
Optimum Systems Control
(Prentice Hall Networks Series),
Prentice Hall
,
Upper Saddle River, NJ
.
3.
Bryson
,
J. A. E.
, and
Ho
,
Y.-C.
,
1975
,
Applied Optimal Control: Optimization, Estimation and Control
,
Hemisphere Publishing Corporation
,
New York
.
4.
Hager
,
W. W.
, and
Pardalos
,
P. M.
,
2013
,
Optimal Control: Theory, Algorithms, and Applications
, Vol.
15
,
Springer Science & Business Media
,
Dordrecht, The Netherlands
.
5.
Hull
,
D. G.
,
2013
,
Optimal Control Theory for Applications
,
Springer Science & Business Media
,
New York
.
6.
Longuski
,
J. M.
,
Guzmán
,
J. J.
, and
Prussing
,
J. E.
,
2014
,
Optimal Control With Aerospace Applications
,
Springer
,
Berlin
.
7.
Ben-Asher
,
J. Z.
,
2010
,
Optimal Control Theory With Aerospace Applications
,
American Institute of Aeronautics and Astronautics
,
Reston, VA
.
8.
Ross
,
I.
,
2015
,
A Primer on Pontryagin's Principle in Optimal Control: Second Edition
,
Collegiate Publishers
.
9.
Naidu
,
D. S.
,
2003
,
Optimal Control Systems
,
CRC Press
,
West Palm Beach, FL
.
10.
Morrison
,
D. D.
,
Riley
,
J. D.
, and
Zancanaro
,
J. F.
,
1962
, “
Multiple Shooting Method for Two-Point Boundary Value Problems
,”
Commun. ACM
,
5
(
12
), pp.
613
614
.10.1145/355580.369128
11.
Larson
,
R.
, and
Casti
,
J.
,
1978
, “
Principles of Dynamic Programming: Advanced Theory and Applications
,”
Control and Systems Theory
, 1v series,
M.
Dekker
, ed.,
John L. Publication
,
New York
.
12.
Betts
,
J. T.
,
2001
, “
Practical Methods for Optimal Control Using Nonlinear Programming
,”
Advances in Design and Control, Society for Industrial and Applied Mathematics
,
Philadelphia, PA
.
13.
Wang
,
L.
,
2009
,
Model Predictive Control System Design and Implementation Using MATLAB®
,
Springer Science & Business Media
,
London, UK
.
14.
Allgöwer
,
F.
, and
Zheng
,
A.
,
2012
, “
Nonlinear Model Predictive Control
,”
Progress in Systems and Control Theory
,
Birkhäuser Basel
,
Basel, Switzerland
.
15.
Chen
,
H.
, and
Allgöwer
,
F.
,
1998
, “
A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme With Guaranteed Stability
,”
Automatica
,
34
(
10
), pp.
1205
1217
.10.1016/S0005-1098(98)00073-9
16.
Mayne
,
D.
,
Rawlings
,
J.
,
Rao
,
C.
, and
Scokaert
,
P.
,
2000
, “
Constrained Model Predictive Control: Stability and Optimality
,”
Automatica
,
36
(
6
), pp.
789
814
.10.1016/S0005-1098(99)00214-9
17.
Rawlings
,
J. B.
,
Angeli
,
D.
, and
Bates
,
C. N.
,
2012
, “
Fundamentals of Economic Model Predictive Control
,”
IEEE 51st IEEE Conference on Decision and Control (CDC)
,
Maui, HI
, Dec. 10–13, pp.
3851
3861
.10.1109/CDC.2012.6425822
18.
Wang
,
Y.
, and
Boyd
,
S.
,
2010
, “
Fast Model Predictive Control Using Online Optimization
,”
IEEE Trans. Control Syst. Technol.
,
18
(
2
), pp.
267
278
.10.1109/TCST.2009.2017934
19.
Fahroo
,
F.
, and
Ross
,
I. M.
,
2002
, “
Direct Trajectory Optimization by a Chebyshev Pseudospectral Method
,”
J. Guid., Control, Dyn.
,
25
(
1
), pp.
160
166
.10.2514/2.4862
20.
Gong
,
Q.
,
Fahroo
,
F.
, and
Ross
,
I. M.
,
2008
, “
Spectral Algorithm for Pseudospectral Methods in Optimal Control
,”
J. Guid., Control, Dyn.
,
31
(
3
), pp.
460
471
.10.2514/1.32908
21.
Balakrishnan
,
S. N.
, and
Biega
,
V.
,
1996
, “
Adaptive-Critic Based Neural Networks for Aircraft Optimal Control
,”
J. Guid., Control Dyn.
,
19
(
4
), pp.
893
898
.10.2514/3.21715
22.
Padhi
,
R.
, and
Kothari
,
M.
,
2009
, “
Model Predictive Static Programming: A Computationally Efficient Technique for Suboptimal Control Design
,”
Int. J. Innov. Comput., Inform. Control
,
5
(
2
), pp.
399
411
.https://www.researchgate.net/publication/38304645_Model_Predictive_Static_Programming_A_Computationally_Efficient_Technique_For_Suboptimal_Control_Design
23.
Halbe
,
O.
,
Raja
,
R. G.
, and
Padhi
,
R.
,
2014
, “
Robust Reentry Guidance of a Reusable Launch Vehicle Using Model Predictive Static Programming
,”
J. Guid., Control, Dyn.
,
37
(
1
), pp.
134
148
.10.2514/1.61615
24.
Maity
,
A.
,
Padhi
,
R.
,
Mallaram
,
S.
,
Rao
,
G. M.
, and
Manickavasagam
,
M.
,
2016
, “
A Robust and High Precision Optimal Explicit Guidance Scheme for Solid Motor Propelled Launch Vehicles With Thrust and Drag Uncertainty
,”
Int. J. Syst. Sci.
,
47
(
13
), pp.
3078
3097
.10.1080/00207721.2015.1088100
25.
Kumar
,
P.
,
Anoohya
,
B. B.
, and
Padhi
,
R.
,
2019
, “
Model Predictive Static Programming for Optimal Command Tracking: A Fast Model Predictive Control Paradigm
,”
ASME J. Dyn. Syst., Meas., Control
,
141
(
2
), p.
021014
.10.1115/1.4041356
26.
Mathavaraj
,
S.
, and
Padhi
,
R.
,
2019
, “
Unscented Mpsp for Optimal Control of a Class of Uncertain Nonlinear Dynamic Systems
,”
ASME J. Dyn. Syst., Meas., Control
,
141
(
6
), p.
065001
.10.1115/1.4042549
27.
Sakode
,
C. M.
, and
Padhi
,
R.
,
2014
, “
Computationally Efficient Suboptimal Control Design for Impulsive Systems Based on Model Predictive Static Programming
,”
IFAC Proc. Vol
,
47
(
1
), pp.
41
46
.10.3182/20140313-3-IN-3024.00172
28.
Dwivedi
,
P. N.
,
Bhattacharya
,
A.
, and
Padhi
,
R.
,
2011
, “
Suboptimal Midcourse Guidance of Interceptors for High-Speed Targets With Alignment Angle Constraint
,”
J. Guid., Control, Dyn.
,
34
(
3
), pp.
860
877
.10.2514/1.50821
29.
Oza
,
H. B.
, and
Padhi
,
R.
,
2012
, “
Impact-Angle-Constrained Suboptimal Model Predictive Static Programming Guidance of Air-to-Ground Missiles
,”
J. Guid., Control, Dyn.
,
35
(
1
), pp.
153
164
.10.2514/1.53647
30.
Sachan
,
K.
, and
Padhi
,
R.
,
2019
, “
Waypoint Constrained Multi-Phase Optimal Guidance of Spacecraft for Soft Lunar Landing
,”
Unmanned Syst.
,
07
(
02
), pp.
83
104
.10.1142/S230138501950002X
31.
Mondal
,
S.
, and
Padhi
,
R.
,
2018
, “
Angle-Constrained Terminal Guidance Using Quasi-Spectral Model Predictive Static Programming
,”
J. Guid., Control, Dyn.
,
41
(
3
), pp.
783
791
.10.2514/1.G002893
32.
Manchester
,
I. R.
, and
Savkin
,
A. V.
,
2006
, “
Circular-Navigation-Guidance Law for Precision Missile/Target Engagements
,”
J. Guid., Control, Dyn.
,
29
(
2
), pp.
314
320
.10.2514/1.13275
33.
Park
,
B.
,
Jeon
,
B.
,
Kim
,
T.
,
Tahk
,
M.
, and
Kim
,
Y.
,
2012
, “
Composite Guidance Law for Impact Angle Control of Tactical Missiles With Passive Seekers
,”
Asia-Pacific International Symposium on Aerospace Technology
,
Nanjing, China
, Nov. 1–3, pp.
13
15
.
34.
Kim
,
T.-H.
,
Park
,
B.-G.
, and
Tahk
,
M.-J.
,
2013
, “
Bias-Shaping Method for Biased Proportional Navigation With Terminal-Angle Constraint
,”
J. Guid., Control, Dyn.
,
36
(
6
), pp.
1810
1816
.10.2514/1.59252
35.
Tekin
,
R.
, and
Erer
,
K. S.
,
2015
, “
Switched-Gain Guidance for Impact Angle Control Under Physical Constraints
,”
J. Guid., Control, Dyn.
,
38
(
2
), pp.
205
216
.10.2514/1.G000766
36.
Erer
,
K. S.
,
Tekin
,
R.
, and
Özgören
,
M. K.
,
2015
, “
Look Angle Constrained Impact Angle Control Based on Proportional Navigation
,”
AIAA Paper No. 2015-0091
.10.2514/6.2015-0091
37.
Park
,
B.-G.
,
Kim
,
T.-H.
, and
Tahk
,
M.-J.
,
2016
, “
Range-to-Go Weighted Optimal Guidance With Impact Angle Constraint and Seeker's Look Angle Limits
,”
IEEE Trans. Aerosp. Electron. Syst.
,
52
(
3
), pp.
1241
1256
.10.1109/TAES.2016.150415
38.
Shaferman
,
V.
,
2017
, “
Optimal Guidance With an in Route Look-Angle Constraint
,”
AIAA Paper No. 2017-1507
.10.2514/6.2017-1507
39.
Mondal
,
S.
, and
Padhi
,
R.
,
2018
, “
State and Input Constrained Missile Guidance Using Spectral Model Predictive Static Programming
,”
AIAA Paper No. 2018-1584
.10.2514/6.2018-1584
40.
Lovelly
,
T. M.
, and
George
,
A. D.
,
2017
, “
Comparative Analysis of Present and Future Space-Grade Processors With Device Metrics
,”
J. Aerosp. Inf. Syst.
,
14
(
3
), pp.
184
197
.10.2514/1.I010472
41.
Akhil
,
G.
, and
Ghose
,
D.
,
2012
, “
Biased PN Based Impact Angle Constrained Guidance Using a Nonlinear Engagement Model
,”
American Control Conference (ACC)
,
Fairmont Queen Elizabeth, Montréal
,
QC, Canada
, June 27–29, pp.
950
955
.
42.
Kim
,
J.
,
Cho
,
N.
, and
Kim
,
Y.
,
2019
, “
Field-of-View Constrained Impact Angle Control Guidance Guaranteeing Error Convergence Before Interception
,”
AIAA Paper No. 2019-1927
.10.2514/6.2019-1927
43.
Padhi
,
R.
,
Chawla
,
C.
, and
Das
,
P. G.
,
2014
, “
Partial Integrated Guidance and Control of Interceptors for High-Speed Ballistic Targets
,”
J. Guid., Control, Dyn.
,
37
(
1
), pp.
149
163
.10.2514/1.61416
44.
Enns
,
D.
,
Bugajski
,
D.
,
Hendrick
,
R.
, and
Stein
,
G.
,
1994
, “
Dynamic Inversion: An Evolving Methodology for Flight Control Design
,”
Int. J. Control
,
59
(
1
), pp.
71
91
.10.1080/00207179408923070
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