Abstract
A modular flight control strategy is presented here to demonstrate the improved command tracking performance with fault tolerance and reconfiguration capabilities. The modular control design process consists of inner and outer loop design concept, where outer baseline controller feedback loop ensures the stability and robustness and inner reconfigurable design is responsible for the fault-tolerance against actuator faults/failures. This guarantees augmented autonomy and intelligence on board aircraft for real time decision and fault tolerant control. Requirements for aerospace cyber physical systems (ACPS) and software are far more stringent than those found in industrial automation systems. The results shows that fault tolerant aspect is mandatory for ACPS, that must support real time behavior and also requires ultra-high reliability as many systems or/sub-systems are safety critical and require certification.
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References
K. Butts, N. Sivashankar, J. Sun, Feedforward and feedback design for engine idle speed control using l1 optimization, in Proceedings of the American Control Conference, 1995, pp. 2587–2590
A. Tarau, B. De Schutter, H. Hellendoorn, Centralized versus decentralized route choice control in dcv-based baggage handling systems, in International Conference on Networking, Sensing and Control, 2009. ICNSC’09, 2009, pp. 334–339
W. Wang, D.E. Rivera, K.G. Kempf, Centralized model predictive control strategies for inventory management in semiconductor manufacturing supply chains, in Proceedings of the American Control Conference, 2003, pp. 585–590
C. Vermillion, J. Sun, K. Butts, Modeling, control design, and experimental validation of an overactuated thermal management system for engine dynamometer applications. IEEE Trans. Control Syst. Technol. 17, 540–551 (2009)
M.S. Kim, C.S. Chung, The robust flight control of an uav using mimo qft: ga-based automatic loop-shaping method, in Systems Modeling and Simulation: Theory and Applications, pp. 467–477 (2005)
Härkegård, Ola, and S. Torkel Glad. Resolving Actuator Redundancy—optimal control vs. control allocation. Automatica 41(1), 137–144 (2005)
O. Harkegard, Dynamic control allocation using constrained quadratic programming. J. Guid. Control Dyn. 27, 1028–1034 (2004)
Y. Luo, A. Serrani, S. Yurkovich, D.B. Doman, M.W. Oppenheimer, Model predictive dynamic control allocation with actuator dynamics, in Proceedings of the American Control Conference, 2004, pp. 1695–1700
J. Tjonnas, T.A. Johansen, Optimizing adaptive control allocation with actuator dynamics, in 2007 46th IEEE Conference on Decision and Control, 2007, pp. 3780–3785
T.A. Johansen, T.P. Fuglseth, P. Tøndel, T.I. Fossen, Optimal constrained control allocation in marine surface vessels with rudders. Control Eng. Pract. 16, 457–464 (2008)
O. Sørdalen, Optimal thrust allocation for marine vessels. Control Eng. Pract. 5, 177–185 (537)
S.P. Berge, T.I. Fossen, Robust control allocation of overactuated ships; experiments with a model ship, in Proceedings of the 4th IFAC Conference on Manoeuvring and Control of Marine Craft, vol. 537, pp. 20–25
T.A. Johansen, Optimizing nonlinear control allocation, in 43rd IEEE Conference on Decision and Control, 544, CDC. 544, vol. 4, pp. 3435–3440
T.A. Johansen, T.I. Fossen, P. Tøndel, Efficient optimal constrained control allocation via multiparametric programming. J. Guidance Control Dyn. 28, 506–515
K.P. Lindegaard, T.I. Fossen, Fuel-efficient rudder and propeller control allocation for marine craft: experiments with a model ship. IEEE Trans Control Syst. Technol. 11, 850–862
R.H. Shertzer, D. Zimpfer, P.D. Brown, Control allocation for the next generation of entry vehicles, in AIAA Guidance, Navigation, and Control Conference and Exhibit
Y. Luo, A. Serrani, S. Yurkovich, M.W. Oppenheimer, D.B. Doman, Model-predictive dynamic control allocation scheme for reentry vehicles. J. Guidance Control Dyn. 30, 100–113
O. Härkegård, Efficient active set algorithms for solving constrained least squares problems in aircraft control allocation, in Proceedings of the 41st IEEE Conference on Decision and Control, 542, vol. 2, pp. 1295–1300
K.A. Bordignon, Constrained control allocation for systems with redundant control effectors, Ph.D. Dissertation, Virginia Polytechnic Institute and State University, 1996
J.M. Buffington, Tailless aircraft control allocation. Tech. Rep., DTIC Document, 1997
J.H. Plumlee, D.M. Bevly, A.S. Hodel, Control of a ground vehicle using quadratic programming based control allocation techniques, in Proceedings of the American Control Conference, 2004, vol. 5, pp. 4704–4709
B. Schofield, T. Hagglund, A. Rantzer, Vehicle dynamics control and controller allocation for rollover prevention. IEEE International Conference on Control Applications Computer Aided Control System Design, 546, IEEE International Symposium on Intelligent Control, IEEE, pp. 3–8
J. Tjoennas, T.A. Johansen, Adaptive optimizing dynamic control allocation algorithm for yaw stabilization of an automotive vehicle using brakes, in 14th Mediterranean Conference on Control and Automation, 546. MED’06, 546, pp. 1–6
P. Tøndel, Constrained optimal control via multi-parametric quadratic programming, Ph.D. thesis, Norwegian University of Science and Technology, 543
J. Tjonnas, T.A. Johansen, Stabilization of automotive vehicles using active steering and adaptive brake control allocation. IEEE Trans. Control Syst. Technol. 18, 545–558 (2010)
D.B. Doman, M.W. Oppenheimer, D. Sigthorsson, Dynamics and control of a biomimetic vehicle using biased wingbeat forcing functions: Part ii: Controller. AIAA, Washington, 1024 (2010)
K.S. Jung, Y.S. Baek, Force distribution of a six-legged walking robot with high constant speed. J. Mech. Sci. Technol. 14, 131–140 (2000)
S. Sreenivasan, K. Waldron, S. Mukherjee, Globally optimal force allocation in active mechanisms with four frictional contacts. J. Mech. Des. 118(3), 353–359 (1996)
M.P.J. Fromherz, W.B. Jackson, Force allocation in a large-scale distributed active surface. IEEE Trans. Control Syst. Technol. 11, 641–655 (2003)
K. Bordignon, J. Bessolo, Control allocation for the X-35b, in 2002 Biennial International Powered Lift Conference and Exhibit, 2002
J.B. Davidson, F.J. Lallman, W.T. Bundick, Real-time adaptive control allocation applied to a high performance aircraft, in 5th SIAM Conference on Control & Its Application, 2001, pp. 1211–1229
O. Harkegard, Backstepping and control allocation with applications to flight control, Ph.D. dissertation, Linkoping universitet, 2003
J.Q. Leedy, Real-Time Moment Rate Constrained Control Allocation for Aircraft with a Multiply-Redundant Control Suite, Ph.D. thesis, Virginia Polytechnic Institute and State University, 1998
W.C. Durham, Computationally efficient control allocation. J. Guid. Control Dyn. 24(3), 519–524 (2001)
K.R. Scalera, A comparison of control allocation methods for the F-15 ACTIVE research aircraft utilizing real-time piloted simulations, Ph.D. thesis, Virginia Polytechnic Institute and State University, 1999
M. Bodson, Evaluation of optimization methods for control allocation. J. Guidance Control Dyn. 25 (2008)
A.H. Khan, Z. Weiguo, Z.H. Khan, S. Jingping, Evolutionary computing based modular control design for aircraft with redundant effectors. Procedia Eng. 29, 110–117 (2012)
A.H. Khan, Z. Weiguo, S. Jingping, Z.H. Khan, Optimized reconfigurable modular flight control design using swarm intelligence. Procedia Eng. 24, 621–628 (2011)
M.A. Bolender, D.B. Doman, M.W. Oppenheimer, Application of piecewise linear control allocation to reusable launch vehicle guidance and control, in 14th Mediterranean Conference on Control and Automation, 2006. MED’06, 2006, pp. 1–10
J.A.M. Petersen, Algorithms for optimal real-time control allocation, Ph.D. dissertation, 2003
J.A.M. Petersen, M. Bodson, Interior-point algorithms for control allocation. J. Guid. Control Dyn. 28, 471–480 (2005)
Y. Hattori, K. Koibuchi, T. Yokoyama, Force and moment control with nonlinear optimum distribution for vehicle dynamics, in Proceedings of the 6th International Symposium on Advanced Vehicle Control (2002), pp. 595–600
R.C. Eberhart, Y. Shi, J. Kennedy, Swarm intelligence, Morgan Kaufmann, 2001
J. Kennedy, R. Eberhart, Particle swarm optimization, in Proceedings of the IEEE International Conference on Neural Networks, vol. 4 (1995), pp. 1942–1948
Z.L. Gaing, A particle swarm optimization approach for optimum design of pid controller in avr system. IEEE Trans. Energy Convers. 19, 384–391 (2004)
N. Jin, Y. Rahmat-Samii, Parallel particle swarm optimization and finite-difference timedomain (pso/fdtd) algorithm for multiband and wide-band patch antenna designs. IEEE Trans. Antennas Propag. 53, 3459–3468 (2005)
Y. del Valle, G.K. Venayagamoorthy, S. Mohagheghi, J.C. Hernandez, R.G. Harley, Particle swarm optimization: basic concepts, variants and applications in power systems. IEEE Trans. Evol. Comput. 12, 171–195 (2008)
R. Poli, Analysis of the publications on the applications of particle swarm optimization. J. Artif. Evol. Appl. 2008, 3 (2008)
Y. Shi, R. Eberhart, A modified particle swarm optimizer, in Proceedings of the 1998 IEEE International Conference on Evolutionary Computation (IEEE World Congress on Computational Intelligence, 1998), pp. 69–73
R.C. Eberhart, Y. Shi, Tracking and optimizing dynamic systems with particle swarms, in Proceedings of the 2001 Congress on Evolutionary Computation, vol. 1 (2001), pp. 94–100
P. Fourie, A. Groenwold, The particle swarm optimization algorithm in size and shape optimization. Struct. Multidiscip. Optim. 23, 259–267 (2002)
Y.L. Zheng, L.H. Ma, L.Y. Zhang, J.X. Qian, On the convergence analysis and parameter selection in particle swarm optimization, in Proceedings of the 2003 International Conference on Machine Learning and Cybernetics, vol. 3 (2003), pp. 1802–1807
J. Kennedy, R. Eberhart, Particle swarm optimization, in Proceedings of the IEEE International Conference on Neural Networks, vol. 4 (1995), pp. 1942–1948
M. Nasri, H. Nezamabadi-Pour, M. Maghfoori, A PSO-based optimum design of pid controller for a linear brushless dc motor. World Acad. Sci., Eng. Technol. 26, 211–215 (2007)
C.N. Ko, C.J. Wu, A PSO-tuning method for design of fuzzy PID controllers. J. Vib. Control 14, 375–396 (2008)
M.I. Solihin, W. Akmeliawati, R. Akmeliawati, PSO-based optimization of state feedback tracking controller for a flexible link manipulator, in Proceedings of the International Conference of Soft Computing and Pattern Recognition, 2009 (SOCPAR’09) (2009), pp. 72–76
S.A. Ghoreishi, M.A. Nekoui, S.O. Basiri, Optimal design of LQR weighting matrices based on intelligent optimization methods. IJIIP: Int. J. Intell. Inf. Process., AICIT 2, 63–74 (2011)
D. Enns, Control allocation approaches, in Proceeding of the AIAA Guidance, Navigation, and Control Conference (1998)
M. Grant, S. Boyd, Y. Ye, Disciplined convex programming, in Global Optimization (Springer, New York, 2006), pp. 155–210
M. Grant, Disciplined convex programming. Ph.d. dissertation, Stanford University (2004)
M. Grant, S. Boyd, Y. Ye, cvx users’ guide. Technical Report Build 711, Citeseer (2009), http://citeseerx.ist.psu.edu/viewdoc/download
J. Mattingley, S. Boyd, CVXGEN: a code generator for embedded convex optimization, in Optimization and Engineering (2012), pp. 1–27
W.C. Durham, K.A. Bordignon, Multiple control effector rate limiting. J. Guid. Control Dyn. 19, 30–37 (1996)
S.A. Frost, M. Bodson, Resource balancing control allocation. Am. Control Conf. (ACC) 2010, 1326–1331 (2010)
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Khan, A.H., Khan, Z.H., Khan, S.H. (2014). Optimized Reconfigurable Autopilot Design for an Aerospace CPS. In: Khan, Z., Ali, A., Riaz, Z. (eds) Computational Intelligence for Decision Support in Cyber-Physical Systems. Studies in Computational Intelligence, vol 540. Springer, Singapore. https://doi.org/10.1007/978-981-4585-36-1_13
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DOI: https://doi.org/10.1007/978-981-4585-36-1_13
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