Multiobjective controller design by solving a multiobjective matrix inequality problem
- Author(s): Wei-Yu Chiu 1
-
-
View affiliations
-
Affiliations:
1:
Multiobjective Control Laboratory, Department of Electrical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan
-
Affiliations:
1:
Multiobjective Control Laboratory, Department of Electrical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan
- Source:
Volume 8, Issue 16,
06 November 2014,
p.
1656 – 1665
DOI: 10.1049/iet-cta.2014.0026 , Print ISSN 1751-8644, Online ISSN 1751-8652
In this study, linear matrix inequality (LMI) approaches and multiobjective (MO) evolutionary algorithms are integrated to design controllers. An MO matrix inequality problem (MOMIP) is first defined. A hybrid MO differential evolution (HMODE) algorithm is then developed to solve the MOMIP. The hybrid algorithm combines deterministic and stochastic searching schemes. In the solving process, the deterministic part aims to exploit the structures of matrix inequalities, and the stochastic part is used to fully explore the decision variable space. Simulation results show that the HMODE algorithm can produce an approximated Pareto front (APF) and Pareto-efficient controllers that stabilise the associated controlled system. In contrast with single-objective designs using LMI approaches, the proposed MO methodology can clearly illustrate how the objectives involved affect each other, that is, a broad perspective on optimality is provided. This facilitates the selecting process for a representative design, and particularly the design that corresponds to a non-dominated vector lying in the knee region of the APF. In addition, controller gains can be readily modified to incorporate the preference or need of a system designer.
Inspec keywords: evolutionary computation; Pareto optimisation; stability; linear matrix inequalities; control system synthesis; stochastic systems; search problems
Other keywords: stochastic searching schemes; multiobjective matrix inequality problem; Pareto-efficient controllers; HMODE algorithm; approximated Pareto front; linear matrix inequality; hybrid MO differential evolution; decision variable space; LMI; APF; MO matrix inequality problem; multiobjective evolutionary algorithms; single-objective designs; multiobjective controller design; MO evolutionary algorithms; MOMIP
Subjects: Algebra; Time-varying control systems; Optimisation techniques; Stability in control theory; Control system analysis and synthesis methods
References
-
-
1)
-
7. Ebihara, Y., Hagiwara, T.: ‘New dilated LMI characterizations for continuous-time control design and robust multiobjective control’. Proc. American Control Conf., Anchorage, AK, May 2002, pp. 47–52.
-
-
2)
-
16. Audet, C., Savard, G., Zghal, W.: ‘Multiobjective optimization through a series of single-objective formulations’, SIAM J. Optim., 2008, 19, (1), pp. 188–210 (doi: 10.1137/060677513).
-
-
3)
-
3. Wojsznis, W., Mehta, A., Wojsznis, P., Thiele, D., Blevins, T.: ‘Multi-objective optimization for model predictive control’, ISA Trans., 2007, 46, (3), pp. 351–361 (doi: 10.1016/j.isatra.2006.10.002).
-
-
4)
-
34. Lin, C.M., Li, H.Y.: ‘TSK fuzzy CMAC-based robust adaptive backstepping control for uncertain nonlinear systems’, IEEE Trans. Fuzzy Syst., 2012, 20, (6), pp. 1147–1154 (doi: 10.1109/TFUZZ.2012.2191789).
-
-
5)
-
1. She, Y., Baran, M.E., She, X.: ‘Multiobjective control of PEM fuel cell system with improved durability’, IEEE Trans. Sust. Energy, 2013, 4, (1), pp. 127–135 (doi: 10.1109/TSTE.2012.2203324).
-
-
6)
-
35. Assawinchaichote, W., Nguang, S.K., Shi, P.: ‘Fuzzy control and filter design for uncertain fuzzy systems’ (Springer-Verlag GmbH, Berlin Heidelberg, 2006).
-
-
7)
-
24. Fazzolari, M., Alcala, , Nojima, R.Y., Ishibuchi, H., Herrera, F.: ‘A review of the application of multiobjective evolutionary fuzzy systems: current status and further directions’, IEEE Trans. Fuzzy Syst., 2013, 21, (1), pp. 45–65 (doi: 10.1109/TFUZZ.2012.2201338).
-
-
8)
- N. Poursafar , H. Taghirad , M. Haeri . Model predictive control of non-linear discrete time systems: a linear matrix inequality approach. IET Control Theory Appl. , 10 , 1922 - 1932
-
9)
- C.S. Tseng , B.S. Chen . Multiobjective PID control design in uncertain robotic systems using neural network elimination scheme. IEEE Trans. Syst. Man Cybern. A , 6 , 632 - 644
-
10)
-
13. Lu, J., DePoyster, M.: ‘Multiobjective optimal suspension control to achieve integrated ride and handling performance’, IEEE Trans. Control Syst. Technol., 2002, 10, (6), pp. 807–821 (doi: 10.1109/TCST.2002.804121).
-
-
11)
-
42. Santana-Quintero, L.V., Coello, C.A.C.: ‘An algorithm based on differential evolution for multi-objective problems’, Int. J. Comput. Intell. Res., 2005, 1, (2), pp. 151–169 (doi: 10.5019/j.ijcir.2005.32).
-
-
12)
- M. Elmusrati , R. Jäntti , H.N. Koivo . Multiobjective distributed power control algorithm for CDMA wireless communication systems. IEEE Trans. Veh. Technol. , 3 , 779 - 788
-
13)
-
39. Forbes, J.R.: ‘Dual approaches to strictly positive real controller synthesis with a H2 performance using linear matrix inequalities’, Int. J. Robust Nonlinear Control, 2013, 23, (8), pp. 903–918 (doi: 10.1002/rnc.2808).
-
-
14)
-
21. Patnaik, A., Behera, L.: ‘Evolutionary multiobjective optimization based control strategies for an inverted pendulum on a cart’. Proc. IEEE Congress on Evolutionary Computation, Hong Kong, China, June 2008, pp. 3141–3147.
-
-
15)
-
9. Shimomura, T., Fujii, T.: ‘Multiobjective control design via successive over-bounding of quadratic terms’. Proc. IEEE Conf. on Decision and Control, Sydney, Australia, December 2000, pp. 2763–2768.
-
-
16)
-
46. Wang, Y., Cai, Z.: ‘Combining multiobjective optimization with differential evolution to solve constrained optimization problems’, IEEE Trans. Evol. Comput., 2012, 16, (1), pp. 117–134 (doi: 10.1109/TEVC.2010.2093582).
-
-
17)
-
10. Tanaka, K., Hori, S., Wang, H.O.: ‘Multiobjective control of a vehicle with triple trailers’, IEEE/ASME Trans. Mechatronics, 2002, 7, (3), pp. 357–368 (doi: 10.1109/TMECH.2002.802728).
-
-
18)
- H.J. Lee , J.B. Park , G. Chen . Robust fuzzy control of nonlinear systems with parametric uncertainties. IEEE Trans. Fuzzy Syst. , 2 , 369 - 379
-
19)
-
36. Henrion, D., Korda, M.: ‘Convex computation of the region of attraction of polynomial control systems’, IEEE Trans. Autom. Control, 2014, 59, (2), pp. 297–312 (doi: 10.1109/TAC.2013.2283095).
-
-
20)
-
43. Hernandez-Diaz, A.G., Santana-Quintero, L.V., Coello, C.C., Caballero, R., Molina, J.: ‘A new proposal for multi-objective optimization using differential evolution and rough sets theory’. Proc. Genetic and Evolutionary Computation Conf., Seattle, WA, July 2006, pp. 675–682.
-
-
21)
-
29. Chiu, W.-Y., Chen, B.-S., Poor, H.V.: ‘A multiobjective approach for source estimation in fuzzy networked systems’, IEEE Trans. Circuits Syst. I, 2013, 60, (7), pp. 1890–1900 (doi: 10.1109/TCSI.2012.2226488).
-
-
22)
-
20. Abbaszadeh, M., Marquez, H.J.: ‘Nonlinear robust H-infinity filtering for a class of uncertain systems via convex optimization’, J. Control Theory Appl., 2012, 10, (2), pp. 152–158 (doi: 10.1007/s11768-012-0290-9).
-
-
23)
-
22. Ma, H.M., Ng, K.-T., Man, K.F.: ‘Multiobjective coordinated power voltage control using jumping genes paradigm’, IEEE Trans. Ind. Electron., 2008, 55, (11), pp. 4075–4084 (doi: 10.1109/TIE.2008.928107).
-
-
24)
- M. Abbaszadeh , H.J. Marquez . LMI optimization approach to robust H∞ observer design and static output feedback stabilization for discrete-time nonlinear uncertain systems. Int. J. Robust Nonlinear Control , 3 , 313 - 340
-
25)
-
17. Coello, C.A.C., Van Veldhuizen, D.A., Lamont, G.B.: ‘Evolutionary algorithms for solving multi-objective problems’ (Kluwer Academic, New York, 2002).
-
-
26)
- J.Q. Zhang , A.C. Sanderson . JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. , 5 , 945 - 958
-
27)
- Z. Wang , H. Zeng , D.W.C. Ho , H. Unbehauen . Multiobjective control of a four-link flexible manipulator: a robust H∞ approach. IEEE Trans. Control Syst. Technol. , 6 , 866 - 875
-
28)
-
25. Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V.: ‘Linear matrix inequalities in system and control theory’ (SIAM, Philadelphia, 1994).
-
-
29)
-
33. Ho, W.-H., Chou, J.-H.: ‘Robust finite-time optimal linear state feedback control of uncertain TS-fuzzy-model-based control systems’. Proc. IEEE Int. Conf. on Systems, Man and Cybernetics, Taipei, Taiwan, October 2006, pp. 2590–2595.
-
-
30)
-
40. Sadeghzadeh, A.: ‘Identification and robust control for systems with ellipsoidal parametric uncertainty by convex optimization’, Asian J. Control, 2012, 14, (5), pp. 1251–1261 (doi: 10.1002/asjc.437).
-
-
31)
-
6. Lin, C.-L., Jan, H.-Y., Shieh, N.-C.: ‘GA-based multiobjective PID control for a linear brushless DC motor’, IEEE/ASME Trans. Mechatronics, 2003, 8, (1), pp. 56–65 (doi: 10.1109/TMECH.2003.809136).
-
-
32)
-
37. Lee, D., Joo, H.Y.H., Tak, M.H.: ‘Linear matrix inequality approach to local stability analysis of discrete-time Takagi–Sugeno fuzzy systems’, IET Control Theory Appl., 2013, 7, (9), pp. 1309–1318 (doi: 10.1049/iet-cta.2013.0033).
-
-
33)
-
15. Yang, C.-Y., Chen, B.-S., Jian, C.-Y.: ‘Robust two-loop power control for CDMA systems via multiobjective optimization’, IEEE Trans. Veh. Technol., 2012, 61, (5), pp. 2145–2157 (doi: 10.1109/TVT.2012.2191311).
-
-
34)
-
8. Chen, H., Guo, K.: ‘An LMI approach to multiobjective RMS gain control for active suspensions’. Proc. American Control Conf., Arlington, VA, June 2001, pp. 2646–2651.
-
-
35)
-
23. Aggelogiannaki, E., Sarimveis, H.: ‘A simulated annealing algorithm for prioritized multiobjective optimization-implementation in an adaptive model predictive control configuration’, IEEE Trans. Syst. Man Cybern. B, 2007, 37, (4), pp. 902–915 (doi: 10.1109/TSMCB.2007.896015).
-
-
36)
-
45. Hsieh, M.-N., Chiang, T.-C., Fu, L.-C.C.: ‘A hybrid constraint handling mechanism with differential evolution for constrained multiobjective optimization’. Proc. IEEE Congress on Evolutionary Computation, New Orleans, LA, June 2011, pp. 1785–1792.
-
-
37)
-
18. Lin, C.-T., Chung, I.-F.: ‘A reinforcement neuro-fuzzy combiner for multiobjective control’, IEEE Trans. Syst. Man Cybern. B, 1999, 29, (6), pp. 726–744 (doi: 10.1109/3477.809028).
-
-
38)
-
12. Heo, J.S., Lee, K.Y., Garduno-Ramirez, R.: ‘Multiobjective control of power plants using particle swarm optimization techniques’, IEEE Trans. Energy Convers., 2006, 21, (2), pp. 552–561 (doi: 10.1109/TEC.2005.858078).
-
-
39)
-
30. Tanaka, K., Wang, H.O.: ‘Fuzzy control systems design and analysis: a linear matrix inequality approach’ (Wiley-Interscience, New York, 2001).
-
-
40)
- M.V. Kothare , V. Balakrishnan , M. Morari . Robust constrained model predictive control using linear matrix inequalities. Automatica , 10 , 1361 - 1379
-
41)
-
2. Chipperfield, A.J., Bica, B., Fleming, P.J.: ‘Fuzzy scheduling control of a gas turbine aero-engine: a multiobjective approach’, IEEE Trans. Ind. Electron., 2002, 49, (3), pp. 536–548 (doi: 10.1109/TIE.2002.1005378).
-
-
42)
-
31. Ho, W.-H., Tsai, J.-T., Chou, J.-H.: ‘Robust quadratic-optimal control of TS-fuzzy-model-based dynamic systems with both elemental parametric uncertainties and norm-bounded approximation error’, IEEE Trans. Fuzzy Syst., 2009, 17, (3), pp. 518–531 (doi: 10.1109/TFUZZ.2008.924220).
-
-
43)
- Z. Wan , M.V. Kothare . An efficient off-line formulation of robust model predictive control using linear matrix inequalities. Automatica , 5 , 837 - 846
-
44)
-
28. Chiu, W.-Y., Chen, B.-S.: ‘Multisource prediction under nonlinear dynamics in WSNs using a robust fuzzy approach’, IEEE Trans. Circuits Syst. I, 2011, 58, (1), pp. 137–149 (doi: 10.1109/TCSI.2010.2055331).
-
-
45)
-
11. Bender, F.A., Gomes da Silva, J.M.Jr., Tarbouriech, S.: ‘Convex framework for the design of dynamic anti-windup for state-delayed systems’, IET Contr. Theory Appl., 2011, 5, (12), pp. 1388–1396 (doi: 10.1049/iet-cta.2010.0435).
-
-
46)
- C.Y. Yang , Q.L. Zhang . Multiobjective control for T-S fuzzy singularly perturbed systems. IEEE Trans. Fuzzy Syst. , 1 , 104 - 115
-
1)