A novel model predictive control scheme based on bees algorithm in a class of nonlinear systems: Application to a three tank system
This paper proposes a novel algorithm for utilizing bees algorithm in a model predictive control (MPC) in order to control a class of nonlinear systems. The bees algorithm is utilized in order to solve the open loop optimization problem (OOP), and it is based on the foraging behavior of honey bees....
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| Published in | Neurocomputing (Amsterdam) Vol. 152; pp. 294 - 304 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
25.03.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-2312 1872-8286 |
| DOI | 10.1016/j.neucom.2014.10.066 |
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| Abstract | This paper proposes a novel algorithm for utilizing bees algorithm in a model predictive control (MPC) in order to control a class of nonlinear systems. The bees algorithm is utilized in order to solve the open loop optimization problem (OOP), and it is based on the foraging behavior of honey bees. The proposed algorithm makes use of the bees algorithm for minimizing a predefined cost function in order to find the best input signals subject to constraints and a model of the system. The class of systems considered in this paper includes autonomous nonlinear systems without delay and with continuous and discrete inputs. The proposed algorithm is validated by simulating a three tank system as a case study. A comparison between the proposed novel MPC with different predictive horizons and a conventional MPC demonstrates the potential advantages of the proposed method such as reduction in computation time, good convergence toward desired values and ability of control management. Simulations also show the simplicity of applying and efficiency of the proposed algorithm for designing an MPC based on the bees algorithm.
•A bees algorithm is used to solve the open loop optimization problem in a MPC.•Application to nonlinear autonomous systems with continuous and discrete inputs.•Main features of the method are computation time reduction and control management.•The proposed method has been applied to a three tank system as a case study.•Comparison with a traditional optimization method (MILP) has been provided. |
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| AbstractList | This paper proposes a novel algorithm for utilizing bees algorithm in a model predictive control (MPC) in order to control a class of nonlinear systems. The bees algorithm is utilized in order to solve the open loop optimization problem (OOP), and it is based on the foraging behavior of honey bees. The proposed algorithm makes use of the bees algorithm for minimizing a predefined cost function in order to find the best input signals subject to constraints and a model of the system. The class of systems considered in this paper includes autonomous nonlinear systems without delay and with continuous and discrete inputs. The proposed algorithm is validated by simulating a three tank system as a case study. A comparison between the proposed novel MPC with different predictive horizons and a conventional MPC demonstrates the potential advantages of the proposed method such as reduction in computation time, good convergence toward desired values and ability of control management. Simulations also show the simplicity of applying and efficiency of the proposed algorithm for designing an MPC based on the bees algorithm. This paper proposes a novel algorithm for utilizing bees algorithm in a model predictive control (MPC) in order to control a class of nonlinear systems. The bees algorithm is utilized in order to solve the open loop optimization problem (OOP), and it is based on the foraging behavior of honey bees. The proposed algorithm makes use of the bees algorithm for minimizing a predefined cost function in order to find the best input signals subject to constraints and a model of the system. The class of systems considered in this paper includes autonomous nonlinear systems without delay and with continuous and discrete inputs. The proposed algorithm is validated by simulating a three tank system as a case study. A comparison between the proposed novel MPC with different predictive horizons and a conventional MPC demonstrates the potential advantages of the proposed method such as reduction in computation time, good convergence toward desired values and ability of control management. Simulations also show the simplicity of applying and efficiency of the proposed algorithm for designing an MPC based on the bees algorithm. •A bees algorithm is used to solve the open loop optimization problem in a MPC.•Application to nonlinear autonomous systems with continuous and discrete inputs.•Main features of the method are computation time reduction and control management.•The proposed method has been applied to a three tank system as a case study.•Comparison with a traditional optimization method (MILP) has been provided. |
| Author | Rahmani, Zahra Sarailoo, Morteza Rezaie, Behrooz |
| Author_xml | – sequence: 1 givenname: Morteza surname: Sarailoo fullname: Sarailoo, Morteza email: m.sarailoo@gmail.com organization: Department of Electrical and computer engineering, Binghamton University, 4400 Vestal Pkwy East, Binghamton, NY 13902, USA – sequence: 2 givenname: Zahra surname: Rahmani fullname: Rahmani, Zahra organization: Intelligent System Research Group, Department of Electrical and Computer Engineering, Babol University of Technology, Babol 47148-71167, Iran – sequence: 3 givenname: Behrooz surname: Rezaie fullname: Rezaie, Behrooz organization: Intelligent System Research Group, Department of Electrical and Computer Engineering, Babol University of Technology, Babol 47148-71167, Iran |
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| Cites_doi | 10.1142/S146902680300094X 10.1109/WSC.2006.322980 10.1016/0005-1098(89)90002-2 10.1016/j.automatica.2013.02.003 10.23919/ECC.1999.7099963 10.2307/2686478 10.1002/aic.12672 10.1109/INDICO.2004.1497759 10.1109/TAC.1981.1102596 10.1049/iet-cta.2011.0228 10.1007/s11071-010-9656-z 10.1049/iet-cta:20080015 10.1109/TCST.2011.2154383 10.1049/iet-cta.2011.0187 10.1016/j.isatra.2012.10.004 10.1016/j.asoc.2010.07.021 10.1016/j.nahs.2006.06.005 10.1016/j.jprocont.2007.07.003 10.1016/j.compchemeng.2013.04.011 10.1021/ie402649u 10.1049/el:20030383 10.1109/CEC.2001.934391 10.1016/S0005-1098(98)00178-2 10.1016/S0967-0661(02)00186-7 10.1049/iet-cta.2010.0301 10.1016/j.automatica.2011.11.001 10.1016/S0005-1098(99)00214-9 10.1016/j.ces.2011.07.015 10.1109/TCST.2004.824309 |
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| Keywords | Bees algorithm Model predictive control Intelligent algorithm Optimization technique Three tank system Optimal control |
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| References | Huang, Li, Xi (bib5) 2012; 6 Teo, Abbass, True (bib20) 2003; 3 Qin, Badgwell (bib9) 2000 Moro, Grossmann, Mixed-integer (bib13) 2013; 55 Alipouri, Poshtan (bib27) 2012; 52 Sarailoo, Rezaie, Rahmani (bib34) 2014; 228 A. Makhorin, Glpk (gnu linear programming kit), version 4.42, 2007. Heidarinejad, Liu, Christofides (bib11) 2012; 58 A. Bemporad, Hybrid Toolbox v.1.2.6, 〈http://control.ee.ethz.ch/~hybrid〉 (accessed 25.01.14). Mayne, Rawlings, Rao, Scokaert (bib10) 2000; 36 P. Lučić, D. Teodorović, Bee system: modelling combinatorial optimization transportation engineering problems by swarm intelligence, the preprints of the TRISTAN IV triennial symposium on transportation analysis, Sao Miguel, Azores Islands, Portugal, 12–19 June 2001, pp. 441–445. Sarailoo, Rahmani, Rezaie (bib37) 2013; 3 Nandola, Bhartiya (bib28) 2008; 18 Yang, Cocquempot, Jiang (bib29) 2009; 3 Lazar (bib15) 2006 Zhou, He, Wang, Liu, Ji (bib30) 2012; 20 Sontag (bib39) 1981; 26 Groetsch (bib35) 1993; 24 Bemporad, Morari (bib36) 1999; 35 Gerkšič, Pregelj (bib4) 2012; 6 Ławryńczuk (bib3) 2011; 66 Delavari, Ranjbar, Ghaderi, Momani (bib31) 2010; 61 Ławryńczuk (bib2) 2011; 11 Sarailoo, Rahmani, Rezaie (bib16) 2014; 53 Mignone (bib18) 2002 Karer, Mušič, Škrjanc, Zupančič (bib7) 2008; 2 Torrisi, Bemporad (bib38) 2004; 12 Qin, Badgwell (bib8) 2003; 11 H.A. Abbass, MBO: Marriage in Honey Bees Optimization A Haplometrosis Polygynous Swarming Approach, in: IEEE CEC 2001 Evolutionary Computation, 27–30 May 2001, Seoul, Korea, New York, NY, USA, IEEE, pp. 207–214. B. Heiming, J. Lunze, Definition of the Three-Tank Benchmark Problem for Controller Reconfiguration, in: ECC 1999 European Control Conference, Karlsruhe, Germany, 31 August–3 September 1999. Wedde, Farooq, Zhang (bib22) 2004 C.S. Chong, A.I. Sivakumar, M.Y.H. Low, K.L. Gay, A. Bee, Colony Optimization Algorithm to Job Shop Scheduling, in: IEEE WSC 2006 Simulation Conference, Monterey, Canada, New York, NY, USA, IEEE, 3–6 December 2006, pp. 1954–1961. Garcia, Prett, Morari (bib1) 1989; 25 Aswani, Gonzalez, Sastry, Tomlin (bib14) 2013; 49 Pham, Ghanbarzadeh, Koc, Otri, Rahim, Zaidi (bib24) 2006 Sung (bib25) 2003; 39 M.F. Azeem, A.M. Saad, Modified queen bee evolution based genetic algorithm for tuning of scaling factors of fuzzy knowledge base controller, in: IEEE INDICON 2004 India Annual Conference, Kharagpur, India, New York, NY, USA, IEEE, 20–22 December 2004, pp. 299–303. Slotine, Li (bib17) 1991 Lunze, Askari-Marnani, Cela, Frank, Gehin, Heiming, Lemos, Marcu, Rato, Staroswiecki (bib32) 2001 Ling, Maciejowski, Richards, Wu (bib12) 2012; 48 Wang, Zhang, Sun, Liu, Min (bib6) 2012; 6 Teo (10.1016/j.neucom.2014.10.066_bib20) 2003; 3 Wedde (10.1016/j.neucom.2014.10.066_bib22) 2004 Qin (10.1016/j.neucom.2014.10.066_bib9) 2000 Alipouri (10.1016/j.neucom.2014.10.066_bib27) 2012; 52 Groetsch (10.1016/j.neucom.2014.10.066_bib35) 1993; 24 Gerkšič (10.1016/j.neucom.2014.10.066_bib4) 2012; 6 Karer (10.1016/j.neucom.2014.10.066_bib7) 2008; 2 Lunze (10.1016/j.neucom.2014.10.066_bib32) 2001 Bemporad (10.1016/j.neucom.2014.10.066_bib36) 1999; 35 10.1016/j.neucom.2014.10.066_bib19 Sontag (10.1016/j.neucom.2014.10.066_bib39) 1981; 26 10.1016/j.neucom.2014.10.066_bib40 Aswani (10.1016/j.neucom.2014.10.066_bib14) 2013; 49 10.1016/j.neucom.2014.10.066_bib21 Wang (10.1016/j.neucom.2014.10.066_bib6) 2012; 6 Qin (10.1016/j.neucom.2014.10.066_bib8) 2003; 11 Heidarinejad (10.1016/j.neucom.2014.10.066_bib11) 2012; 58 10.1016/j.neucom.2014.10.066_bib41 Ławryńczuk (10.1016/j.neucom.2014.10.066_bib2) 2011; 11 Ławryńczuk (10.1016/j.neucom.2014.10.066_bib3) 2011; 66 Huang (10.1016/j.neucom.2014.10.066_bib5) 2012; 6 Lazar (10.1016/j.neucom.2014.10.066_bib15) 2006 Slotine (10.1016/j.neucom.2014.10.066_bib17) 1991 Torrisi (10.1016/j.neucom.2014.10.066_bib38) 2004; 12 Sarailoo (10.1016/j.neucom.2014.10.066_bib37) 2013; 3 Garcia (10.1016/j.neucom.2014.10.066_bib1) 1989; 25 Sarailoo (10.1016/j.neucom.2014.10.066_bib16) 2014; 53 Moro (10.1016/j.neucom.2014.10.066_bib13) 2013; 55 Ling (10.1016/j.neucom.2014.10.066_bib12) 2012; 48 10.1016/j.neucom.2014.10.066_bib26 10.1016/j.neucom.2014.10.066_bib23 Sung (10.1016/j.neucom.2014.10.066_bib25) 2003; 39 Zhou (10.1016/j.neucom.2014.10.066_bib30) 2012; 20 10.1016/j.neucom.2014.10.066_bib33 Mignone (10.1016/j.neucom.2014.10.066_bib18) 2002 Yang (10.1016/j.neucom.2014.10.066_bib29) 2009; 3 Delavari (10.1016/j.neucom.2014.10.066_bib31) 2010; 61 Mayne (10.1016/j.neucom.2014.10.066_bib10) 2000; 36 Nandola (10.1016/j.neucom.2014.10.066_bib28) 2008; 18 Sarailoo (10.1016/j.neucom.2014.10.066_bib34) 2014; 228 Pham (10.1016/j.neucom.2014.10.066_bib24) 2006 |
| References_xml | – start-page: 241 year: 2001 end-page: 283 ident: bib32 article-title: Three-tank control reconfiguration publication-title: Control of Complex Systems – volume: 52 start-page: 291 year: 2012 end-page: 299 ident: bib27 article-title: Designing a robust minimum variance controller using discrete slide mode controller approach publication-title: ISA Trans. – reference: B. Heiming, J. Lunze, Definition of the Three-Tank Benchmark Problem for Controller Reconfiguration, in: ECC 1999 European Control Conference, Karlsruhe, Germany, 31 August–3 September 1999. – start-page: 83 year: 2004 end-page: 94 ident: bib22 article-title: Bee hive: an efficient fault-tolerant routing algorithm inspired by honey bee behaviour publication-title: Ant Colony, Optimization and Swarm Intelligence – volume: 35 start-page: 407 year: 1999 end-page: 427 ident: bib36 article-title: Control of systems integrating logic, dynamics, and constraints publication-title: Automatica – reference: A. Makhorin, Glpk (gnu linear programming kit), version 4.42, 2007. – volume: 3 start-page: 211 year: 2009 end-page: 224 ident: bib29 article-title: Robust fault tolerant tracking control with application to hybrid nonlinear systems publication-title: IET Control Theory Appl. – start-page: 454 year: 2006 end-page: 459 ident: bib24 article-title: The bees algorithm – a novel tool for complex optimisation problems publication-title: Intelligent Production Machines and Systems – volume: 20 start-page: 857 year: 2012 end-page: 870 ident: bib30 article-title: Leakage fault diagnosis for an internet-based three-tank system: an experimental study publication-title: IEEE Trans. Control Syst. Technol. – reference: A. Bemporad, Hybrid Toolbox v.1.2.6, 〈http://control.ee.ethz.ch/~hybrid〉 (accessed 25.01.14). – volume: 11 start-page: 2202 year: 2011 end-page: 2215 ident: bib2 article-title: Accuracy and computational efficiency of suboptimal nonlinear predictive control based on neural models publication-title: Appl. Soft Comput. – volume: 12 start-page: 235 year: 2004 end-page: 249 ident: bib38 article-title: HYSDEL-a tool for generating computational hybrid models for analysis and synthesis problems publication-title: IEEE Trans. Control Syst. Technol. – volume: 66 start-page: 5253 year: 2011 end-page: 5267 ident: bib3 article-title: On improving accuracy of computationally efficient nonlinear predictive control based on neural models publication-title: Chem. Eng. Sci. – year: 2002 ident: bib18 article-title: Control and estimation of hybrid systems with mathematical optimization – volume: 6 start-page: 596 year: 2012 end-page: 604 ident: bib6 article-title: Using subset sequence to approach the maximal terminal region for model predictive control publication-title: IET Control Theory Appl. – volume: 36 start-page: 789 year: 2000 end-page: 814 ident: bib10 article-title: Constrained model predictive control: stability and optimality publication-title: Automatica – start-page: 42 year: 1991 end-page: 43 ident: bib17 article-title: Applied Nonlinear Control – volume: 58 start-page: 855 year: 2012 end-page: 870 ident: bib11 article-title: Economic model predictive control of nonlinear process systems using Lyapunov techniques publication-title: AIChE J. – volume: 228 start-page: 369 year: 2014 end-page: 384 ident: bib34 article-title: Fuzzy predictive control of three-tank system based on a modeling framework of hybrid systems publication-title: Part I: J. Syst. Control Eng. – volume: 3 start-page: 20 year: 2013 end-page: 23 ident: bib37 article-title: Modeling of three-tank system with nonlinear valves based on hybrid system approach publication-title: J. Control Eng. Technol. – volume: 3 start-page: 199 year: 2003 end-page: 211 ident: bib20 article-title: Annealing approach to the marriage in honey-bees optimization algorithm publication-title: Int. J. Comput. Intell. Appl. – volume: 26 start-page: 346 year: 1981 end-page: 358 ident: bib39 article-title: Nonlinear regulation—the piecewise linear approach publication-title: IEEE Trans. Autom. Control – volume: 11 start-page: 733 year: 2003 end-page: 764 ident: bib8 article-title: A survey of industrial model predictive control technology publication-title: Control Eng. Pract. – volume: 61 start-page: 383 year: 2010 end-page: 397 ident: bib31 article-title: Fractional order control of a coupled tank publication-title: Nonlinear Dyn. – volume: 18 start-page: 131 year: 2008 end-page: 148 ident: bib28 article-title: A multiple model approach for predictive control of nonlinear hybrid systems publication-title: J. Process Control – volume: 24 start-page: 210 year: 1993 end-page: 217 ident: bib35 article-title: Inverse problems and Torricelli׳s law publication-title: Coll. Math. J. – volume: 53 start-page: 2362 year: 2014 end-page: 2381 ident: bib16 article-title: Fuzzy predictive control of a boiler–turbine system based on a hybrid model system publication-title: Ind. Eng. Chem. Res. – volume: 2 start-page: 491 year: 2008 end-page: 509 ident: bib7 article-title: Model predictive control of nonlinear hybrid systems with discrete inputs employing a hybrid fuzzy model publication-title: Nonlinear Anal. Hybrid Syst. – volume: 25 start-page: 335 year: 1989 end-page: 348 ident: bib1 article-title: Model predictive control: theory and practice—a survey publication-title: Automatica – volume: 6 start-page: 498 year: 2012 end-page: 505 ident: bib5 article-title: Design and input-to-state practically stable analysis of the mixed H2/H feedback robust model predictive control publication-title: IET Control Theory Appl. – volume: 39 start-page: 575 year: 2003 end-page: 576 ident: bib25 article-title: Queen-bee evolution for genetic algorithms publication-title: Electron. Lett. – volume: 55 start-page: 1 year: 2013 end-page: 18 ident: bib13 article-title: Model predictive control formulation for linear systems publication-title: Comput. Chem. Eng. – reference: H.A. Abbass, MBO: Marriage in Honey Bees Optimization A Haplometrosis Polygynous Swarming Approach, in: IEEE CEC 2001 Evolutionary Computation, 27–30 May 2001, Seoul, Korea, New York, NY, USA, IEEE, pp. 207–214. – start-page: 369 year: 2000 end-page: 392 ident: bib9 article-title: An overview of nonlinear model predictive control applications publication-title: Nonlinear Model Predictive Control – volume: 6 start-page: 669 year: 2012 end-page: 679 ident: bib4 article-title: Tuning of a tracking multi-parametric predictive controller using local linear analysis publication-title: IET Control Theory Appl. – reference: M.F. Azeem, A.M. Saad, Modified queen bee evolution based genetic algorithm for tuning of scaling factors of fuzzy knowledge base controller, in: IEEE INDICON 2004 India Annual Conference, Kharagpur, India, New York, NY, USA, IEEE, 20–22 December 2004, pp. 299–303. – year: 2006 ident: bib15 article-title: Model predictive control of hybrid systems stability and robustness – volume: 49 start-page: 1216 year: 2013 end-page: 1226 ident: bib14 article-title: Provably safe and robust learning-based model predictive control publication-title: Automatica – reference: C.S. Chong, A.I. Sivakumar, M.Y.H. Low, K.L. Gay, A. Bee, Colony Optimization Algorithm to Job Shop Scheduling, in: IEEE WSC 2006 Simulation Conference, Monterey, Canada, New York, NY, USA, IEEE, 3–6 December 2006, pp. 1954–1961. – reference: P. Lučić, D. Teodorović, Bee system: modelling combinatorial optimization transportation engineering problems by swarm intelligence, the preprints of the TRISTAN IV triennial symposium on transportation analysis, Sao Miguel, Azores Islands, Portugal, 12–19 June 2001, pp. 441–445. – volume: 48 start-page: 396 year: 2012 end-page: 401 ident: bib12 article-title: Multiplexed model predictive control publication-title: Automatica – volume: 3 start-page: 199 year: 2003 ident: 10.1016/j.neucom.2014.10.066_bib20 article-title: Annealing approach to the marriage in honey-bees optimization algorithm publication-title: Int. J. Comput. Intell. Appl. doi: 10.1142/S146902680300094X – ident: 10.1016/j.neucom.2014.10.066_bib23 doi: 10.1109/WSC.2006.322980 – volume: 25 start-page: 335 year: 1989 ident: 10.1016/j.neucom.2014.10.066_bib1 article-title: Model predictive control: theory and practice—a survey publication-title: Automatica doi: 10.1016/0005-1098(89)90002-2 – volume: 49 start-page: 1216 year: 2013 ident: 10.1016/j.neucom.2014.10.066_bib14 article-title: Provably safe and robust learning-based model predictive control publication-title: Automatica doi: 10.1016/j.automatica.2013.02.003 – ident: 10.1016/j.neucom.2014.10.066_bib33 doi: 10.23919/ECC.1999.7099963 – volume: 24 start-page: 210 year: 1993 ident: 10.1016/j.neucom.2014.10.066_bib35 article-title: Inverse problems and Torricelli׳s law publication-title: Coll. Math. J. doi: 10.2307/2686478 – volume: 58 start-page: 855 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib11 article-title: Economic model predictive control of nonlinear process systems using Lyapunov techniques publication-title: AIChE J. doi: 10.1002/aic.12672 – ident: 10.1016/j.neucom.2014.10.066_bib26 doi: 10.1109/INDICO.2004.1497759 – volume: 26 start-page: 346 year: 1981 ident: 10.1016/j.neucom.2014.10.066_bib39 article-title: Nonlinear regulation—the piecewise linear approach publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.1981.1102596 – volume: 6 start-page: 669 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib4 article-title: Tuning of a tracking multi-parametric predictive controller using local linear analysis publication-title: IET Control Theory Appl. doi: 10.1049/iet-cta.2011.0228 – volume: 61 start-page: 383 year: 2010 ident: 10.1016/j.neucom.2014.10.066_bib31 article-title: Fractional order control of a coupled tank publication-title: Nonlinear Dyn. doi: 10.1007/s11071-010-9656-z – volume: 3 start-page: 211 year: 2009 ident: 10.1016/j.neucom.2014.10.066_bib29 article-title: Robust fault tolerant tracking control with application to hybrid nonlinear systems publication-title: IET Control Theory Appl. doi: 10.1049/iet-cta:20080015 – volume: 20 start-page: 857 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib30 article-title: Leakage fault diagnosis for an internet-based three-tank system: an experimental study publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2011.2154383 – year: 2002 ident: 10.1016/j.neucom.2014.10.066_bib18 – volume: 6 start-page: 498 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib5 article-title: Design and input-to-state practically stable analysis of the mixed H2/H feedback robust model predictive control publication-title: IET Control Theory Appl. doi: 10.1049/iet-cta.2011.0187 – ident: 10.1016/j.neucom.2014.10.066_bib21 – volume: 52 start-page: 291 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib27 article-title: Designing a robust minimum variance controller using discrete slide mode controller approach publication-title: ISA Trans. doi: 10.1016/j.isatra.2012.10.004 – ident: 10.1016/j.neucom.2014.10.066_bib40 – volume: 11 start-page: 2202 year: 2011 ident: 10.1016/j.neucom.2014.10.066_bib2 article-title: Accuracy and computational efficiency of suboptimal nonlinear predictive control based on neural models publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2010.07.021 – volume: 2 start-page: 491 year: 2008 ident: 10.1016/j.neucom.2014.10.066_bib7 article-title: Model predictive control of nonlinear hybrid systems with discrete inputs employing a hybrid fuzzy model publication-title: Nonlinear Anal. Hybrid Syst. doi: 10.1016/j.nahs.2006.06.005 – volume: 18 start-page: 131 year: 2008 ident: 10.1016/j.neucom.2014.10.066_bib28 article-title: A multiple model approach for predictive control of nonlinear hybrid systems publication-title: J. Process Control doi: 10.1016/j.jprocont.2007.07.003 – start-page: 83 year: 2004 ident: 10.1016/j.neucom.2014.10.066_bib22 article-title: Bee hive: an efficient fault-tolerant routing algorithm inspired by honey bee behaviour – volume: 55 start-page: 1 year: 2013 ident: 10.1016/j.neucom.2014.10.066_bib13 article-title: Model predictive control formulation for linear systems publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2013.04.011 – start-page: 42 year: 1991 ident: 10.1016/j.neucom.2014.10.066_bib17 – volume: 53 start-page: 2362 year: 2014 ident: 10.1016/j.neucom.2014.10.066_bib16 article-title: Fuzzy predictive control of a boiler–turbine system based on a hybrid model system publication-title: Ind. Eng. Chem. Res. doi: 10.1021/ie402649u – volume: 39 start-page: 575 year: 2003 ident: 10.1016/j.neucom.2014.10.066_bib25 article-title: Queen-bee evolution for genetic algorithms publication-title: Electron. Lett. doi: 10.1049/el:20030383 – start-page: 241 year: 2001 ident: 10.1016/j.neucom.2014.10.066_bib32 article-title: Three-tank control reconfiguration – start-page: 369 year: 2000 ident: 10.1016/j.neucom.2014.10.066_bib9 article-title: An overview of nonlinear model predictive control applications – ident: 10.1016/j.neucom.2014.10.066_bib19 doi: 10.1109/CEC.2001.934391 – volume: 35 start-page: 407 year: 1999 ident: 10.1016/j.neucom.2014.10.066_bib36 article-title: Control of systems integrating logic, dynamics, and constraints publication-title: Automatica doi: 10.1016/S0005-1098(98)00178-2 – volume: 11 start-page: 733 year: 2003 ident: 10.1016/j.neucom.2014.10.066_bib8 article-title: A survey of industrial model predictive control technology publication-title: Control Eng. Pract. doi: 10.1016/S0967-0661(02)00186-7 – volume: 6 start-page: 596 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib6 article-title: Using subset sequence to approach the maximal terminal region for model predictive control publication-title: IET Control Theory Appl. doi: 10.1049/iet-cta.2010.0301 – year: 2006 ident: 10.1016/j.neucom.2014.10.066_bib15 – start-page: 454 year: 2006 ident: 10.1016/j.neucom.2014.10.066_bib24 article-title: The bees algorithm – a novel tool for complex optimisation problems – volume: 48 start-page: 396 year: 2012 ident: 10.1016/j.neucom.2014.10.066_bib12 article-title: Multiplexed model predictive control publication-title: Automatica doi: 10.1016/j.automatica.2011.11.001 – volume: 3 start-page: 20 year: 2013 ident: 10.1016/j.neucom.2014.10.066_bib37 article-title: Modeling of three-tank system with nonlinear valves based on hybrid system approach publication-title: J. Control Eng. Technol. – volume: 36 start-page: 789 year: 2000 ident: 10.1016/j.neucom.2014.10.066_bib10 article-title: Constrained model predictive control: stability and optimality publication-title: Automatica doi: 10.1016/S0005-1098(99)00214-9 – volume: 228 start-page: 369 year: 2014 ident: 10.1016/j.neucom.2014.10.066_bib34 article-title: Fuzzy predictive control of three-tank system based on a modeling framework of hybrid systems publication-title: Part I: J. Syst. Control Eng. – ident: 10.1016/j.neucom.2014.10.066_bib41 – volume: 66 start-page: 5253 year: 2011 ident: 10.1016/j.neucom.2014.10.066_bib3 article-title: On improving accuracy of computationally efficient nonlinear predictive control based on neural models publication-title: Chem. Eng. Sci. doi: 10.1016/j.ces.2011.07.015 – volume: 12 start-page: 235 year: 2004 ident: 10.1016/j.neucom.2014.10.066_bib38 article-title: HYSDEL-a tool for generating computational hybrid models for analysis and synthesis problems publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2004.824309 |
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| SubjectTerms | Algorithms Bees Bees algorithm Computer simulation Dynamical systems Intelligent algorithm Mathematical models Model predictive control Nonlinear dynamics Optimal control Optimization technique Predictive control Tanks Three tank system |
| Title | A novel model predictive control scheme based on bees algorithm in a class of nonlinear systems: Application to a three tank system |
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