Download PDF by T. Zheng : Advanced Model Predictive Control

By T. Zheng

ISBN-10: 9533072989

ISBN-13: 9789533072982

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Predictive Control with Constraints, Prentice-Hal. Mattingley, J. & Boyd, S. (2010). Real-time convex optimization in signal processing, IEEE Signal Processing Magazine 27: 50-61. Mattingley, J. & Boyd, S. (2010). CVXGEN: A code generator for embedded convex optimization, working manuscript. Mattingley & Boyd (2009). Automatic Code Generation for Real-Time Convex Optimization, Cambridge University, chapter Convex Optimization in Signal Processing and Communications. Mehrotra, S. (1992). On the implementation of a primal-dual interior point method, SIAM Journal on Optimization 2: 575-601.

2007). Explicit Hybrid Model Predictive Control of the dc-dc Boost Converter, IEEE Power Electronics Specialists Conference, PESC 2007, Orlando, Florida, USA, pp. 2503-2509 Bemporad, A. (2004). Hybrid Toolbox - User’s Guide. ; Morari, M; Dua, V. N. (2002). The explicit linear quadratic regulator for constrained systems, Automatica 38: 3-20. Bemporad, A. & Morary, M. (1999). Control of systems integrating logic, dynamics, and constraints, Automatica 35: 407-427. D. & Marco, J. (2006 ). Evaluating the Impact of Driveability Requirements on the Performance of an Energy Management Control Architecture for a Hybrid Electric Vehicle, The 2nd International IEE Conference on Automotive Electronics, IEE Savoy Place, UK.

The control performance of MAMPC algorithm is Fast Nonlinear Model Predictive Control using Second Order Volterra Models Based Multi-agent Approach 47 evaluated by illustrative comparison with general NMPC. All the results prove that MAMPC approach is a fairly promising algorithm by delivering significantly improved control. The performance of the proposed controllers is evaluated by applying to single input-single output control of non linear system. Theoretical analysis and simulation results demonstrate better performance of the MAMPC over a conventional NMPC based on sequential quadratic programming in tracking the setpoint changes as well as stabilizing the operation in the presence of input disturbances.

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Advanced Model Predictive Control by T. Zheng


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