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一本英文版的MPC的MATLAB教程
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1 v+ S4 b8 n% L' d. VModel predictive control(MPC) has a long history in the field of control engineering.It is one of the few areas that has received on-going interest from researchers in both the industrial and cademic communities.Four major aspects of model predictive control make the design methodology attractive to both practitioners and academics.The first aspect is the design formulation. which uses a completely multivariable system framework where the peRFormance parameters of the multivariable control system are related to the engineering aspects of the system;hence,they can be understood and 'tuned' by engineers. The second aspect is the ability of the method to handle both 'soft' constraints and hard constraints in a multivariable control framework.This is particularly attractive to industry where tight profit margins and limits on the process operation are inevitably present. The third aspect is the ability to perform on-line process optimization. The fourth aspect is the simplicity of the design framework in handling all these complex issues.
9 b c; J, K1 C2 M$ PThis book gives an introduction to model predictive control, and recent developments in design and implementation.Beginning with an over view of the field,the book will systematically cover topics in receding horizon control ,MPC design formulations, constrained control,Laguerre-function-based predictive control,predictive control using exponential data weighting, reformulation of classical predictive control,tuning of predictive control,as well as simulation and implementation using MATLAB and SIMULINK as a platform. Both continuous-time and discrete-time model predictive control is presented in a similar framework./ ]& q) y2 F+ e& Z. k( N
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