Model-Based Predictive Control: A Practical Approach by J.A. Rossiter

By J.A. Rossiter

Version Predictive keep watch over (MPC) has develop into a known method throughout all engineering disciplines, but there are few books which research this technique. formerly, no publication has addressed intimately all key concerns within the box together with apriori balance and powerful balance effects. Engineers and MPC researchers now have a quantity that offers an entire evaluate of the speculation and perform of MPC because it pertains to method and keep an eye on engineering.Model-Based Predictive regulate, a pragmatic technique, analyzes predictive keep watch over from its base mathematical starting place, yet provides the subject material in a readable, intuitive variety. the writer writes in layman's phrases, warding off jargon and utilizing a method that depends own perception into useful applications.This designated creation to predictive keep watch over introduces easy MPC options and demonstrates how they're utilized within the layout and keep an eye on of structures, experiments, and commercial strategies. The textual content outlines the best way to version, supply robustness, deal with constraints, determine feasibility, and warrantly balance. It additionally info recommendations in regard to algorithms, versions, and complexity vs. functionality matters.

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Dl,1 xn (k) . . cl,n C xk d1,2 d2,2 .. 1)   u1 (k) . . d1,m   . . d2,m    u2 (k)  ..   ..  .  .  um (k) . . 2) x denotes the state vector (dimension n), y (dimension l) denotes the process outputs (or measurements) to be controlled and u (dimension m) denotes the process inputs Common linear models used in model predictive control 21 (or controller output) and A, B,C, D are the matrices defining the state-space model. Ordinarily for real processes D = 0. 2 Nonsquare systems Although MPC can cope with nonsquare systems (l = m), it is more usual to do some squaring down and hence control a square system.

U ..   →k−1 .  yk+ny CAny CAny −1 B CAny −2 B CAny −3 B . . 1 These prediction equations do not consider the disturbance model explicitly. 4. 12) to ensure offset free control. 1. g. [102]); some are more transparent than others. This book will not contrast the different methods in detail because they give the same prediction equations so which to use reduces to personal preference. Typically papers in the academic journals make use of diophantine identities to form the prediction equations.

5. 31). The development is given below. For simplicity the sample time subscript is dropped. g. C ACT−1 = CT−1CA ), therefore eqn. 40), can be written explicity in terms of the model parameters. 4 Using recursion to find matrices H, P, Q This section is here solely because it gives an efficient means of computing the predictions for coding purposes. You are advised to skip it unless computational efficiency is more important than having compact equations. g. [21]). Although it complicates notation a little, for generality the MIMO case will be given here with an MFD model.

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