By Huang Sunan PhD, Tan Kok Kiong PhD, Lee Tong Heng PhD (auth.)
The presence of substantial time delays within the dynamics of many commercial tactics, resulting in tough difficulties within the linked closed-loop keep watch over platforms, is a well-known phenomenon. The functionality possible in traditional suggestions keep an eye on platforms will be considerably degraded if an commercial strategy has a comparatively huge time hold up in comparison with the dominant time consistent. below those situations, complicated predictive keep an eye on is important to enhance the functionality of the keep an eye on approach considerably.
The ebook is a centred remedy of the subject material, together with the basics and a few cutting-edge advancements within the box of predictive regulate. 3 major schemes for complicated predictive keep watch over are addressed during this book:
• Smith Predictive Control;
• Generalised Predictive Control;
• a kind of predictive regulate according to Finite Spectrum Assignment.
A immense a part of the ebook addresses software concerns in predictive regulate, offering a number of fascinating case stories for extra application-oriented readers. therefore, whereas the ebook is written to function a sophisticated keep watch over reference on predictive regulate for researchers, postgraduates and senior undergraduates, it's going to be both helpful to these commercial practitioners who're prepared to discover using complex predictive regulate in genuine difficulties. The prerequisite for gaining greatest reap the benefits of this ebook is a easy wisdom of keep an eye on structures, akin to that imparted by way of a primary undergraduate path on regulate platforms engineering.
Advances in business Control goals to file and inspire the move of know-how on top of things engineering. The swift improvement of keep watch over know-how has an effect on all parts of the keep watch over self-discipline. The sequence bargains a chance for researchers to give a longer exposition of recent paintings in all features of business control.
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Additional resources for Applied Predictive Control
17) + R)-l FrQ being the first m rows of the 3. 19) This performance criterion is used in many predictive controllers. 20) where Fu = [ H(::I)B HT~2)B ;B ... HT(P2: - l)B ::: H APi ~ ~P2-1 B 1 ' LlU = [Llu(t) , Llu(t + 1), ... , Llu(t + P2)f, F2 = [ H(::I)B H(APi-l + APl-2 ~ ... + AP2-P2- 1)B 1 ' and T(j) = 2:~~~APi-P2-1+k. 15) yields: LlU = (F'ftQFu + rI)-l F'ftQ[Yd - Gx(t) - F2U(t -1)]. 21) gives the complete control sequence minimising J over the prediction horizon, only the first m row values are actually applied to the system as the control signal.
Signals v and u in Fig. 7 are viewed as the system output and 24 Applied Predictive Control r(t) yet) J6-~--------,--l~~ i;;:-l e(t) vet) ~~~----' Fig. 7. 16). ,Tu(t + T)dT. 23) as it now enters the system through the generalised system. ) U(s) q(W~(s) e-LsU(s). 25) and the nominal system is stable provided that pes) and q(s) are Hurwitz polynomials . 2. 4 The system in Fig. 7 achieves asymptotic tracking and regulation in response to a step set-point change and/or load disturbance provided that it is stable.
22) where a(s) = -ap(s) and b(s) = sbp(s). Note that in the general case, G(s) refers to the actual system. However, for the modified FSA method, the actual system is denoted by Gp(s) and the generalised system by G(s). It is assumed that the system has no zero at s = 0 so that a( s) and b( s) are coprime. Signals v and u in Fig. 7 are viewed as the system output and 24 Applied Predictive Control r(t) yet) J6-~--------,--l~~ i;;:-l e(t) vet) ~~~----' Fig. 7. 16). ,Tu(t + T)dT. 23) as it now enters the system through the generalised system.