Nonlinear Predictive Control Using Particle Swarm Optimization

Name: Nonlinear Predictive Control Using Particle Swarm Optimization
Brand: VDM Verlag
SKU: 9783639249668
Price: 20594 HUF
Availability: InStock

Application to Power Systems

Szerző: Muhammad Salman Yousuf

Nyelv:

Kötés: Puha kötésű

Kiadó: VDM Verlag

Elérhetőség: Kiadói készleten rendelésre

Küldés 17-27 napon belül

20 594 Ft

It is well recognized that linear control methods are not always the optimum way to deal with typica...

Információk a könyvről

Szerző

Muhammad Salman Yousuf

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2010

oldal

144

EAN

9783639249668

ISBN

3639249666

Enbook ID

06832510

Kiadó

VDM Verlag

Súly

222

Méretek

152 x 229 x 9

Teljes leírás

It is well recognized that linear control methods are not always the optimum way to deal with typical nonlinear plants. Due to continual increment in the complexity of systems and tighter product specifications, the quality requirements from automatic control have increased. Recently, the available computing power has rose to fantastic levels as well. Consequently, computationally intensive control methods can now be applied to complex systems. Model Predictive Control (MPC) techniques were developed to obtain tighter control and were applied successfully to several industrial applications. In this book, a new implementation of MPC is proposed using Particle Swarm Optimization (PSO). The proposed method formulates the MPC as an optimization problem and PSO is used to minimize it. This gives advantages like adaptability, possibility of varying control objectives, and enhanced capability of handling constraints. The proposed method is applied to an area of industrial systems that has been relatively unexplored by MPC, i.e. power systems. Both SISO and MIMO nonlinear systems are considered. Three practical Power System problems are taken and the proposed technique is applied to them.

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Nonlinear Predictive Control Using Particle Swarm Optimization

Application to Power Systems

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