Discrete-Time Model Predictive Control

More than 25 years after model predictive control (MPC) or receding horizon control ... The focus of this chapter is on MPC of constrained dynamic sys...

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Key words: Motion Cueing, Model Predictive Control, Vestibular System, Dynamic Platform, Optimization. Introduction .... calculate the result at each sample time, without off-line precalculations. After having .... 995-1003, 2009. [Fer1] H.J. ...

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Then, x(k + N|k) can be obtained at the instant k following the mode trace λ, ... antee the stability of the system (5) at the instant k +N after N steps predictive ...

Model predictive control is formulated as a repeated solution of a (finite) horizon open- loop optimal control problem subject to system dynamics and input and ...

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Abstract Model Predictive Control (MPC) is a con- ... Stochastic Model Predictive Control (SMPC) refers to a family of numerical optimization strategies for controlling stochastic systems subject to constraints ..... ∼stoorvogelaa/subm01.pdf.

world, is one possible candidate to meet these demands. ... This chapter reviews the main principles underlying NMPC and outlines some of ... presented Section 3. ..... (1996) An overview of industrial model predictive control technology. .... predic

First-generation MPC systems were developed in- dependently in the 1970s ... 20.1 OVERVIEW OF MODEL PREDICTIVE. CONTROL. The overall objectives of an MPC controller have been summarized by Qin and Badgwell (2003):. 1. Prevent violations of .... model

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If we want to control the position of a car, MPC is equivalent to look at the road through the windscreen, whereas classical control only is allowed to look in the rear window. ... Decision and Control, Sydney, Australia, 2000. The material in ......

Sep 27, 2005 - Lecture Notes for the course SC4060. Model Predictive .... 8 MPC using a feedback law, based on linear matrix inequalities. 165 ..... Flexibility and timing are key parameters that drive performance. ...... ∆xo(k + 1) ] = [ I Co ....

3. A view of the pilot canal. Tank. Monovar valve. Pool 1. Pool 2. Pool 3. Pool 4. G1. G2. G3. G4. M1. M2. M3. M4. Q1. Q2. Q3. Q4. Vo1. Vo2. Vo3. Vo4 h0 c1 m1 j1 c2 m2 j2 c3 m3 j3 c4 m4. Fig. 4. Schematics of the pilot canal. are orifices in the chan

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Mar 13, 2013 - critical systems, such as chemical process control systems.3. Motivated by the above, ... nity over the last decade; see, for example, the book in Ref. 4 and the ..... Part 1. When x(t) is maintained in Xq0 for t < tf and in Xqj for t

We approach this problem within the model predictive control (MPC) framework by representing the ... the configuration space in terms of unit dual quaternions. ...... 0.75 s. 238.1 kg. 3208 kN. 975 Nm. 24 s. 166. 1.29 s. 262.2 kg. 3010 kN.

Aug 29, 2014 - considered by model predictive control allocation (MPCA) lr lf. Ftx,rl. Ftx,rr. Ftx,fr ls ... include slip constraints is explained. A simulation example.

k Ruk. ) (3) where γ2 is the upper bound of the worst case performance (or the .... expressions in a form that suits with our new format of the closed loop equation ...

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Model predictive control (MPC) is an advanced control algorithm that has been very successful in the control industries due to its capability of handling multi input multi output (MIMO) systems with physical constraints. In MPC, the control action ar

Stable control of packed distillation column is of great importance for improvements of operation efficiency and higher product concentration. ... Key words: Packed distillation column Decoupling Constrained model predictive control. INTRODUCTION ...

extended the NMPC approach as well as its stability theory to account for .... Biegler, 2010) and leads to offset-free formulations to deal with state and output ...

where the MPC optimization is treated as a robust multi– parametric optimization problem. Explicit robust MPC problems with quadratic costs have not yet been ...