Model predictive control is a form of control in which the current control action is obtained by
solving, at each sampling instant, a finite horizon open-loop optimal control problem, using …

The control problem was formulated in the previous chapters considering all signals to
possess an unlimited range. This is not very realistic because in practice all processes are …

This book provides a comprehensive treatment of the principles underlying optimal
constrained control and estimation. The contents progress from optimisation theory, fixed …

The series Advances in Industrial Control aims to report and encourage technology transfer
in control engineering. The rapid development of control technology impacts all areas of the …

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Pneumatic artificial muscles (PAMs) usually exhibit strong hysteresis nonlinearity and time-
varying features that bring PAMs modeling and control difficulties. To characterize the …

Progress in the design and use of Model-Based Predictive Control is reviewed. The two-
degree-of-freedom solution of many predictive algorithms enables optimal set-point …

The paper deals with I/O versions of receding horizon controllers based on the minimization
of multistep quadratic costs with the constraint that the terminal state goes to zero. The …

In the first chapters, this paper contains a survey on the theory of ordinary characters of finite
reductive groups with non-connected centre. The last chapters are devoted to the proof of …

We present a dual-receding horizon controller with deadzone for the control of constrained
linear discrete-time systems. This controller relaxes the feasibility requirements of the …