IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 6, JUNE 2009 1963
Constrained Model Predictive Control of the Drive
System With Mechanical Elasticity
Marcin Cychowski, Member, IEEE, Krzysztof Szabat, and Teresa Orlowska-Kowalska, Senior Member, IEEE
Abstract—In this paper, the application of model predictive
control (MPC) for high-performance speed control and torsional
vibration suppression in the drive system with flexible coupling
is demonstrated. The control methodology presented in this pa-
per relies on incorporating the drive’s safety and physical lim-
itations directly into the control problem formulation so that
future constraint violations are anticipated and prevented. In
order to reduce the computational complexity, the standard MPC
controller is replaced by its explicit form. The resulting explicit
controller achieves the same level of performance as the con-
ventional MPC, but requires only a fraction of the real-time
computational machinery, thus leading to fast and reliable im-
plementation. The simulation results are confirmed by laboratory
experiments.
Index Terms—Constrained control, elastic couplings, industrial
drives, model predictive control (MPC).
I. I NTRODUCTION
D
RIVE SYSTEMS are a cornerstone of modern industrial
processes including rolling-mills, conveyor belts, robot
manipulators, and textile or paper machines [1]–[6]. These
systems are typically composed of a motor coupled to a load
machine through a metal shaft. Large inertias of the motor-load
system together with a long shaft create an elastic system. The
torsional characteristics of the mechanical coupling, which are
often neglected in the drive control synthesis, greatly influence
the torque transmission properties of the drive system and
results in increased angular vibrations of the shaft. Excessive
shaft twists and poorly damped torsional vibrations are detri-
mental to the drive’s performance greatly compromising prod-
uct quality and system reliability, and in some cases leading to
instability and failure of the entire drive system [3]–[9].
The problem of suppressing torsional vibrations in two-mass
drive systems has been a subject of extensive research efforts
resulting in several different control proposals. In this group,
proportional plus integral (plus derivative) [PI(D)] controllers
are the most widely employed types of control solutions for
modern electrical drive systems [1], [9]. These algorithms are
simple, well established, and accepted by industry but lack
Manuscript received August 30, 2008; revised February 9, 2009. First
published February 27, 2009; current version published June 3, 2009. This
work was supported in part by Enterprise Ireland under the Applied Research
Enhancement Program (Grant RE/05/003).
M. Cychowski is with the Department of Electronic Engineering, Cork
Institute of Technology, Cork, Ireland (e-mail: marcin.cychowski@cit.ie).
K. Szabat and T. Orlowska-Kowalska are with Wroclaw University of
Technology, Institute of Electrical Machines, Drives and Measurements,
50-372 Wroclaw, Poland (e-mail: krzysztof.szabat@pwr.wroc.pl; teresa.
orlowska-kowalska@pwr.wroc.pl).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIE.2009.2015753
the ability to shape the system speed response and suppress
the torsional oscillations simultaneously. If high-performance
closed-loop control is required, the application of additional
feedbacks from selected state variables is necessary [6], [7],
[9]–[13]. As shown in [9], the inclusion of one additional
feedback control loop guarantees effective damping of torsional
oscillations although shaping of the system speed response
within a wide range of set points cannot be realized. These
two objectives can be achieved by incorporating feedback loops
from all system state variables (torsional torque, load speed,
and disturbance torque) [6], [9], [12], [13]. A more detailed
literature review on this topic can be found in [9] and [13].
In drive systems with significant parameter variations, more
sophisticated control paradigms such as nonlinear or adaptive
control can be adopted in order to achieve the required dynamic
performance of the system [13]–[16]. In [7] and [15], sliding-
mode control is demonstrated which achieves good dynamic
properties and a satisfactory level of robustness to plant parame-
ter variations. A strategy based on a self-tuning regulator and
nonlinear Kalman filter is proposed in [13]. In this paper, the
desired transient properties of the drive system are obtained by
allowing for the simultaneous adaptation of the control law and
the observer gain matrix. The application of neuro-fuzzy adap-
tive control has been suggested in [14] demonstrating feasibility
and good robustness properties. More detailed reviews can be
found in [13]–[15].
In practice, all industrial processes are subject to constraints.
Specific process variables must not violate specified bounds
due to safety limitations, environmental regulations, consumer
specifications, and physical restrictions [17], [18]. In two-
mass drive systems for instance, the produced motor torque
can only operate within its physical limits (imposed by the
drive inverter) while the mechanical coupling must never be
exposed to stresses exceeding the shaft’s ultimate tensile stress
limit for safety reasons. While violating the electromagnetic
torque constraint might in some applications be acceptable,
exceeding the shaft torque constraint may result in damage to
the shaft and ultimately in the failure of the entire drive system.
Considering everything previously mentioned, it is surprising
that this important practical problem has received very little
attention from the drive control community. The main focus
has primarily been on ensuring that the physical limitation
of the motor torque variable (control input) is respected [13],
[19]. An approach for direct torsion control based on the
sliding-mode principle has been presented in [7]. In this paper,
the torsion of the shaft (expressed as a difference between
motor and load angular positions) is explicitly incorporated
as a control variable. The drawbacks of the technique are the
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