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M. M. (René) van Paassen
From the Neuromuscular System to Supervisory Control
AbstractThis paper presents two examples, one in the field of manual control, and one in the field of supervisory control, where velocity feedback - although on a different scale, and described in different terms - helps the human operator.
Introduction - manual controlIn manual control of relatively fast continuous systems, for example when driving a car, riding a bike or flying an aeroplane, the properties felt in the manipulator (steering wheel, handlebar or yoke/stick) can play an important role in the handling of the system. The relationship between the human operator, the manipulator and the controlled system can be classified into three different categories (see Figure 1):
Note that it is also possible that this indirect feedback takes place via other means than direct mechanical linking. An example is the Boeing 777, where a hydraulic system simulates the "feel" of the aerodynamic forces on the control surfaces.
Three levels of integration of manipulator dynamics and system
(a) de-coupled, (b) indirect feedback of the system state to the
and (c) direct feedback of a system output to the manipulator.
Figure 2: Human-machine systems laboratory at the Delft University
Technology, featuring a side stick with electro-hydraulic control
Introduction - supervisory controlIn the control of slower systems, and in this case a cement mill is used as an example, the role of the manipulator is less prominent. Control inputs can be given with a mouse and slider on a graphical interface, hardware controls or by keyboard input, but since the controlled system's dynamics are slow compared to these input actions, the actual implementation of the input device and its properties have no influence on the system's response.
Work on such systems is characterised by the operator taking control actions, and subsequently waiting for the system to respond. A typical frequency of control action is 5 per hour (Hollnagel, 1998). This mode of control is further promoted by the fact that large plants are provided with automated controllers for parts of the process. The operator assumes a role of supervisor, giving set-points to the automated controller and monitoring their work.
Sheridan (1987) gives an overview and definitions of supervisory control. The strict definition, according to Sheridan, describes a situation in which the operator gives setpoints to an automated controller, and monitors the supervision of the process. A second definition, which to the author appears a more appropriate, is supervisory control in the broad sense. In this definition, encompasses also the situation where an automated system interprets measured data from the plant, to provide "reports" on the plant's functioning.
This broader definition of supervisory control also applies to the second example considered here, the control of a cement mill, subject of study during the author's stay as a postdoc at the University of Kassel (Paassen, 1995b, 1997). An overview of this system is given in Figure 3. Central component in cement milling is a rotating mill, filled with steel balls or pellets, which, by crushing clinker between the falling and rolling steel balls, grinds clinker to cement. Such a mill is normally operated in a closed loop circuit, with a separating unit (SEPAX), which separates fine cement from the coarser output, with the course output being fed back into the mill. Input feed, with conveyor belts, digging machines and a pre-crusher, an output line, with a pump and storage silos, and a cooling unit, which cools the mill by spraying water in the mill, complete the system.
Overview of the simulation of the cement mill
An experimental interface was developed for (a simulation of) this system. Goal in the development of the interface was to see whether information about goal fullfillment would aid operators in their task. The interface was based on a mix of two techniques, Multilevel Flow Modelling (Lind, 1990), and Ecological Interface Design (Vicente & Rasmussen, 1990, 1992; Bisantz & Vicente, 1994).
Multilevel Flow Modelling is a functional modelling technique that
to express a system in terms of the goals that have to be achieved, and
the functions available to achieve these goals. As such, it is not
for interface design, but the author used a dynamic representation of
MFM model for the process interface. Ecological Interface Design starts
with a mapping of the process onto Rasmussen's Abstraction Hierarchy
1986; Bisantz & Vicente, 1994). This hierarchy shows the goals to
achieved (functional purpose), and functions to achieve these goals at
various levels of abstraction. In this case the goal and function
of MFM was used as a basis for the EID design. Such an interface should
show the to control the system ("affordances" in the parlance of
Gibson (1979)), and the relationship between these possibilities and
achievement of the goals. This in contrast to conventional interfaces,
that usually show little more than the controls and the measured
The inverse of goal achievement, i.e. goal violation, is normally show
through means of alarms (Paassen & Wieringa, 1997).
FeedbackA human (or automatic) controller displays goal-directed behaviour, which means that he will try to control the system so that his objectives will be achieved. Now, both a cement mill and an aircraft are dynamical systems, which means that their output and state will not change instantly, but gradually, over time. In order to support this goal-oriented behaviour, the operator needs to know:
An indirectly coupled manipulator, a conventional yoke in an aircraft, provides a stiffer feel at higher speeds. Automatically, the operator will be inclined to give smaller inputs (smaller in excursion, but similar in size) at high speeds, leading to forces and moments on the aircraft that are approximately the same at low and high speeds. At low speeds, the manipulator will feel very light, warning the pilot of the danger of stall. The feedback is therefore helping the pilot achieve safety.
The active side stick can feed back aircraft roll and pitch rates. Therefore the stick position indicate the first derivative of either the goal (if trying to fly with a certain pitch and roll attitude), or of a sub-goal, thus a contribution to performance, instead of to safety, as with an indirectly coupled manipulator.
A passive manipulator, with the dynamics uncoupled from the
system dynamics, has neither the feedback on the safety of the flight,
nor feedback that aids in achieving higher performance. It would be a
choice for application in an aircraft that is otherwise controlled in a
conventional manner, and indeed, it is not intended as a controller for
conventional aircraft dynamics. The side sticks as used in Airbus
provide input to a closed-loop flight control system. The stick is thus
used as a setpoint device, and the flight control system closes the
that implements the setpoint. In doing so, the controller makes the
dynamics, seen from the setpoint
input to the attitude response, look like a single integrator. In addition to this, the flight control system implements protection of the aircraft envelope; it is - with a fully operational flight control system - not possible to stall the aircraft or to achieve an excessive load factor. Thus part of the responsability for achieving safety goals, and part of achieving production goals is shifted to the flight control computer.
In manual control of fast reacting systems, use of the manipulator as a feedback device, in either of the two of the three ways discussed above, helps pilot performance by providing feedback through the neuromuscular system. In the control of a slower system, such as a cement mill, feedback through manipulators is not usually considered important, because of the slower speed of such systems, there is ample time to observe such feedback from visual displays.
It is however, as with the faster systems, important to be able to observe not only goal achievement, but also the development towards - or from - goal achievement. The problems are different:
EID interface for the cement mill simulation.
In the cement mill, one of the problems is that the milling process
itself is not measured directly. One can observe power consumption,
level in the mill (only approximately), the feed of the mill and the
flow of the mill. The feed can be controlled, and the output can be
a little, one can choose to accept a coarser product and thereby empty
the mill faster. However, how finely the material in the mill has been
ground is unknown. It is largely the fineness of the material in the
that determines the outflow. At a
start-up, the mill is filled close to its optimim level, then the inflow is reduced a little, and just when the material is fine enough, and the outflow is picking up, one should increase the inflow to get a nice steady production
An experimental interface, based on Ecological Interface Design, was developed for the cement mill (Figure 4). This interface supports the operator in seeing the development of the achievement of the production goal.
The following elements are present:
The dotted boxes placed around the EID graphs show the controls, and
possibly sub-goals (clicking these opens other windows) that are needed for
The interface helps the operator achieve the optimum fill level. The
slope of the mass balance provides rate information, so also here the
trend in goal achievement is shown. The process dynamics are complex,
normally a process simulation for a cement mill is of very high
order. However, to give the operator an impression of the state of the
milled material, a low-order approximation is given with the
efficiency graph, the milling energy inventory and the specific
milling energy. This enables one to anticipate the point where the
mill starts producing, and, although not exactly giving its
derivative, it helps in seeing the development of the output flow. The
specific energy also allows for a quick estimate of the quality of the
Lessons learnedClassic control theory, and its application to human control
ConclusionsNeither the active side stick, nor the functional interface for the cement mill have found application outside laboratory environments. However, the research efforts are not lost. The questions raised by the active side stick's extraordinary performance triggered research to find out more about the interaction between a pilot and the manipulator (Paassen, 1994, 1995a), which in turn triggerred the development of measurement techniques for measuring human operator's reponses in a multi-loop feedback systems (Paassen & Mulder, 1998; Mulder, 1999). The MFM/EID interface took some shortcuts in the functional modelling, for which correct alternatives are given in (Paassen & Wieringa, 1999). Continued work in this field looks at EID interfaces for certain aspects of aircraft control (Coelho, Paassen, Mulder & Mulder, 2000; Paassen, Coelho & Mulder, 2001). The main conclusion is that manual control of fast systems and supervisory control of slower systems do have a surprising lot in common, although one sometimes needs some reflection to see this.
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