Supervisory Control

Supervisory control may be defined by the analogy between a supervisor of subordinate staff in an organization of people and the human overseer of a modern computer-mediated semiautomatic control system. The supervisor gives human subordinates general instructions which they in turn may translate into action. The supervisor of a computer-controlled system does the same.
Defined strictly, supervisory control means that one or more human operators are setting initial conditions for, intermittently adjusting, and receiving high-level information from a computer that itself closes a control loop in a well-defined process through artificial sensors and effectors. For some time period the computer controls the process automatically.
By a less strict definition, supervisory control is used when a computer transforms human operator commands to generate detailed control actions, or makes significant transformations of measured data to produce integrated summary displays. In this latter case the computer need not have the capability to commit actions based upon new information from the environment, whereas in the first it necessarily must. The two situations may appear similar to the human supervisor, since the computer mediates both human outputs and human inputs, and the supervisor is thus removed from detailed events at the low level.

FIGURE 6.1.2Direct manual control-loop analysis.

Supervisory control system here the human operator issues commands to a human-interactive computer capable of understanding high-level language and providing integrated summary displays of process state information back to the operator. This computer, typically located in a control room or cockpit or office near to the supervisor, in turn communicates with at least one, and probably many (hence the dotted lines), task-interactive computers, located with the equipment they are controlling. The task-interactive computers thus receive subgoal and conditional branching information from the human-interactive computer. Using such information as reference inputs, the task-interactive computers serve to close low-level control loops between artificial sensors and mechanical actuators;i.e., they accomplish the low-level automatic control.
The low-level task typically operates at some physical distance from the human operator and his human-friendly display-control computer. Therefore, the communication channels between computers may be constrained by multiplexing, time delay, or limited bandwidth. The task-interactive computer, of course, sends analog control signals to and receives analog feedback signals from the controlled process, and the latter does the same with the environment as it operates (vehicles moving relative to air, sea, or earth, robots manipulating objects, process plants modifying products, etc.).
Supervisory command and feedback channels for process state information are shown in Figure 6.1.3 to pass through the left side of the human-interactive computer. On the right side are represented decisionaiding functions, with requests of the computer for advice and displayed output of advice (from a database, expert system, or simulation) to the operator. There are many new developments in computerbased decision aids for planning, editing, monitoring, and failure detection being used as an auxiliary part of operating dynamic systems. Reflection upon the nervous system of higher animals reveals a similar kind of supervisory control wherein commands are sent from the brain to local ganglia, and peripheral motor control loops are then closed locally through receptors in the muscles, tendons, or skin.
The brain, presumably, does higher-level planning based on its own stored data and “mental models,” an internalized expert system available to provide advice and permit trial responses before commitment to actual response.
Theorizing about supervisory control began as aircraft and spacecraft became partially automated. It became evident that the human operator was being replaced by the computer for direct control responsibility, and was moving to a new role of monitor and goal-constraint setter. An added incentive was the U.S. space program, which posed the problem of how a human operator on Earth could control a manipulator arm or vehicle on the moon through a 3-sec communication round-trip time delay. The only solution which avoided instability was to make the operator a supervisory controller communicating intermittently with a computer on the moon, which in turn closed the control loop there. The rapid development of microcomputers has forced a transition from manual control to supervisory control in a variety of industrial and military applications (Sheridan, 1992).
Let us now consider some examples of human-machine interaction, particularly those which illustrate supervisory control in its various forms. First, we consider three forms of vehicle control, namely, control of modern aircraft, “intelligent” highway vehicles, and high-speed trains, all of which have both human operators in the vehicles as well as humans in centralized traffic-control centers. Second, we consider telerobots for space, undersea, and medical applications.

Direct Manual Control

In the 1940s aircraft designers appreciated the need to characterize the transfer function of the human pilot in terms of a differential equation. Indeed, this is necessary for any vehicle or controlled physical process for which the human is the controller, see Figure 6.1.2. In this case both the human operator H and the physical process P lie in the closed loop (where H and P are Laplace transforms of the component transfer functions), and the HP combination determines whether the closed-loop is inherently stable (i.e., the closed loop characteristic equation 1+HP = 0 has only negative real roots).
In addition to the stability criterion are the criteria of rapid response of process state x to a desired or reference state r with minimum overshoot, zero “steady-state error” between r and output x, and reduction to near zero of the effects of any disturbance input d. (The latter effects are determined by the closed-loop transfer functions x=HP/(1+ HP)r+ 1/(1+ HP)d
, where if the magnitude of
H is large enough
HP /(1+ HP) approaches unity and 1/(1+ HP) approaches 0. Unhappily, there are ingredients of
H which produce delays in combination with magnitude and thereby can cause instability.
Therefore, H must be chosen carefully by the human for any given P.)
Research to characterize the pilot in these terms resulted in the discovery that the human adapts to a wide variety of physical processes so as to make HP=K(1/s)(esT). In other words, the human adjusts H to make
HP constant. The term K is an overall amplitude or gain, (1/ s) is the Laplace transform of an integrator, and ( e-sT) is a delay T long (the latter time delay being an unavoidable property of the nervous system). Parameters
K and T vary modestly in a predictable way as a function of the physical process and the input to the control system. This model is now widely accepted and used, not only in engineering aircraft control systems, but also in designing automobiles, ships, nuclear and chemical plants, and a host of other dynamic systemsŲ²

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