Heigh Level Control
HIGH-LEVEL CONTROLS
Controllers in a complex monitor and control system are typically organized hierarchically. One or more digital controllers at the lowest level directly control the physical plant. Each output of a higher-level controller is a reference input of one or more lower-level controllers. With few exceptions, one or more of the higher-level controllers interfaces with the operator( s).
Examples of Control Hierarchy
For example, a patient care system may consist of microprocessor-based controllers that monitor and control the patient’s blood pressure, respiration, glucose, and so forth. There may be a higher-level controller (e.g., an expert system) which interacts with the operator (a nurse or doctor) and chooses the desired values of these health indicators. While the computation done by each digital controller is simple and nearly deterministic, the computation of a highlevel controller is likely to be far more complex and variable. While the period of a lowlevel control-law computation ranges from milliseconds to seconds, the periods of high-level
control-law computations may be minutes, even hours. Figure 1–4 shows a more complex example: the hierarchy of flight control, avionics, and air traffic control systems.5 The Air Traffic Control (ATC) system is at the highest level. It regulates the flow of flights to each destination airport. It does so by assigning to each aircraft an arrival time at each metering fix6 (or waypoint) en route to the destination: The aircraft is supposed to arrive at the metering fix at the assigned arrival time. At any time while in flight, the assigned arrival time to the next metering fix is a reference input to the on-board flight management system. The flight management system chooses a time-referenced flight path that brings the aircraft to the next metering fix at the assigned arrival time. The cruise speed, turn radius, decent/accent rates, and so forth required to follow the chosen time-referenced flight path are the reference inputs to the flight controller at the lowest level of the control hierarchy.
In general, there may be several higher levels of control. Take a control system of robots that perform assembly tasks in a factory for example. Path and trajectory planners at the second level determine the trajectory to be followed by each industrial robot. These planners typically take as an input the plan generated by a task planner, which chooses the sequence of assembly steps to be performed. In a space robot control system, there may be a scenario planner, which determines how a repair or rendezvous function should be performed. The plan generated by this planner is an input of the task planner.
Guidance and Control
While a digital controller deals with some dynamical behavior of the physical plant, a secondlevel controller typically performs guidance and path planning functions to achieve a higher-
level goal. In particular, it tries to find one of the most desirable trajectories among all trajectories that meet the constraints of the system. The trajectory is most desirable because it optimizes some cost function(s). The algorithm(s) used for this purpose is the solution(s) of some constrained optimization problem(s).
As an example, we look again at a flight management system. The constraints that must be satisfied by the chosen flight path include the ones imposed by the characteristics of the aircraft, such as the maximum and minimum allowed cruise speeds and decent/accent rates, as well as constraints imposed by external factors, such as the ground track and altitude profile specified by the ATC system and weather conditions. A cost function is fuel consumption: A most desirable flight path is a most fuel efficient among all paths that meet all the constraints and will bring the aircraft to the next metering fix at the assigned arrival time. This problem is known as the constrained fixed-time, minimum-fuel problem. When the flight is late, theflight management system may try to bring the aircraft to the next metering fix in the shortest time. In that case, it will use an algorithm that solves the time-optimal problem.
Complexity and Timing Requirements. The constrained optimization problems that a guidance (or path planning) system must solve are typically nonlinear. In principle, these problems can be solved using dynamic programming and mathematical programming techniques. In practice, however, optimal algorithms are rarely used because most of them are not only very compute intensive but also do not guarantee to find a usable solution. Heuristic algorithms [GiMW] used for guidance and control purposes typically consider one constraint at a time, rather than all the constraints at the same time. They usually start with an initial condition (e.g., in the case of a flight management systems, the initial condition includes the initial position, speed, and heading of the aircraft) and some initial solution and adjust the value of one solution parameter at a time until a satisfactory solution is found.
Fortunately, a guidance system does not need to compute its control laws as frequently as a digital controller. Often, this computation can be done off-line. In the case of a flight management system, for example, it needs to compute and store a climb speed schedule for use during takeoff, an optimum cruise trajectory for use en route, and a descent trajectory for landing. This computation can be done before takeoff and hence is not time-critical. While in-flight, the system still needs to compute some control laws to monitor and control the transitions between different flight phases (i.e., from climb to cruise and cruise to descent) as well as algorithms for estimating and predicting times to waypoints, and so forth. These timecritical computations tend to be simpler and more deterministic and have periods in order of seconds and minutes. When the precomputed flight plan needs to be updated or a new one computed in-flight, the system has minutes to compute and can accept suboptimal solutions when there is no time.
Other Capabilities. The complexity of a higher-level control system arises for many other reasons in addition to its complicated control algorithms. It often interfaces with the operator and other systems. To interact with the operator, it updates displays and reacts to operator commands. By other systems, we mean those outside the control hierarchy. An example is a voice, telemetry, or multimedia communication system that supports operator interactions. Other examples are radar and navigation devices. The control system may use the information provided by these devices and partially control these devices.
An avionic or flight management system has these capabilities. One of its functions is to update the display of radar, flight path, and air-data information. Like keyboard monitoring, the display updates must done no less frequently than once every 100 milliseconds to achieve a satisfactory performance. Similarly, it periodically updates navigation data provided by inertial and radio navigation aids.7 An avionics system for a military aircraft also does tracking and ballistic computations and coordinates radar and weapon control systems, and it does them with repetition periods of a few to a few hundred milliseconds. (You can find detailed timing information on this types of avionics system in [LoVM].) The workload due to these functions is demanding even for today’s fast processors and data links.