Week 11-2: Manual Control

1. 1 Week 11-2: Manual Control This module will provide you with a general overview of the needs assessment process. Later modules will provide more detail on the steps involved. This module will provide you with a general overview of the needs assessment process. Later modules will provide more detail on the steps involved.

2. 2 Week 11 Topics Lecture 11-1 Open Loop vs. Closed-loop systems Modeling movement time: Fitt�s law Elements of the Tracking loop Lecture 11-2 Revisting Fitt�s Law as a feedback system Tracking capabilities of the human operator Multi-axis control Spectral Analysis and the cross-over model

3. Transfer Functions and Control Order transfer function: function that relates system input to system output control order: the number of integrations performed by the transfer function Two important parameters Gain: ratio of system output to system input Lag pure time delay exponential lag 3

4. Continuous Tracking of Dynamic Systems Transfer Functions and Control Order (cont.) Zero-order: displacement controller, no integration Example: computer mouse Types Pure gain Pure time delay exponential lag Good for systems designed to control position precisely controllers without a natural zero point 4

5. Continuous Tracking of Dynamic Systems Transfer Functions and Control Order (cont.) First-order: velocity controller, single integration Example: car steering wheel Output equals integral (sum) of input input displacement is proportional to output velocity Good for systems designed to control velocity precisely controllers with a natural zero point (joysticks) Similar response to zero-order controller with exponential lag 5

6. Continuous Tracking of Dynamic Systems Transfer Functions and Control Order (cont.) Second-order: acceleration controller, double integration Example: car breaks and gas pedals Output equals double-integral of input input displacement is proportional to output acceleration operator must move to negative position to slow down overcorrection can lead to instability and oscillatory behavior 6

7. Continuous Tracking of Dynamic Systems Transfer Functions and Control Order (cont.) Minus-first-order: differentiator output is proportional to rate of change of the input (derivative) can be used in series with first and second-order controllers to reduce control order 7

8. Human Operator Limits in Tracking Lags generated by perceptual-motor processing time effective time delay zero- and first-order systems: 150-300 ms second-order systems: 400-500 ms Bandwidth in information transmission Elkind & Sprague (1961): upper frequency limit for human tracking of unpredictable signals is between 0.5-1.0 Hz (2 corrective decisions per second) if signals are predictable then bandwidth increases to 2-3 Hz-->motor limit 8

9. Human Operator Limits in Tracking Difficulty in predicting or anticipating movement large system lags require operator to predict future states based on the system�s current trajectory --> velocity and acceleration humans are poor at perceiving changes in velocity and acceleration, thus poor at predicting Anticipation requires mental resources for calculations --> increases mental workload S-R compatibility: misaligned axes of controls and displays increase error and control reversals 9

10. Human Operator Limits in Tracking System Dynamics and Tracking Performance Gain: intermediate is best, inverted �U-shaped� function Time delay: directly related to magnitude of error System Order zero and first are roughly equal Why? Successful tracking requires both position and velocity to be matched If space is constrained, first order offers better economy of movement Second-order and higher are much more difficult can lead to instability 10

11. Instability and Feedback Negative feedback � feedback that tends to reduce error � self-correcting systems Most systems typically have negative feedback Purposeful control means trying to minimize error Positive feedback � feedback that tends to increase error Not common in purposeful control, but possible in some physical systems If left unattended, small errors inevitably lead to larger errors 11

12. Displays & Closed-loop Control Goal: eliminate effects of lags or higher-order systems Input prediction: preview displays Output Prediction: predictive displays: computer estimates future position and adds a second symbol to the display representing this future position (predictive span) quickened displays: same as predictive except no symbol representing current position, only future position is displayed 12

13. Input Devices Constraints on Input devices supporting continuous closed-loop control Physical constraints space, fatigue, vibration, G-forces Control-order compatibility Speed-accuracy trade-off Voice control? 13

14. Multi-axis Control Many tasks require the operator to control more than one dimension of a dynamic system Independent vs. Cross-coupled axes Example of independent: speed and steering Example of Cross-coupled: aircraft pitch and roll Hierarchical cross-coupled (Fig. 10.13) e.g., heading and lateral position, yaw and roll, thrust and speed operator sets goal based on highest order system but controls a lower order system 14 After Abbott and Costello High HT: very consistent stimulus-response mappings, but although information was conveyed (�back to third again�), misunderstandings perpetuated. Costello�s conceptual model of the team was inaccurate Why was the misunderstanding not corrected? Ineffective feedbackAfter Abbott and Costello High HT: very consistent stimulus-response mappings, but although information was conveyed (�back to third again�), misunderstandings perpetuated. Costello�s conceptual model of the team was inaccurate Why was the misunderstanding not corrected? Ineffective feedback

15. Factors Affecting Multi-axis Control Display Separation: multi-axis control is impeded by spatially separated displays--increases visual scanning Integrated vs. Separated Displays and Controls Advantage for integrated displays: object perception Smaller advantage for integrated controls: cross-talk Integral vs. Separable Axes: Proximity compatibility Resource Demand: Higher control orders more difficult Similarity of Control Dynamics: best to require only a single mental model of control dynamics for all axes 15 After Abbott and Costello High HT: very consistent stimulus-response mappings, but although information was conveyed (�back to third again�), misunderstandings perpetuated. Costello�s conceptual model of the team was inaccurate Why was the misunderstanding not corrected? Ineffective feedbackAfter Abbott and Costello High HT: very consistent stimulus-response mappings, but although information was conveyed (�back to third again�), misunderstandings perpetuated. Costello�s conceptual model of the team was inaccurate Why was the misunderstanding not corrected? Ineffective feedback

16. Modeling Human Operator in Manual Control Frequency vs. Time domain Bode plots (Figures 10.16-10.19) Y-axes Gain: log10(output/input amplitude ratio), expressed in units of decibels (dB) Phase Lag: expressed in units of degrees X-axis: log10(frequency) Representations of 0, 1st, and 2nd order systems 16

17. The Cross-over Model Good control achieved by Low error High degree of stability Cross-over model states that human adapts to controller and system dynamics such that the total open-loop transfer function e(t)?o(t) is first-order Operator compensates for higher-order control and system dynamics by differentiating Gain is adjusted to balance error and stability 17