https://ntrs.nasa.gov/api/citations/19760004259/downloads/19760004259.pdf

Paper: A survey of design methods for failure detection in dynamic systems

The purpose of this paper is to summarize some results obtained for the adaptive control of the F-8C aircraft using the so-called MMAC method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the "identification" aspects of the design using hypothesis testing ideas, and the performance of the closed-loop adaptive system.

The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method--Part I: Equilibrium flight

The problem of state estimation for discrete systems with parameters which may be switching within a finite set of values is considered. In the general case it is shown that the optimal estimator requires a bank of elemental estimators with its number growing exponentially with time. For the Markov parameter case, it is found that the optimal estimator requires only N2 elemental estimators where N is the number of possible parameter values.

State Estimation for Discrete Systems with Switching Parameters

Dynamic Models for Torque Converter Equipped Vehicles

Multiple model adaptive control with mixing

This paper describes the application of linear quadratic (LQ) optimal control theory to the design of electronic automotive engine controls. The resulting structure of the control is different from conventional controls in that the accelerator pedal is connected to the microcomputer control rather than directly to the fuel metering device. This strategy is analogous to the "fly-by-wire" aircraft concept. Simulation results indicate that this approach has better engine torque and speed responses to driver commands. This suggests the possibility of improved vehicular driveability. An LQ tracking controller was designed using constant coefficient state variable models (17 states) obtained by linearizing about nomional operating points. Time delays were modeled by first-order Pade approximations. Carburetor throttle blade position, spark advance, exhaust gas recirculation, and fuel flow were defined as controls and output variables include speed, torque, manifold vacuum, fuel and air flows, and exhaust emissions (carbon monoxide, hydrocarbons, and oxides of nitrogen). It is assumed that both engine torque and exhaust emissions are Similarly affected by actuator, intake, and combustion dynamics, thereby allowing the experimental models to be derived from torque response data. Parameter values for the models are derived from measured static data and perturbation frequency response tests about the nominal operating conditions. Simulations show that the optimal design has superior driver command step response performance. Whereas the conventionally controlled lean calibrated engine has a torque sag (suggestive of poor driveability), the optimal design yields a smooth torque increase with no torque undershoot. This explained physically by the fact that the LQ controller slows down the air control loop (throttle) to match line slower fuel control loop dynamics, thereby avoiding the lean air-fuel ratio transients which are the main cause of the torque sag. In addition, the spark is advanced rapidly to achieve the initial torque increase.

On the design of electronic automotive engine controls using linear quadratic control theory

The purpose of this paper is to summarize results obtained for the adaptive control of the F-8C aircraft using the so-called MMAC method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the "identification" aspects of the design using hypothesis testing ideas, and the performance of the closed loop adaptive system.

/pdf/the-stochastic-control-of-the-f-8c-aircraft-using-the-nu1v253p65.pdf

The stochastic control of the F-8C aircraft using the multiple model adaptive control (MMAC) method

A suboptimal dynamic compensator to be used in conjunction with the ordinary discrete-time Kalman filter is derived. The resultant compensated Kalman filter has the property that steady-state bias estimation errors, resulting from modelling errors, are eliminated. The implementation of the compensated Kalman filter involves the use of accumulators in the residual channels in addition to the nominal dynamic model of the stochastic system.

The discrete-time compensated Kalman filter

In this short paper, we illustrate the application of recently developed notions of multivariable stability margins to the analysis of vehicle flight control systems. Specifically, three designs are developed for the lateral axis dynamics of the CH- 47B helicopter, all of which satisfy classical design specifications. However, two of the designs exhibit extreme sensitivity to modeling errors that cannot be detected by measuring classical single-loop stability margins. These sensitivities are readily detected and investigated by computing the new multivariable stability margins.

Multivariable stability margins for vehicle flight control systems

This paper discusses how the frequency domain optimality conditions of the linear quadratic system can be used in system design synthesis It attempts to show that the control and state weighting matrices in an LQ design can be used to facilitate tradeoffs of feedback properties such as performance, disturbance rejection, system robustness and sensitivity, in order for the control system to meet a set of specifications The fact that an additional tradeoff dimension is provided by the directionality of the multivariable structure of multiinput-multioutput systems is discussed

A robustness synthesis method

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