Decoupling in the design and synthesis of multivariable control systems.
Time invariant linear control system decoupling using state variable feedback, determining synthesis procedure to obtain desired closed loop configurations
Falb, P. L.↗
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Ground Simulator Studies of a Nonlinear Linkage in a Power Control System
An investigation was made to determine the characteristics of a nonlinear linkage installed in a power control system incorporated in a ground simulator. The nonlinear linkage provided for increased control-stick motion for relatively small simulator response at control motions near neutral. The quality of the control system was rated on the ease and precision with which various tracking tasks were performed by the pilots who operated the simulator. The results obtained with the nonlinear linkage installed in the control system were compared with those obtained by using the normal linear control system. Several combinations of nonlinearity of the linkage were tested for various dynamic characteristics of the simulator. It was found that the pilots were able to track almost as well with the nonlinear linkage installed as with the normal system. All of the pilots were of the opinion, however, that the nonlinearity was an undesirable feature in the control system because of the apparent lack of simulator response through the neutral range of the linkage where relatively large stick deflections could be made with very little simulator motion. The results showed that increased lag between the target and chair position, higher stick-force levels, and uneven stick forces due to the dynamics of the linkage were general characteristics of all the nonlinear linkage conditions tested. It was also found that for cases of low simulator damping, rapid control motions caused considerably higher overshoots when the nonlinear linkage was installed than were obtained for the normal linear control system. These characteristics were considered to be sufficiently undesirable to out-weigh the advantages to be gained from the use of a nonlinear linkage in the control system of an airplane.
Assadourian, Arthur↗
Modeling with Liapunov function
Liapunov functions for finding lower order models of linear control systems
LINEAR SYSTEM↗
Design of sensitivity-constrained optimal linear state-regulator control systems.
Optimal linear controller synthesis with minimized trajectory sensitivity achieved by using quadratic cost function
Higginbotham, R. E.↗
Linear stochastic optimal control and estimation problem
Problem involves design of controls for linear time-invariant system disturbed by white noise. Solution is Kalman filter coupled through set of optimal regulator gains to produce desired control signal. Key to solution is solving matrix Riccati differential equation. LSOCE effectively solves problem for wide range of practical applications. Program is written in FORTRAN IV for batch execution and has been implemented on IBM 360.
Geyser, L. C.↗
Frequency control circuit for all-digital phase-lock loops
Phase-lock loop references all its operations to fixed high-frequency service clock operating at highest speed which digital circuits permit. Wide-range control circuit provides linear control of frequency of reference signal. It requires only two counters in combination with control circuit consisting only of flip-flop and gate.
Anderson, T. O.↗
Linear stochastic optimal control and estimation
Digital program has been written to solve the LSOCE problem by using a time-domain formulation. LSOCE problem is defined as that of designing controls for linear time-invariant system which is disturbed by white noise in such a way as to minimize quadratic performance index.
Geyser, L. C.↗
Linear stochastic optimal control and estimation
Problem is defined as that of designing controls for linear time invariant system, which is disturbed by white noise, in such a way as to minimize quadratic performance index.
Geyser, L. C.↗
The effects of time delay in man-machine control systems: Implications for design of flight simulator Visual-Display-Delay compensation
When human operators are performing precision tracking tasks, their dynamic response can often be modeled by quasilinear describing functions. That fact permits analysis of the effects of delay in certain man machine control systems using linear control system analysis techniques. The analysis indicates that a reduction in system stability is the immediate effect of additional control system delay, and that system characteristics moderate or exaggerate the importance of the delay. A selection of data (simulator and flight test) consistent with the analysis is reviewed. Flight simulator visual-display delay compensation, designed to restore pilot aircraft system stability, was evaluated in several studies which are reviewed here. The studies range from single-axis, tracking-task experiments (with sufficient subjects and trials to establish the statistical significance of the results) to a brief evaluation of compensation of a computer generated imagery (CGI) visual display system in a full six degree of freedom simulation. The compensation was effective, improvements in pilot performance and workload or aircraft handling qualities rating (HQR) were observed. Results from recent aircraft handling qualities research literature, which support the compensation design approach, are also reviewed.
Crane, D. F.↗
An L1 Adaptive Control Augmentation for a Lift Plus-Cruise Vehicle
This paper presents anL1adaptive control augmentation for a Lift-Plus-Cruise (L+C)vehicle. This class of vehicles operates in three flight modes with different dynamic behavior: vertical, transition, and forward flight. A robust uniform controller is used as a baseline to stabilize the system throughout these flight modes. The uniform controller is a linear control law designed around trim conditions of the aircraft and includes control allocation to achieve the desired forces and moments on the vehicle. TheL1control augmentation is designed for each of these trim conditions to compensate for the nonlinear time- and state-dependent uncertainties in the vehicle dynamics. The augmented control output is then added to the desired force and moment commands on the vehicle. Simulation results demonstrate the effectiveness of control augmentation for reducing the effects of unmodeled dynamics, reduced actuator effectiveness, and time-dependent disturbances. Effectiveness is demonstrated through tracking error metrics.
Andrew Patterson↗
Finite-dimensional discrete-time control of linear distributed parameter systems
Systems described by partial differential equations have an infinite-dimensional state space. Feedback control of such distributed parameter systems must be accomplished by finite-dimensional controllers to be implemented by on-line digital computers. A further practical constraint is that the controller must operate in discrete (rather than continuous) time. This paper investigates the stability of such distributed parameter feedback controllers in closed-loop with the actual system.
Balas, M. J.↗
Modeling with Liapunov functions.
Behavior of high-order linear control systems analyzed using liapunov second method, by finding low-order model with closely approximate response behavior of high order linear control systems analyzed, using Liapunov second method, by finding low order model with closely approximate response
LIAPUNOV FUNCTION↗
Adaptive stochastic control for linear systems. I - Solution method
Linear discrete time stochastic system with unknown gain parameters, interpreting open loop feedback optimal control identifier and controller equations
Athans, M.↗
Robust stability and control of linear and multilinear interval systems
This paper is a survey of recent results obtained by the authors and their coworkers on the robust stability and control of systems containing parametric uncertainty. The starting point is a generalization of Kharitonov's theorem obtained by Chapellat and Bhattacharyya in 1989. This theorem, called the Linear CB theorem, its generalization to the multilinear case, the singling out of extremal stability subsets, and other ramifications now constitute an extensive and coherent theory of robust parametric stability that is summarized in the results contained here.
Bhattacharyya, S. P.↗
Nonlinear rescaling of control values simplifies fuzzy control
Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.
Vanlangingham, H.↗
Adaptive Control of Linear Modal Systems Using Residual Mode Filters and a Simple Disturbance Estimator
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.
Balas, Mark↗
Stable direct adaptive control of linear infinite-dimensional systems using a command generator tracker approach
The topics are presented in view graph form and include the following: an adaptive model following control; adaptive control of a distributed parameter system (DPS) with a finite-dimensional controller; a direct adaptive controller; a closed-loop adaptively controlled DPS; Lyapunov stability; the asymptotic stability of the closed loop; and model control of a simply supported beam.
Balas, Mark↗
Nonclassical Flight Control for Unhealthy Aircraft
This research set out to investigate flight control of aircraft which has sustained damage in regular flight control effectors, due to jammed control surfaces or complete loss of hydraulic power. It is recognized that in such an extremely difficult situation unconventional measures may need to be taken to regain control and stability of the aircraft. Propulsion controlled aircraft (PCA) concept, initiated at the NASA Dryden Flight Research Center. represents a ground-breaking effort in this direction. In this approach, the engine is used as the only flight control effector in the rare event of complete loss of normal flight control system. Studies and flight testing conducted at NASA Dryden have confirmed the feasibility of the PCA concept. During the course of this research (March 98, 1997 to November 30, 1997), a comparative study has been done using the full nonlinear model of an F-18 aircraft. Linear controllers and nonlinear controllers based on a nonlinear predictive control method have been designed for normal flight control system and propulsion controlled aircraft. For the healthy aircraft with normal flight control, the study shows that an appropriately designed linear controller can perform as well as a nonlinear controller. On the other hand. when the normal flight control is lost and the engine is the only available means of flight control, a nonlinear PCA controller can significantly increase the size of the recoverable region in which the stability of the unstable aircraft can be attained by using only thrust modulation. The findings and controller design methods have been summarized in an invited paper entitled.
Lu, Ping↗