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At least 91 records · Page 5

Generalized proportional-plus-derivative compensators for a class of uncertain plants

Controller design for a class of systems consisting of a positive-real transfer function P(s) followed by an integrator is considered. A generalized proportional-plus-derivative compensator is proposed for robustly stabilizing a class of uncertain plants represented by a positive-real transfer function followed by an integrator. The novel feature of the proposed compensator is that the proportional and rate gains used are transfer functions rather than constants, which allows more design freedom and offers the potential for better performance with guaranteed robust stability. The results obtained are for single-input/single-output systems. If the results are extended to the multivariable case, they will then be applicable to realistic flexible spacecraft.

Joshi, Suresh M.↗

Multivariable control of the Space Shuttle Remote Manipulator System

Linear controllers are designed to regulate the end effector of the Space Shuttle Remote Manipulator System (SRMS) operating in position hold mode. Design techniques used include H2 and H-infinity optimization. The nonlinear SRMS is linearized by modeling the effects of the significant nonlinearities as uncertain parameters. Each regulator design is evaluated for robust stability using both the small gain theorem with an H-infinity norm and the less conservative mu-analysis test. Regulator designs offer significant improvement over the current system for the nominal plant. Unfortunately, the SRMS model suffers from lightly damped poles with real parametric uncertainty. Under such conditions, the mu-analysis test, which allows for complex perturbations, cannot guarantee robust stability.

Adams, Neil J.↗

Dissipative compensators for flexible spacecraft control

The problem of controller design for flexible spacecraft is addressed. Model-based compensators, which rely on the knowledge of the system parameters to tune the state estimator, are considered. The instability mechanisms resulting from high sensitivity to parameter uncertainties are investigated. Dissipative controllers, which use collocated actuators and sensors, are also considered, and the robustness properties of constant-gain dissipative controllers in the presence of unmodeled elastic-mode dynamics, sensor/actuator nonlinearities, and actuator dynamics are summarized. In order to improve the performance without sacrificing robustness, a class of dissipative dynamic compensators is proposed and is shown to retain robust stability in the presence of second-order actuator dynamics if acceleration feedback is employed. A class of dissipative dynamic controllers is proposed which consists of a low-authority, constant-gain controller and a high-authority dynamic compensator. A procedure for designing an optimal dissipative dynamic compensator is given which minimizes a quadratic performance criterion. Such compensators offer the promise of better performance while still retaining robust stability.

Joshi, S. M.↗

Analysis of airframe/engine interactions in integrated flight and propulsion control

An analysis framework for the assessment of dynamic cross-coupling between airframe and engine systems from the perspective of integrated flight/propulsion control is presented. This analysis involves to determining the significance of the interactions with respect to deterioration in stability robustness and performance, as well as critical frequency ranges where problems may occur due to these interactions. The analysis illustrated here investigates both the airframe's effects on the engine control loops and the engine's effects on the airframe control loops in two case studies. The second case study involves a multi-input/multi-output analysis of the airframe. Sensitivity studies are performed on critical interactions to examine the degradations in the system's stability robustness and performance. Magnitudes of the interactions required to cause instabilities, as well as the frequencies at which the instabilities occur are recorded. Finally, the analysis framework is expanded to include control laws which contain cross-feeds between the airframe and engine systems.

Schierman, John D.↗

Small Body GN&C Research Report: A Robust Model Predictive Control Algorithm with Guaranteed Resolvability

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.

model predictive control algorithm (MPC)↗

A robust model predictive control algorithm for uncertain nonlinear systems that guarantees resolvability

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.

feed - forward↗

A new approach to mixed H2/H infinity controller synthesis using gradient-based parameter optimization methods

In the past few years, the mixed H(sub 2)/H-infinity control problem has been the object of much research interest since it allows the incorporation of robust stability into the LQG framework. The general mixed H(sub 2)/H-infinity design problem has yet to be solved analytically. Numerous schemes have considered upper bounds for the H(sub 2)-performance criterion and/or imposed restrictive constraints on the class of systems under investigation. Furthermore, many modern control applications rely on dynamic models obtained from finite-element analysis and thus involve high-order plant models. Hence the capability to design low-order (fixed-order) controllers is of great importance. In this research a new design method was developed that optimizes the exact H(sub 2)-norm of a certain subsystem subject to robust stability in terms of H-infinity constraints and a minimal number of system assumptions. The derived algorithm is based on a differentiable scalar time-domain penalty function to represent the H-infinity constraints in the overall optimization. The scheme is capable of handling multiple plant conditions and hence multiple performance criteria and H-infinity constraints and incorporates additional constraints such as fixed-order and/or fixed structure controllers. The defined penalty function is applicable to any constraint that is expressible in form of a real symmetric matrix-inequity.

Ly, Uy-Loi↗

Stability and robustness of slowly time-varying linear systems

A well-known result for finite-dimensional time-varying linear systems is that if each `frozen time' is stable, then the time-varying system is stable for sufficiently slow time-variations. These results are reviewed and extended to a class of Volterra integrodifferential equations, specifically, differential equations with a convolution operator in the right-hand-side. The results are interpreted in the context of robustness of time-varying linear systems with special emphasis on analysis of gain-scheduled control systems.

Shamma, Jeff S.↗

Robust controls with structured perturbations

This final report summarizes the recent results obtained by the principal investigator and his coworkers on the robust stability and control of systems containing parametric uncertainty. The starting point is a generalization of Kharitonov's theorem obtained in 1989, and its generalization to the multilinear case, the singling out of extremal stability subsets, and other ramifications now constitutes an extensive and coherent theory of robust parametric stability that is summarized in the results contained here.

Keel, Leehyun↗

Analysis and design of gain scheduled control systems

Gain scheduling, as an idea, is to construct a global feedback control system for a time varying and/or nonlinear plant from a collection of local time invariant designs. However in the absence of a sound analysis, these designs come with no guarantees on the robustness, performance, or even nominal stability of the overall gain schedule design. Such an analysis is presented for three types of gain scheduling situations: (1) a linear parameter varying plant scheduling on its exogenous parameters, (2) a nonlinear plant scheduling on a prescribed reference trajectory, and (3) a nonlinear plant scheduling on the current plant output. Conditions are given which guarantee that the stability, robustness, and performance properties of the fixed operating point designs carry over to the global gain scheduled designs, such as the scheduling variable should vary slowly and capture the plants nonlinearities. Finally, an alternate design framework is proposed which removes the slowing varying restriction or gain scheduled systems. This framework addresses some fundamental feedback issues previously ignored in standard gain.

Shamma, Jeff S.↗

Fast computation of the multivariable stability margin for real interrelated uncertain parameters

A novel algorithm for computing the multivariable stability margin for checking the robust stability of feedback systems with real parametric uncertainty is proposed. This method eliminates the need for the frequency search involved in another given algorithm by reducing it to checking a finite number of conditions. These conditions have a special structure, which allows a significant improvement on the speed of computations.

Sideris, Athanasios↗

Analysis of gain scheduled control for nonlinear plants

Gain scheduling has proven to be a successful design methodology in many engineering applications. In the absence of a sound theoretical analysis, these designs come with no guarantees of the robustness, performance, or even nominal stability of the overall gain-scheduled design. An analysis is presented for two types of nonlinear gain-scheduled control systems: (1) scheduling on a reference trajectory and (2) scheduling on the plant output. Conditions which guarantee stability, robustness, and performance properties of the global gain schedule designs are given. These conditions confirm and formalize popular notions regarding gain-scheduled designs, such as that the scheduling variable should vary slowly and capture the plant's nonlinearities.

Shamma, Jeff S.↗

Guaranteed properties of gain scheduled control for linear parameter-varying plants

Gain scheduling has proven to be a successful design methodology in many engineering applications. However, in the absence of a sound theoretical analysis, these designs come with no guarantees on the robustness, performance, or even nominal stability of the overall gain scheduled design. This paper presents such an analysis for one type of gain scheduled system, namely, a linear parameter-varying plant scheduling on its exogenous parameters. Conditions are given which guarantee that the stability, robustness, and performance properties of the fixed operating point designs carry over to the global gain scheduled design. These conditions confirm and formalize popular notions regarding gain scheduled design, such as the scheduling variable should 'vary slowly'.

Shamma, Jeff S.↗

Analysis of airframe/engine interactions for a STOVL aircraft with integrated flight/propulsion control

A multivariable analysis technique is used to evaluate the effects of the dynamic cross coupling between the airframe and engine subsystems in an advanced STOVL configuration. A critical frequency range is identified along with potentially poor stability robustness due to the airframe/engine interactions. Within the critical frequency range, stability and performance are found to be sensitive to variations in the coupling between the airframe's flight path angle and the engine's fuel flow rate. A stability sensitivity study indicates that the interactions between the flight path angle and the fuel flow rate are potentially the most critical with respect to stability and performance robustness.

Schierman, John D.↗

Stability margins for Hurwitz polynomials

The authors treat the robust stability issue using the characteristic polynomial, for two different cases: first in coefficient space with respect to perturbations in the coefficient of the characteristic polynomial; and then for a control system containing perturbed parameters in the transfer function description of the plant. In coefficient space, a simple expression is first given for the l-(squared) stability margin for both the monic and nonmonic cases. Following this, a method is given to find the l(infinity) margin, and the method is extended to reveal much larger stability regions. In parameter space the authors consider all single-input (multi-output) or single-output (multi-input) systems with a fixed controller and a plant described by a set of transfer functions which are ratios of polynomials with variable coefficients. A procedure is presented to calculate the radius of the largest stability ball in the space of these variable parameters. The calculation serves as a stability margin for the control system. The formulas that result are quasi-closed-form expressions for the stability margin and are computationally efficient.

Chapellat, Herve↗

Robust H(infinity) control design for the Space Station with structured parameter uncertainty

A robust H(infinity) control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multiparameter variations in the state-space formulation of H(infinity) control theory. An application of this robust control synthesis technique tothe Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this new robust H(infinity) controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.

Byun, Kuk-Whan↗

Stochastic stability and performance robustness of linear multivariable systems

Stochastic robustness, a simple technique used to estimate the robustness of linear, time-invariant systems, is applied to a single-link robot arm control system. Concepts behind stochastic stability robustness are extended to systems with estimators and to stochastic performance robustness. Stochastic performance robustness measures based on classical design specifications are introduced, and the relationship between stochastic robustness measures and control system design parameters is discussed. The application of stochastic performance robustness and the relationship between performance objectives and design parameters are demonstrated by means of the example. The results prove stochastic robustness to be a good overall robustness analysis method that can relate robustness characteristics to control system design parameters.

Stengel, Robert F.↗