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It is well known that actuator saturation can cause destabilization and degradation in performance; similar problems are encountered when actuation is quantized. This study proposes the design of an antiwindup compensator for systems with actuators that are limited to a finite number of quantization levels. This combination of discrete-level actuation and saturation poses a unique antiwindup problem that has not yet been solved. To surmount this combined issue, an antiwindup compensator is proposed, which provides ultimate boundedness of the system state within a prescribed region and guarantees that the state does not stray outside a larger compact set. The use of shifted ramp functions enables a less conservative bound on the control-signal error, which yields significantly lower L2 gain bounds compared to a standard sector-bound antiwindup design approach. A numerical simulation example illustrates the effectiveness on a rigid-body system, which inspired this study. 

Actuator constraints, particularly saturation limits, are an intrinsic and long‐standing problem in the implementation of most control systems. Model reference adaptive control (MRAC) is no exception and it may suffer considerably when actuator saturation is encountered. With this in mind, this paper proposes an anti‐windup strategy for model reference adaptive control schemes subject to actuator saturation. A prominent feature of the proposed compensator is that it has the same architecture as well‐known nonadaptive schemes, namely model recovery anti‐windup, which rely on the assumption that the system model is known accurately. Since, in the adaptive case, the model is largely unknown, the proposed approach uses an “estimate” of the system matrices for the anti‐windup formulation and modifies the adaptation laws that update the controller gains; if the (unknown) ideal control gains are reached, the model recovery anti‐windup formulation is recovered. The main results provide conditions under which, if theidealcontrol signal eventually lies within the control constraints, then the system states will converge to those of the reference model, that is, the tracking error will converge to zero asymptotically. The article deals with open‐loop stable linear systems and highlights the main challenges involved in the design of anti‐windup compensators for model‐reference adaptive control systems, demonstrating its success via a flight control application. 

This paper proposes a two stage anti-windup compensation scheme for systems subject to both input saturation and input quantization. The paper makes two main contributions: (i) it proposes a new partitioning of the saturation/quantization nonlinearity; and (ii) it formulates and solves a two-stage anti-windup problem on the basis of this partitioned nonlinearity. The anti-windup compensator contains two distinct elements: one to assuage the effects of quantization, the other to do the same when saturation occurs. Theoretical results provide conditions which must be satisfied in order for the two-stage anti-windup compensator to bestow stability on the resulting closed-loop system. These results are expressed as linear matrix inequalities and naturally lead to algorithms for anti-windup design. Simulation examples illustrate the effectiveness of the techniques. 

In this paper, an anti-windup compensation scheme is proposed for the manual mode of a rigid body attitude control system to make the angular velocity dynamics globally asymptotically stable despite actuator saturation. The addressed anti-windup design problem is challenging since the nominal control law includes a nonlinear dynamic inversion element to cancel the nonlinearity in the angular velocity dynamics. The stability of the compensated closed-loop system is proved via the Lyapunov stability criterion appropriately. Moreover, the superiority of the compensated system versus the uncompensated one is demonstrated by simulation. 

It is well known that actuator saturation can cause destabilization and degradation in performance; similar problems are faced when actuation is quantized. This paper proposes the design of an anti-windup compensator for systems with actuators that are limited to a finite number of quantization levels. This combination of discrete level actuation and saturation poses a unique anti-windup problem that has not yet been solved. To surmount this combined issue, an anti-windup compensator is proposed which provides ultimateboundedness of the system state within a prescribed region, and also guarantees that the state does not stray outside a larger compact set. A numerical simulation example illustrates the effectiveness on a rigid-body system which inspired this work. 

This paper proposes an anti-windup mechanism for a model reference adaptive control scheme subject to actuator saturation constraints. The proposed compensator has the same architecture as well known non-adaptive schemes, which rely on the assumption that the system model is known fairly accurately. This is in contrast to the adaptive nature of the controller, which assumes that the system (or parts of it) is unknown. The approach proposed here uses of an “estimate” of the system matrices for the anti-windup compensator formulation and modifies the adaptation laws that update the controller gains. It will be observed that if the (unknown) ideal control gain is reached, a type of “model recovery anti-windup” formulation is obtained. In addition, it is shown that if the ideal control signal eventually lies within the control constraints, then, under certain conditions, the system states will converge to those of the reference model as desired. The paper highlights the main challenges involved in the design of anti-windup compensators for model-reference adaptive control systems and demonstrates its success via a flight control simulation.