Model Recovery Anti-windup Research Articles

Systematic mitigation of gain scheduling induced windup phenomena

Abstract In this paper, we discuss the systematic design of gain scheduling controllers for nonlinear systems. We discuss control signal blending induced windup phenomena and employ an extended Model-Recovery Anti-Windup (MRAW) scheme to mitigate them. Combining control signal blending with MRAW allows to build gain scheduling controllers without imposing the common slow variation assumption regarding the scheduling vectors. In addition, the approach offers a higher flexibility in the choice of the sub-controllers compared to classical approaches and convex optimization allows for a very efficient design of the anti-windup networks.

Antiwindup Control of an Electrohydraulic System With Load Disturbance and Modeling Uncertainty

In this study, a linear antiwindup controller of an electrohydraulic system (EHS) is proposed to drive the joint motion of a two-degree-of-freedom robotic arm. Since the unknown external load disturbance is caused by the driven force/torque of the robotic arm and some hydraulic parametric uncertainties existing in an EHS model, perhaps the control saturation emerges in the controller, which will degrade the dynamic performance and the stable margin of the EHS. Thus, a model recovery antiwindup compensator embedded in an unconstrained controller is designed to suppress the control saturation of a servo valve. The antiwindup effectiveness of the proposed controller has been demonstrated by a comparative experiment study with both linear and nonlinear controllers, which indicates the proposed controller can achieve better dynamic performance under largely unknown load disturbance and model uncertainty.

A switched and scheduled design for model recovery anti-windup of linear plants

We provide two nonlinear solutions to the model recovery anti-windup (MRAW) design problem, both of them relying on the definition of a set of nested ellipsoids in the state space of the anti-windup dynamics. Each ellipsoidal set arises from a convenient trade-off between size of the ellipsoid and guaranteed exponential convergence rate induced by the corresponding saturated feedback. The first solution is given by a hybrid selection of the MRAW stabilizer, relying on a natural hysteresis switching mechanism. The second solution corresponds to a Lipschitz but non-differentiable scheduled selection, which essentially smoothens out the discontinuous nature of the nested ellipsoids. We discuss the role of our design architecture and establish a number of important properties induced by the proposed controllers. Their effectiveness is comparatively illustrated on a few example studies.

Adaptive Model Recovery Anti-Windup for Output-Feedback Plants

The control of real technical systems always involves consideration of maximal input amplitudes. Moreover, the properties of technical systems often change during their lifetime, due to e.g. aging or small defects. In order to satisfy high performance requirements for the whole duration of such systems, the use of adaptive control is beneficial. Since for many industrial control application, e.g. in automotive industry, only the output of systems is measurable, an output-feedback adaptive controller is necessary, which is able to deal with input saturation. A new adaptive method based on model recovery anti-windup (MRAW) for continuous time systems is presented in this work. It allows for performance considerations in the case of input saturation. Results of boundedness for the closed-loop system are shown and verified with a simulation example. The simulation example shows the benefits of the adaptive control scheme with anti-windup in comparison to a robust approach in the presence of parameter uncertainties.

An LMI Approach to Model Recovery Anti-Windup Scheme with PID Controller

An LMI Approach to Model Recovery Anti-Windup Scheme with PID Controller

Model recovery anti-windup for continuous-time rate and magnitude saturated linear plants

In this paper two approaches are given for anti-windup design for nonlinear control systems with linear plants subject to limitations both in the magnitude and the rate of variation of the control input. Both approaches are based on the so-called Model Recovery Anti-Windup (MRAW) framework. The first approach is built by treating the rate + magnitude saturation as a single dynamic nonlinearity, while in the second one, the dynamic compensator dynamics is extended with extra states to treat the two saturations separately. Both approaches lead to global stability with exponentially stable plants and local stability in all other cases. For both approaches, stability and performance guarantees are proven, numerical recipes are given and the relative merits are comparatively highlighted on a simulation example.

Extended Model Recovery Anti-windup for Satellite Control

AbstractSatellite control is facing up new requirements in terms of high precision. Actuators satisfying these demands appear to be sensitive to the saturation. This can induce negative effects (i.e. oscillations, instability). To modify this situation an anti-windup strategy can be applied. The idea consists in introducing control modifications to keep the response close to the linear one. Two main architectures are used. The first one is based on a computation of a saturating feedback law. The second one is based on selecting an anti-windup incorporating a model of the plant. This work combines both approaches to compute a dynamic anti-windup. Simulations compare this anti-windup with other existing architectures.

A Tutorial on Modern Anti-windup Design

In this paper, several constructive linear and nonlinear anti-windup techniques are presented and explained. Two approaches, namely direct linear anti-windup (DLAW) and model recovery anti-windup (MRAW), are described in an algorithmic way, in order to illustrate their main features. Hereafter, theoretical conditions ensuring stability and performance, their applicability, their accompanying guarantees, and their merits and deficiencies are given. The possible extensions to less standard problem settings are also briefly discussed.