Adaptive control of time delay systems and applications to automotive control problems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.Includes bibliographical references (p. 107-114).This thesis is about the adaptive control of time delay systems with applications to automotive control problems. The stabilization of systems involving time delays is a difficult problem since the existence of a delay may induce instability or poor performance for the closed loop system. A unique approach for controlling systems with known time delay was originated by Otto Smith in the 1950s by compensating for the delayed output using input values stored over a time window of [t - [tau], t] and estimating the plant output using a model of the plant. Later, this idea was extended to include unstable plants as well, using finite-time integrals of the delayed input values thereby avoiding unstable pole-zero cancellations that may occur in Smith's controller. Adaptive versions of these delay compensating controllers were also developed with rather complicated adaptive rules which might not be practical to use in real applications. In this thesis, a simpler adaptive version of delay compensating controllers is developed, which has adaptive rules that are easily implementable and thus suitable for real life implementations. The developed controller is tested in two important automotive control problems that are idle speed control (ISC) and fuel-to-air ratio (FAR) control. These two applications, ISC and FAR control, constitute the experimental part of this research. In ISC, the objective is to regulate the engine speed to a prescribed set-point in the presence of accessory load torque disturbances such as due to air conditioning and power steering. The adaptive controller, integrated with the existing proportional spark controller, is used to drive the electronic throttle actuator. Both simulation and experimental results demonstrating the performance improvement by employing the adaptive controller are presented. Modifications and improvements to the controller structure, which were developed during the course of experimentation to solve specific problems, are also presented. In addition, the potential for the reduction in calibration time and effort which can be achieved with our approach is discussed.(cont.) The objective in FAR control is to maintain the in-cylinder FAR at a prescribed set point, determined primarily by the state of the Three-Way Catalyst (TWC), so that the pollutants in the exhaust are removed with the highest efficiency. The FAR controller must also reject disturbances due to canister vapor purge and inaccuracies in air charge estimation and wall-wetting (WW) compensation. Two adaptive controller designs are considered. The first design is based on feedforward adaptation while the second design is based on both feedback and feedforward adaptation. Both simulation and experimental results demonstrating the performance improvement by employing the APC are presented. In addition, modifications and improvements to the APC structure, which were developed during the course of the experiments, to solve specific implementation problems are presented.by Yildiray Yildiz.Ph.D

Stabiity for Systems with Unknown Time Delays

Time delays are of long-standing interest in the study of control systems since they appear in many practical control problems and tend to degrade overall system performance. In this thesis, we consider two distinct problems involving uncertain time delays. The first problem that we consider is the achievable delay margin problem, which is determining the longest delay for which stability can be maintained when using a linear time invariant (LTI) controller. This problem has been considered in continuous-time, where bounds (often tight) have been found for plants with non-zero right half plane poles. In this work, we consider the discrete-time case, where we prove that an LTI controller exists which stabilizes the plant and the plant with a one step delay if and only if the plant has no negative, real unstable poles. The second problem that we consider is stabilizing any continuous-time single-input single-output LTI plant with an arbitrarily large time delay and gain. To solve this problem, we propose a simple generalized hold whose resulting discretized system is amenable to adaptive control. Furthermore, by exploiting the structure of the resulting discretized system, we propose purpose built estimators for the unknown gain and delay, which allows us to not only provide bounded-input bounded-output (BIBO) closed-loop stability, but also guarantees the exponential decay of any plant initial conditions, robustness to un-modelled dynamics, and tolerance to occasional, possibly persistent, jumps in the gain and delay. Furthermore, for the case of a first order plant, a similar, but suitably modified controller is shown to tolerate continuous variation of the unknown delay while still providing BIBO closed-loop stability

Adaptive Output Feedback Apparatuses And Methods Capable Of Controlling A Non-minimum Phase System

The invention comprises apparatuses and methods for providing the capability to stabilize and control a non-minimum phase, nonlinear plant with unmodeled dynamics and/or parametric uncertainty through the use of adaptive output feedback. A disclosed apparatus can comprise a reference model unit for generating a reference model output signal ym. The apparatus can comprise a combining unit that combines and differences a plant output signal y of a non-minimum phase plant for which not all of the states can be sensed, and a plant output signal y, to generate an output error signal ỹ. The apparatus can further comprise an adaptive control unit for generating an adaptive control signal uad used to control the plant.Georgia Tech Research Corporatio

Feedback linearization control for a distributed solar collector field

This article describes the application of a feedback linearization technique for control of a distributed solar collector field using the energy from solar radiation to heat a fluid. The control target is to track an outlet temperature reference by manipulating the fluid flow rate through the solar field, while attenuating the effect of disturbances (mainly radiation and inlet temperature). The proposed control scheme is very easy to implement, as it uses a numerical approximation of the transport delay and a modification of the classical control scheme to improve startup in such a way that results compared with other control structures under similar conditions are improved while preserving short commissioning times. Experiments in the real plant are also described, demonstrating how operation can be started up efficiently.Ministerio de Ciencia y Tecnología DPI2004-07444-C04-04Ministerio de Ciencia y Tecnología DPI2005-0286

Prediction for control

5th IFAC Conference on System Structure and Control 1998 (SSC'98), Nantes, France, 8-10 JulyThis paper shows that "optimal" controllers based on "optimal" predictor structures are not "optimal" in their closed loop behaviour and that predictors should be designed taking into account closed-loop considerations. This is first illustrated with a first order plant with delay. The ISE index is computed for two typical optimal controllers (minimum variance controller and generalized predictive controller) when a stochastic disturbance is considered. The results are compared to those obtained by the use of a non optimal PI controller that uses a non optimal Smith predictor and performs better than the optimal controllers for the illustrative example. A general structure for predictors is proposed. In order to illustrate the results, some simulation examples are shown.Ce papier montre que des lois de commandes "optimales" basees sur des structures predictives "optimales" ne sont pas "optimales" dans leur comportement en boucle fermee et que la synthese de predicteurs devrait prendre en compte des considerations de boucle fermee. Cela est d'abord illustre avec un systeme du premier ordre a retard. l'index ISE est calcule pour deux lois de commandes optimales typiques (loi de commande a variance minim ale et loi de commande predictive generalisee), quand une perturbation stochastique est consideree. Les resultats sont compares a. ceux obtenus avec un regulateur PI non optimal base sur un predicteur de Smith non optimal et sont, pour l'exemple illustratif, meilleurs que ceux obtenus avec un regulateur optimal. Vne structure generale de predicteur est proposee. Pour illustrer les resultats, des exemples de simulations sont montres

A Robust Adaptive Dead-Time Compensator with Application to A Solar Collector Field

This paper describes an easy-to-use PI controller with dead-time compensation that presents robust behaviour and can be applied to plants with variable dead-time. The formulation is based on an adaptive Smith predictor structure plus the addition of a filter acting on the error between the output and its prediction in order to improve robustness. The implementation of the control law is straightforward, and the filter needs no adjustment, since it is directly related to the plant dead-time. An application to an experimentally validated nonlinear model of a solar plant shows that this controller can improve the performance of classical PID controllers without the need of complex calculations.Ministerio de Ciencia y Tecnología TAP95-37

Feedback control by online learning an inverse model

A model, predictor, or error estimator is often used by a feedback controller to control a plant. Creating such a model is difficult when the plant exhibits nonlinear behavior. In this paper, a novel online learning control framework is proposed that does not require explicit knowledge about the plant. This framework uses two learning modules, one for creating an inverse model, and the other for actually controlling the plant. Except for their inputs, they are identical. The inverse model learns by the exploration performed by the not yet fully trained controller, while the actual controller is based on the currently learned model. The proposed framework allows fast online learning of an accurate controller. The controller can be applied on a broad range of tasks with different dynamic characteristics. We validate this claim by applying our control framework on several control tasks: 1) the heating tank problem (slow nonlinear dynamics); 2) flight pitch control (slow linear dynamics); and 3) the balancing problem of a double inverted pendulum (fast linear and nonlinear dynamics). The results of these experiments show that fast learning and accurate control can be achieved. Furthermore, a comparison is made with some classical control approaches, and observations concerning convergence and stability are made