Indirect Adaptive Robust Control Research Articles

Pneumatic Brake Control for Precision Stopping of Heavy-Duty Vehicles

Precision stopping is an important automated vehicle control function that is critical in applications such as precision bus docking, automated truck or bus fueling, as well as automatic intersection, or toll booth stopping. The initial applications of this technology are most likely to be applied to heavy-duty vehicles such as buses or trucks. Such applications require specific attention to brake control since the characteristics of a typical pneumatic brake system of a heavy vehicle is inherently nonlinear with large uncertainties. The feasibility of providing a smooth precision stopping brake control based on a conventional pneumatic brake system has not yet been demonstrated. This paper describes the precision stopping problem, verifies the pneumatic brake model, details the indirect adaptive robust control (IARC) design for a pneumatic brake system, and reports the successful implementation of a bus precision docking demonstration

Integrated Direct/Indirect Adaptive Robust Precision Control of Linear Motor Drive Systems with Accurate Parameter Estimations

The focus of the paper is on the synthesis of nonlinear adaptive robust controllers for precision linear motor drive systems that achieve not only excellent output tracking performance but also accurate parameter estimations for secondary purposes such as machine health monitoring and prognostics. Such an objective is accomplished through the intelligent integration of the output tracking performance oriented direct adaptive robust control (DARC) design with the accurate parameter estimation based indirect adaptive robust control (IARC) design. Comparative experimental results demonstrate that the proposed DIARC controller is able to achieve better tracking performance and better parameter estimation than either the DARC or the IARC algorithms.

INDIRECT ADAPTIVE ROBUST CONTROL OF SISO NONLINEAR SYSTEMS IN SEMI-STRICT FEEDBACK FORMS

In this paper, the modularized adaptive backstepping designs are incorporated into the recently proposed adaptive robust control framework to synthesize indirect adaptive robust controllers that achieve not only good output tracking performance but also better parameter estimation processes to obtain accurate parameter estimates for secondary purposes such as machine health monitoring and prognostics. Departing from the modularized adaptive backstepping designs, the proposed indirect adaptive robust control (IARC) uses available a priori knowledge on the physical bounds of unknown parameters, along with preset adaptation rate limits, to construct projection type parameter estimation algorithms with rate limits for a controlled estimation process. By doing so, regardless of the estimation algorithm to be used, a guaranteed transient performance and final tracking accuracy can be achieved even in the presence of disturbances and uncertain nonlinearities, a desirable feature in applications. In addition, the theoretical performance of the adaptive designs, asymptotic output tracking in the presence of parametric uncertainties only, is also preserved. The precision motion control of a linear motor drive system is used as an application example. Experimental results are obtained to show the improved parameter estimation process of the proposed IARC design.

Robust trajectory control in the workspace of a class of flexible robots

AbstractThis paper presents a robust indirect adaptive controller for a class of robots which have a flexible beam as last link. Since the relation between the joint space and the workspace depends on both the kinematics and the dynamics, a virtual joint space is defined so as to be related kinematically to the workspace. In fact, the transformation is defined from the virtual joint space to the joint and deformation spaces. Since the robot is a non‐minimum‐phase system in the virtual joint space, the transformation is obtained, in‐line by the iterative use of the causal–anticausal approach. Based on that transformation, a robust adaptive controller can be designed to ensure robust and fast convergence of the tracking error in the joint, deformation and virtual joint spaces. The controller thus obtained is simulated for a manipulator having one rigid and one flexible link. The simulation results demonstrate the good performances and the robustness of the system. © 2001 John Wiley & Sons, Inc.

Analysis of a new algorithm for continuous-time robust adaptive control

Analysis of a robust indirect adaptive control scheme is presented. It is shown that a new dead zone technique can be used so that the knowledge of the parameters of the upper bounding function on the unmodeled dynamics and the disturbance is not necessarily required; furthermore, the allowable unmodeled dynamics could be enlarged if the knowledge of the upper bound of the unmodeled dynamics is given.

Nonconservative adaptive robust control and structure selection for SISO plant under coprime factor perturbations

Abstract A robust indirect adaptive controller for SISO plant under coprime factor perturbations and bounded external disturbance is presented. The structure of the plant (orders and time delay) are assumed to be from a finite known family of possible structures. It is assumed also that a linear controller stabilizing the nominal part of the plant is given for known nominal parameters. Closed loop estimation of model structure, model parameters, and the nouns of perturbations and additive disturbance is based on overall criterion taken as the worst case steady-state absolute value of the output. It is proved that the adaptive controller achieves robust performance arbitrarily near to that in the case of completely known plant.

Adaptive Robust Control under Unknown Plant Orders

A robust indirect adaptive controller under additive and parametric disturbances is introduced in this paper. The orders and time delay of the plant are assumed to be unknown apart from their known upper bounds. It is also assumed that a robust linear controller of the plant can be defined for known parameters, model orders and time delay. The robust adaptive controller switches between model structures depending on an overall criterion of performance. It is not only proved that the adaptive control scheme is stable but that its asymptotic performance can be set arbitrarily near to the performance achievable for a known plant. Finally, a simulation illustrates the performance of the scheme.

Robust Adaptive Control Under Unknown Plant Orders

A robust indirect adaptive controller under additive and parametric disturbances is introduced in this paper. The orders and time delay of the plant are assumed to be unknown apart from their known upper bounds. It is also assumed that a robust linear controller of the plant can be defined for known parameters, model orders and time delay. The robust adaptive controller switches between model structures depending on an overall criterion of performance. It is not only proved that the adaptive control scheme is stable but that its asymptotic performance can be set arbitrarily near to the performance achievable for known plant. Finally, a simulation illustrates the performance of the scheme.

Continuous-time indirect adaptive control of the electrohydraulic servo systems

A continuous-time robust indirect adaptive control (IAC) algorithm with a self-excitation capability is proposed for position control of an electrohydraulic servo system subject to parametric uncertainties and load disturbances. In this algorithm, a gradient least squares dead zone estimation is used to identify the plant parameters and then a linear pole-placement controller is designed using the estimate. By a coprimeness verification procedure, the proposed algorithm facilitates the establishment of the adaptive pole-placement control of the closed-loop system by using an additional nonlinear feedback signal implemented for supplying the system with sufficiently rich signals. An analysis shows this algorithm can guarantee parameter estimation convergence and system stability based on the certainty equivalence principle. The performance of the proposed algorithm is evaluated through both the simulation results and the experimental studies. Simulations and experiments are conducted to see how well the proposed algorithm compares with two existing control schemes in controlling the same process. The results show that the IAC scheme confirms the analysis and has considerable robustness subject to parametric uncertainties and load disturbances and has better performance than the other two controllers.

Robust indirect adaptive control of the electrohydraulic velocity control systems

A robust version of an indirect adaptive control scheme with self-excitation capability to the problem of controlling velocity of the electrohydraulic servosystems subject to unmodelled dynamics and load disturbances is proposed. The scheme contains an effective gradient least squares estimator using a dead zone technique and a certainty equivalence based adaptive controller. A design procedure for synthesising the adaptive controller is formulated by using the pole-placement technique, where a signal is created and fed back to the control law such that it has self-excitation capability and thus the stability of the closed-loop control system can be achieved. A series of simulations are performed to demonstrate the effectiveness of the proposed scheme. The results show that the proposed scheme is fairly robust to the control systems with uncertainties as well as improved performance characteristics, compared with that of the suboptimal PID control scheme with constant feedback gain and that of the adaptive model following control scheme.

Robust Indirect Adaptive Control of Time-Varying Plants with Unmodeled Dynamics and Disturbances

It is shown that indirect pole-zero placement adaptive controllers are robust for systems with time-varying parameters as well as unmodeled dynamics and disturbances. A parameter estimator with projection is used. No special signal normalization is employed to ensure robustness. The nominal system parameters need only be bounded, and their variations need only be small in an average sense. This allows them to vary slowly with time, as well as to take large jumps occasionally. The adaptive controllers can also simultaneously tolerate small unmodeled dynamics, as well as bounded disturbances, with no restriction on the magnitude of the bound.

Corrigendum: Discrete Time Stochastic Adaptive Control

Previous article Full AccessCorrigendum: Discrete Time Stochastic Adaptive ControlGraham C. Goodwin, Peter J. Ramadge, and Peter E. CainesGraham C. Goodwin, Peter J. Ramadge, and Peter E. Caineshttps://doi.org/10.1137/0320063PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout"Corrigendum: Discrete Time Stochastic Adaptive Control." SIAM Journal on Control and Optimization, 20(6), p. 893 Previous article FiguresRelatedReferencesCited byDetails Robust Indirect Adaptive Control for a Class of Nonlinear Systems and Its Application to Shape Memory Alloy ActuatorsIEEE Access, Vol. 6 Cross Ref Asymptotic Behavior of Stochastic Systems Possessing Markovian RealizationsS. P. Meyn and P. E. Caines14 July 2006 | SIAM Journal on Control and Optimization, Vol. 29, No. 3AbstractPDF (2634 KB)Ergodic Theorems for Discrete Time Stochastic Systems Using a Stochastic Lyapunov FunctionSean P. Meyn14 July 2006 | SIAM Journal on Control and Optimization, Vol. 27, No. 6AbstractPDF (2969 KB)The Structural Robustness of Stochastic SystemsIFAC Proceedings Volumes, Vol. 21, No. 9 Cross Ref On the adaptive control of a class of systems with random parameters and disturbancesAutomatica, Vol. 21, No. 6 Cross Ref The self-tuning of stochastic adaptive pole placement controllers Cross Ref Volume 20, Issue 6| 1982SIAM Journal on Control and Optimization History Published online:17 February 2012 InformationCopyright © 1982 Society for Industrial and Applied MathematicsPDF Download Article & Publication DataArticle DOI:10.1137/0320063Article page range:pp. 893-893ISSN (print):0363-0129ISSN (online):1095-7138Publisher:Society for Industrial and Applied Mathematics