Ioan Doré Landau

A method for the auto-calibration of PID controllers

Abstract A method for the auto-calibration of PI and PID controllers, using a frequency domain model of the plant to be controlled (obtained by relay excitation), is presented. The tuning rules are inspired from the symmetrical optimum principles, introduced by Kessler [ Regelungstetechnik , 6, 395–400 and 432–436 (1958)]. They have the advantage to take into account both robustness aspects (phase margin, gain margin, sensitivity, neglected dynamics) and desired closed-loop characteristics and to cover a large domain of current, real applications. The proposed method is compared with the Ziegler-Nichols method (theoretically and experimentally). Simulations and results from industrial experiments are given.

Paper: Unification of discrete time explicit model reference adaptive control designs

Various discrete time explicit MRAC designs based on stability considerations are presented from a unified point of view. A general structure and a design procedure are given, which contain as particular cases various possible designs. Some of these designs have been already given in the literature but some are new. The general structure considered removes some of the restrictions encountered in previous designs and solves the important problem of independent specification of tracking and regulation objectives. The proof of boundedness of the control variables is also given. Simulations are included in order to evaluate the various designs in a deterministic environment.

Adaptive narrow band disturbance rejection applied to an active suspension-an internal model principle approach

This paper presents a methodology for feedback adaptive control of active vibration systems in the presence of time varying unknown narrow band disturbances. A direct adaptive control scheme based on the internal model principle and the use of the Youla-Kucera parametrization is proposed. This approach is comparatively evaluated with respect to an indirect adaptive control scheme based on the estimation of the disturbance model. The comparative evaluation is done in real time on an active suspension system.

Robustness of discrete-time direct adaptive controllers

The problem of preserving stability of discrete-time adaptive controllers in spite of reduced-order modeling and output disturbances is addressed in this paper. Conditions for global stability (convergence of the tracking error with bounded signals) are derived for a discrete-time pole-zero placement adaptive controller where the parameter estimator is modified in terms of normalized signals. Following an input-output perpective, the overall system is decomposed into two subsystems reflecting the parameter estimation and modeling errors, respectively, and its stability is studied using the sector stability and passivity theorems. First the analysis is carried for the class of disturbances and reference inputs that are either decaying or can be exactly hulled by a linear controller of the chosen structure. In this L 2 -framework, it is shown that the only substantive assumption to assure stability is the existence of a linear controller such that the closed-loop transfer function verifies certain conicity conditions. The convergence speed and alertness properties of various parameter adaptation algorithms regarding this condition are discussed. The results are further extended to a broader class of L_{\infty} disturbances and reference inputs.

Recursive algorithms for identification in closed loop: a unified approach and evaluation

A unified presentation of recursive algorithms for plant model identification in closed loop is given. From the basic formulation of the problem of finding the plant model that gives the best predictor for the closed-loop system, two families of algorithms using either a reparameterized predictor for the closed loop or a plant predictor operating on filtered data are presented, and their asymptotic properties are examined. Validation tests for the models identified in closed loop are proposed. A comparative evaluation of the various algorithms in simulation and on real-time experiments concludes the paper.

Paper: Reduced order bilinear models for distillation columns

The distillation columns are considered as compartmental systems. Because the inputs act linearly upon the transports matter flows, it is possible to include this type of system in the class of bilinear systems. By considering as output the distillate concentration of one of the products contained in the distilled mixture, the distillation column can be assimilated to a compartmental system with three compartments each of them replacing a set of distillation plates. These considerations finally permit a characterization of a distillation column by a minimal bilinear model having only three state variables and eight structural parameters. An identification algorithm permitting the identification of such a reduced order bilinear model is presented and is based on the minimization of the output error. Simulation results obtained by using as reference a complete non-linear model of a distillation column are presented. These results illustrate the validity of the approach proposed as well as the performance of the identification method. The reduced order bilinear model obtained is robust and valid for large variations of the inputs and of the working points. The use of the resulting bilinear model for control purposes is discussed.

Robust adaptive control of a flexible transmission system using multiple models

An application of the multiple models adaptive control based on switching and tuning to a flexible transmission system is presented. This approach has been considered in order to assure high control performance in the presence of large load variation on the system. The advantages of the multiple models adaptive control system with respect to the classical adaptive control is illustrated via experimental results. It is also shown that the robustness of the adaptive control system can be improved with the appropriate shaping of a sensitivity function. The use of a parameter estimation algorithm based on the minimization of the closed-loop output error in the multiple models scheme also improves the performance of the system in the tuning phase and makes the adaptation algorithm insensitive to unmodeled output disturbances.

An output error recursive algorithm for unbiased identification in closed loop

The problem of unbiased recursive identification of a plant model in closed-loop operation is considered. A particular form of an output error predictor for the closed loop is introduced. This allows one to derive a parameter estimation algorithm for the plant model that is globally asymptotically stable and asymptotically unbiased in the presence of noise. The paper presents a stability analysis in a deterministic environment and a convergence analysis in the stochastic environment. Both require a mild sufficient passivity condition to be satisfied. Simulations and real-time experiments on a flexible transmission illustrate the performances of the proposed algorithm.

Passivity and global stabilization of cascaded nonlinear systems

An alternative stability analysis is presented for recent results on global stabilization of a nonlinear system in cascade with a linear system. The analysis is carried out using passivity arguments. The relationship between passivity and an important class of Lyapunov function is also presented. >

Synthesis of adaptive controllers for robot manipulators using a passive feedback systems approach

Utilizing the fact that a manipulator composed of rigid links is a passive system, an approach based on the properties of interconnected passive systems is proposed for the analysis and synthesis of fixed and adaptive controllers for robot manipulators. This approach clarifies the rationale behind the various fixed and adaptive control laws synthesized using Lyapunov functions.<<ETX>>