Conference Paper

Checking if controllers are stabilizing using closed-loop data

Res. Sch. of Inf. Sci. & Eng., Australian Nat. Univ., Canberra, ACT
DOI: 10.1109/CDC.2006.377549 Conference: Decision and Control, 2006 45th IEEE Conference on
Source: IEEE Xplore

ABSTRACT Suppose an unknown plant is stabilized by a known controller. Suppose also that some knowledge of the closed-loop system is available and on the basis of that knowledge, the use of a new controller appears attractive, as may arise in iterative control and identification algorithms, and multiple-model adaptive control. The paper presents tests using a limited amount of experimental data obtained with the existing known controller for verifying that introduction of the new controller will stabilize the plant

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper suggests a model-free control design technique for unknown stable single-input-single-output (SISO) systems. In traditional control design approaches, a mathematical model of the plant is first identified using a set of measurements, then a controller is designed on the basis of this model. However, the use of such identified models, which are often subject to several uncertainties due to the complexity involved in many practical applications, usually results in degradation of the controller performance. Unlike model-based control approaches, we propose here to directly utilize the measured data in the controller design without going through a model identification. Our proposed control method consists in finding a suitable fixed-order controller for which the closed-loop frequency response is very close to a desired frequency response that describes some desired closed-loop performance indices. This problem is formulated as a minimization problem, where the objective function is defined by the integral of the squared relative error between the closed-loop frequency response and the desired frequency response. The main feature of our proposed method is that the design process does not depend on the increasing order and complexity of the system. Moreover, it enables to design low-order controllers. For simulation purposes, a PID controller is designed to illustrate the feasibility and demonstrate the efficacy of the proposed technique.
    2013 IEEE 52nd Annual Conference on Decision and Control (CDC); 12/2013
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a new model-free technique to design fixed-structure controllers for linear unknown systems. In the current control design approaches, measured data are used to first identify a model of the plant, then a controller is designed based on the identified model. Due to errors associated with the identification process, degradation in the controller performance is expected. Hence, we use the measured data to directly design the controller without the need for model identification. Our objective here is to design measurement-based controllers for stable and unstable systems, even when the closed-loop architecture is unknown. This proposed method can be very useful for many industrial applications. The proposed control methodology is a reference model design approach which aims at finding suitable parameter values of a fixed-order controller so that the closed-loop frequency response matches a desired frequency response. This reference model design problem is formulated as a nonlinear programming problem using the concept of bounded error, which can then be solved to find suitable values of the controller parameters. In addition to the well-known advantages of data-based control methods, the main features of our proposed approach are: (1) the error is guaranteed to be bounded, (2) it enables us to avoid issues related to the use of minimization methods, (3) it can be applied to stable and unstable plants and does not require any knowledge about the closed-loop architecture, and (4) the controller structure can be selected a priori, which means that low-order controllers can be designed. The proposed technique is experimentally validated through a real position control problem of a DC servomotor, where the results demonstrate the efficacy of the proposed method.
    Automatica 08/2014; 50(8). DOI:10.1016/j.automatica.2014.06.001 · 3.13 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this paper is to present a measurement-based control-design approach for single-input single-output linear systems with guaranteed bounded error. A wide range of control-design approaches available in the literature are based on parametric models. These models can be obtained analytically using physical laws or via system identification using a set of measured data. However, due to the complex properties of real systems, an identified model is only an approximation of the plant based on simplifying assumptions. Thus, the controller designed based on a simplified model can seriously degrade the closed-loop performance of the system. In this paper, an alternative approach is proposed to develop fixed-order controllers based on measured data without the need for model identification. The proposed control technique is based on computing a suitable set of fixed-order controller parameters for which the closed-loop frequency response fits a desired frequency response that meets the desired closed-loop performance specifications. The control-design problem is formulated as a nonlinear programming problem using the concept of bounded error. The main advantages of our proposed approach are: (1) it guarantees that the error between the computed and the desired frequency responses is less than a small value; (2) the difficulty of finding the globally optimal solution in the error minimisation problem is avoided; (3) the controller can be designed without the use of any analytical model to avoid errors associated with the identification process; and (4) low-order controllers can be designed by selecting a fixed low-order controller structure. To experimentally validate and illustrate the efficacy of the proposed approach, proportional-integral measurement-based controllers are designed for a DC (direct current) servomotor.
    International Journal of Control 09/2013; 9(9). DOI:10.1080/00207179.2013.791928 · 1.14 Impact Factor


Available from