Conference Paper
Checking if controllers are stabilizing using closedloop 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

Conference Paper: A control design method for unknown systems using frequency domain data
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ABSTRACT: This paper deals with fixedstructure controller design for stable linear systems by using measurements. Most control design approaches developed in the literature are generally based on a mathematical model which can be obtained via identification system by using a set of measured data. However, an identified model, which is often built on the basis of some assumptions, cannot perfectly describe complex behaviors characterizing physical systems. Thus, the performance expected for the closedloop system will be limited by the quality of such models used in the control design process. Hence, databased controller design methods can be viewed as a possible alternative to modelbased methods. In this paper, we propose to directly utilize frequency response data in the controller design. The principle is to design fixedstructure controllers for which the closedloop frequency response fits a desired frequency response. This problem is formulated as an error minimization problem. The main feature of our proposed approach is that controller can be designed free of any mathematical model, which allows to avoid errors associated with identification process. Moreover, it enables to select loworder controllers, which are suitable for embedded systems. A simulation example is given to illustrate and validate the efficacy the proposed approach.Control Conference (ASCC), 2013 9th Asian; 01/2013 
Article: A measurementbased approach for designing reducedorder controllers with guaranteed bounded error
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ABSTRACT: The objective of this paper is to present a measurementbased controldesign approach for singleinput singleoutput linear systems with guaranteed bounded error. A wide range of controldesign 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 closedloop performance of the system. In this paper, an alternative approach is proposed to develop fixedorder controllers based on measured data without the need for model identification. The proposed control technique is based on computing a suitable set of fixedorder controller parameters for which the closedloop frequency response fits a desired frequency response that meets the desired closedloop performance specifications. The controldesign 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) loworder controllers can be designed by selecting a fixed loworder controller structure. To experimentally validate and illustrate the efficacy of the proposed approach, proportionalintegral measurementbased controllers are designed for a DC (direct current) servomotor.International Journal of Control 09/2013; 9(9). · 1.14 Impact Factor 
Conference Paper: A modelfree technique for designing fixedorder controllers
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ABSTRACT: This paper suggests a modelfree control design technique for unknown stable singleinputsingleoutput (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 modelbased 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 fixedorder controller for which the closedloop frequency response is very close to a desired frequency response that describes some desired closedloop 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 closedloop 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 loworder 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
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