scholarly journals PID Controller Design and Closed-Loop Identification with Linear Time-Invariant

In this research, analysis and developed identification of closed loop system with mathematical modeling. Implemented the mathematical analysis & the process parameters by the data obtain in the closed-loop test. Tuned the closed-loop system by control system methodology and using controller. To analyzed the behavior and all parameters of closed loop system i.e. the parameters include stability, frequency, load disturbance and the system output etc. experiment the proposed work for model identification and performance of set point and load-disturbance ,controller output ,robustness, stability margins, noise measurement etc.

Author(s):  
Huzefa Shakir ◽  
Won-Jong Kim

This paper presents improved empirical representations of a general class of open-loop unstable systems using closed-loop system identification. A multi-axis magnetic-levitation (maglev) nanopositioning system with an extended translational travel range is used as a test bed to verify the closed-loop system-identification method proposed in this paper. A closed-loop identification technique employing the Box-Jenkins (BJ) method and a known controller structure is developed for model identification and validation. Direct and coupling transfer functions (TFs) are then derived from the experimental input-output time sequences and the knowledge of controller dynamics. A persistently excited signal with a frequency range of [0, 2500] Hz is used as a reference input. An order-reduction algorithm is applied to obtain TFs with predefined orders, which give a close match in the frequency range of interest without missing any significant plant dynamics. The entire analysis is performed in the discrete-time domain in order to avoid any errors due to continuous-to-discrete-time conversion and vice versa. Continuous-time TFs are used only for order-reduction and performance analysis of the identified plant TFs. Experimental results in the time as well as frequency domains verified the accuracy of the plant TFs and demonstrated the effectiveness of the closed-loop identification and order-reduction methods.


2021 ◽  
Vol 26 (1) ◽  
pp. 21
Author(s):  
Ahmad Taher Azar ◽  
Fernando E. Serrano ◽  
Nashwa Ahmad Kamal

In this paper, a loop shaping controller design methodology for single input and a single output (SISO) system is proposed. The theoretical background for this approach is based on complex elliptic functions which allow a flexible design of a SISO controller considering that elliptic functions have a double periodicity. The gain and phase margins of the closed-loop system can be selected appropriately with this new loop shaping design procedure. The loop shaping design methodology consists of implementing suitable filters to obtain a desired frequency response of the closed-loop system by selecting appropriate poles and zeros by the Abel theorem that are fundamental in the theory of the elliptic functions. The elliptic function properties are implemented to facilitate the loop shaping controller design along with their fundamental background and contributions from the complex analysis that are very useful in the automatic control field. Finally, apart from the filter design, a PID controller loop shaping synthesis is proposed implementing a similar design procedure as the first part of this study.


1995 ◽  
Vol 117 (4) ◽  
pp. 484-489
Author(s):  
Jenq-Tzong H. Chan

A correlation equation is established between open-loop test data and the desired closed-loop system characteristics permitting control system synthesis to be done on the basis of a numerical approach using experimental data. The method is applicable when the system is linear-time-invariant and open-loop stable. The major merits of the algorithm are two-fold: 1) Arbitrary placement of the closed-loop system equation is possible, and 2) explicit knowledge of an open-loop system model is not needed for the controller synthesis.


Author(s):  
Z Ren ◽  
G G Zhu

This paper studies the closed-loop system identification (ID) error when a dynamic integral controller is used. Pseudo-random binary sequence (PRBS) q-Markov covariance equivalent realization (Cover) is used to identify the closed-loop model, and the open-loop model is obtained based upon the identified closed-loop model. Accurate open-loop models were obtained using PRBS q-Markov Cover system ID directly. For closed-loop system ID, accurate open-loop identified models were obtained with a proportional controller, but when a dynamic controller was used, low-frequency system ID error was found. This study suggests that extra caution is required when a dynamic integral controller is used for closed-loop system identification. The closed-loop identification framework also has significant effects on closed-loop identification error. Both first- and second-order examples are provided in this paper.


2016 ◽  
Vol 24 (4) ◽  
pp. 722-738 ◽  
Author(s):  
Atta Oveisi ◽  
Tamara Nestorović

A robust nonfragile observer-based controller for a linear time-invariant system with structured uncertainty is introduced. The [Formula: see text] robust stability of the closed-loop system is guaranteed by use of the Lyapunov theorem in the presence of undesirable disturbance. For the sake of addressing the fragility problem, independent sets of time-dependent gain-uncertainties are assumed to be existing for the controller and the observer elements. In order to satisfy the arbitrary H2-normed constraints for the control system and to enable automatic determination of the optimal [Formula: see text] bound of the performance functions in disturbance rejection control, additional necessary and sufficient conditions are presented in a linear matrix equality/inequality framework. The [Formula: see text] observer-based controller is then transformed into an optimization problem of coupled set of linear matrix equalities/inequality that can be solved iteratively by use of numerical software such as Scilab. Finally, concerning the evaluation of the performance of the controller, the control system is implemented in real time on a mechanical system, aiming at vibration suppression. The plant under study is a multi-input single-output clamped-free piezo-laminated smart beam. The nominal mathematical reduced-order model of the beam with piezo-actuators is used to design the proposed controller and then the control system is implemented experimentally on the full-order real-time system. The results show that the closed-loop system has a robust performance in rejecting the disturbance in the presence of the structured uncertainty and in the presence of the unmodeled dynamics.


2018 ◽  
Vol 41 (3) ◽  
pp. 687-695
Author(s):  
Weilin Wu ◽  
Wei Xie ◽  
Wei He ◽  
Langwen Zhang

This paper deals with the problem of designing a switching controller, which includes several linear time-invariant (LTI) controllers designed beforehand and independently for a specific LTI plant with corresponding H2 control performance criteria. It is possible to find suitable state space realizations for any given family of controller transfer matrices, which guarantee not only certain H2 performance of the overall closed-loop system under arbitrary switching but also the corresponding H2 performance of local subsystems at each switching point. The effectiveness of the proposed method is demonstrated with a numerical example.


Author(s):  
Hassene Jammoussi ◽  
Matthew Franchek ◽  
Karolos Grigoriadis ◽  
Martin Books

A closed-loop system identification method is developed to estimate the parameters of a single input single output (SISO) linear time invariant system (LTI) operating within a feedback loop. The method uses the reference command in addition to the input–output data and establishes a correlation framework to structure the system. The correlation-based method is capable of delivering consistent estimates provided that the specific conditions on the signals are met. The method parallels the instrumental variables four step algorithm (IV4) and is comprised of three steps. First a model is estimated using cross correlation calculations between the reference input signal and the control and measured output signals. In the second step, a prefilter is identified to reduce estimation bias. In the final step, the prefilter, the instrumental variables and the measured signals are employed to estimate the final model. A consistency proof is provided for the proposed estimation process. The method is demonstrated on two examples. The first uses data collected from a diesel engine operation, and an open-loop model relating fueling to engine speed is sought. The identification process is complicated by the presence of nonmeasurable external torque disturbances and stochastic sensor noise. The second example uses data obtained from a time domain simulation of a closed-loop system where high levels of nonmeasured noise and disturbances were considered and a comparison with existing methods is made.


Author(s):  
Nomzamo Tshemese-Mvandaba ◽  
R. Tzoneva ◽  
M. E. S. Mnguni

An enhanced method for design of decenralised proportional integral (PI) controllers to control various variables of flotation columns is proposed. These columns are multivariable processes characterised by multiple interacting manipulated and controlled variables. The control of more than one variable is not an easy problem to solve as a change in a specific manipulated variable affects more than one controlled variable. Paper proposes an improved method for design of decentralized PI controllers through the introduction of decoupling of the interconnected model of the process. Decoupling the system model has proven to be an effective strategy to reduce the influence of the interactions in the closed-loop control and consistently to keep the system stable. The mathematical derivations and the algorithm of the design procedure are described in detail. The behaviour and performance of the closed-loop systems without and with the application of the decoupling method was investigated and compared through simulations in MATLAB/Simulink. The results show that the decouplers - based closed-loop system has better performance than the closed-loop system without decouplers. The highest improvement (2 to 50 times) is in the steady-state error and 1.2 to 7 times in the settling and rising time. Controllers can easily be implemented.


Author(s):  
Nathan A. Weir ◽  
Andrew G. Alleyne

Abstract Due to the unique structure of two-input single-output (TISO) feedback systems, several closed-loop properties can be characterized using the concepts of plant and controller “directions” and “alignment.” Poor plant/controller alignment indicates significant limitations in terms of closed-loop performance. In general, it is desirable to design a controller that is well aligned with the plant in order to minimize the size of the closed-loop sensitivity functions and closed-loop interactions. Although the concept of alignment can be a useful analysis tool for a given plant/controller pair, it is not obvious how a controller should be designed to achieve good alignment. We present a new controller design approach, based on the PQ method (Schroeck et al., 2001, “On Compensator Design for Linear Time invariant Dual-Input Single-Output Systems,” IEEE/ASME Trans. Mechatronics, 6(1), pp. 50–57), which explicitly incorporates knowledge of alignment into the design process. This is accomplished by providing graphical information about the alignment angle on the Bode plot of the PQ frequency response. We show the utility of this approach through a design example.


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