A Laboratory Experiment to Teach Closed-Loop System Identification

To what extent and in what ways can two closed-loop dynamic systems be said to be similar? This question arises in a wide range of dynamic systems modeling and control system applications. For example, bounds on error models are fundamental to the controller optimization with modern control methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a similar dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal design model) are sought for the purpose of bounding the validity of a model for control and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

System identification deals with the problem of building the mathematical models of dynamical systems according to the input and output data. The open-loop system identification (Observer/Kalman Filter SystemIdentification, OKID) for stable systems without requiring feedback control is introduced first. For identifying marginally stable or unstable system, however, feedback control is required to ensure the overall system stability. The algorithm of closed-loop system identification (CLID) with known feedback dynamics is shown next.

In this paper, we propose a simple framework for closed-loop system identification: the stabilized output error method. Traditional closed-loop system identification methods rely on the linearity of the target system, and they require the identification of noise models or prior knowledge or identifiability of the feedback controllers to obtain unbiased estimates. But in many real-world applications, the noise dynamics and feedback controllers are complex and difficult to identify, and the nonlinearity may not be ignored. The proposed framework introduces a virtual controller that stabilizes the error between model prediction and the output of the target system. This enables us to apply the output error method, which gives unbiased estimates without depending on the noise model and is applicable to a wide range of models, including nonlinear systems, to closed-loop system identification problems. The paper describes the framework and gives the theoretical support and design guidelines for virtual controllers. Through numerical examples, we show the effectiveness of the proposed framework in various situations, which include identification of (a) linear gray box models, (b) systems in the presence of disturbances having realistic complexity, and (c) a nonlinear unstable system in a human-in-the-loop environment.

The frequent minor wars have brought to the fore guided missiles as the main weapon against all types of military targets. Restoring the single shot kill probability can be achieved by using two methods as follows: first, using large warhead with the large lethal area; second, design a robust guidance system to reduce the miss-distance with high single shot kill probability. The performance of an anti-tank guided missile can be enhanced by select the nominal model to design the guidance computer system. Furthermore, an online closed-loop system identification is required to adaptive autopilot design. This paper is devoted to using system identification in position control robotic benchmark via open and closed loops system identification. Hence, applying the closed-loop methods to identify the actuator and airframe of the intended plant in order to design a self-tuning controller. The online system identification is based on the recursive least square method.

Identification of dynamic systems operating under feedback control is an important issue. A bias correction method was previously proposed for indirect identification of closed-loop systems with disturbances. A key assumption used in deriving this method required that the order of the controller is not less than that of the open-loop plant. In this paper it is shown that this assumption can be removed by prefiltering the input data through a digital prefilter, so that this method can be applied to unbiased identification of closed-loop systems with low order controllers.

In this paper, we consider a problem to estimate process parameters using input-output data collected from the process operating in closed-loop control system. When orders and delay-time of the process are known correctly, under some conditions of identifying experiments, it is reported that accurate identification results can be obtained by applying prediction error method. To get accurate estimates, it is necessary to know orders and delay-time of the process. It is difficult to determine them in closed-loop identification, because ill-condition for identification are easily caused by selection of unsuitable order or delay-time. Furthermore, the procedures to select orders and delay-time in open-loop identification aren't always available in closed-loop identification. The purpose of this paper is to determine a delay-time under suitable assumption that order of the process are known as the first step.

System identification in closed-loop has been of considerable interest in the last two decades. Most of the existing methods have been developed for discrete-time models. In this paper, various instrumental variable-based methods are proposed for identifying continuous-time models of systems operating in closed-loop. The accuracy of these methods is also investigated leading to the definition of the optimal IV estimator which gives minimum variance. As this needs the exact knowledge of the noise model, it cannot be used directly in practice. Several alternatives are therefore proposed to cope with this drawback and illustrated with a simulation example.

Piston engine system identification models are crucial for autonomous and control-oriented applications. However, piston engines exhibit relatively unstable behavior, which may lead to overspeed during open-loop operation. In this study, system identification of a piston engine is investigated on a piston engine–dynamometer test bench. The identification process is carried out under closed-loop conditions to ensure safe and reliable operation. Known system parameters are utilized to transform the closed-loop system into an equivalent open-loop representation. Three system identification models—a State-Space model, a nonlinear ARX model, and a Hammerstein–Wiener model—are employed and comparatively evaluated. The identified models are validated based on their closed-loop responses. Subsequently, a gain scheduled cruise controller is designed using the identified model and implemented on an engine dynamic model. Finally, a disturbance observer is integrated into the cruise controller to enhance disturbance rejection performance. The disturbance observer is developed based on the identified system model.

Background. Registrars play a vital role in teaching undergraduate (UG) medical students. Previous studies indicate that registrars contribute as much as 30% of medical students’ knowledge and that up to 20% of a registrar’s time is spent on teaching UG medical students. The Association for Medical Education in Europe (AMEE) Guide No. 20 defines 12 roles of a teacher, including an on-the-job role-model. Objective. To evaluate the perception and attitudes of registrars with regard to their role as teachers of UG medical students. Methods. A questionnaire-based study with qualitative and quantitative aspects was conducted at the Faculty of Health Sciences, University of Pretoria, South Africa. Results. Despite numerous attempts, the response rate to the study was very poor, with only 25 registrars participating. This pilot study indicated that registrars were mostly involved with on-the-job training, followed by ward rounds and practical sessions. The attitudes towards teaching included that registrars deemed teaching as beneficial, with only three indicating that it should not be done by registrars. Advantages of teaching included own learning opportunities and gaining confidence in teaching. Registrars’ own workload and lack of time hampered teaching. The majority of registrars indicated that receiving training with regard to teaching would be useful. Conclusion. Our pilot study concurs with international studies, indicating that the benefits of teaching medical students include knowledge acquired by registrars. Studies showed that the knowledge obtained in this manner outweighed that obtained by self-study/attendance of lectures. The on-the-job role-model as part of teaching is applicable to registrars. The international literature indicates that until recently registrars were not offered a formal teaching programme. Our study echoed this, with only one student indicating that it is not necessary, as registrars should not be expected to teach.

Background . Numerous articles have been published on the use of autopsies in training medical students in anatomy and different branches of pathology. Some authors have described the emotional response of students who attend such postmortem sessions. Forensic pathology is an important subdivision of pathology. In some countries undergraduate medical students are expected to attend postmortem examinations on persons who died from traumatic causes. Objective . To determine the attitudes and perceptions of 5th-year medical students with regard to forensic postmortem examinations at the University of Pretoria, South Africa. Methods . A questionnaire was voluntarily completed by medical students on the last day of the practical rotation. Results . The overall rating of the practical rotation was 82%. The strengths, weaknesses, opportunities and threats (SWOT) analysis indicated the following as strengths: record keeping, legislation review and traumatology description; as weaknesses: emotional trauma and nightmares; as opportunities: the attendance of autopsies; and as threats: physical dangers. Conclusion . The current study was similar to international studies with regard to students’ emotional response to attending autopsies. The autopsy remains a valuable teaching tool for undergraduate students. Emotional support is currently available for all students to assist them in overcoming their fear of attending forensic autopsy sessions.

Although the dynamic characteristics of the baroreflex system have been described by baroreflex transfer functions obtained from open-loop analysis, the predictability of time-series output dynamics from input signals, which should confirm the accuracy of system identification, remains to be elucidated. Moreover, despite theoretical concerns over closed-loop system identification, the accuracy and the predictability of the closed-loop spontaneous baroreflex transfer function have not been evaluated compared with the open-loop transfer function. Using urethane and α-chloralose anaesthetized, vagotomized and aortic-denervated rabbits (n = 10), we identified open-loop baroreflex transfer functions by recording renal sympathetic nerve activity (SNA) while varying the vascularly isolated intracarotid sinus pressure (CSP) according to a binary random (white-noise) sequence (operating pressure ± 20 mmHg), and using a simplified equation to calculate closed-loop-spontaneous baroreflex transfer function while matching CSP with systemic arterial pressure (AP). Our results showed that the open-loop baroreflex transfer functions for the neural and peripheral arcs predicted the time-series SNA and AP outputs from measured CSP and SNA inputs, with r2 of 0.8 ± 0.1 and 0.8 ± 0.1, respectively. In contrast, the closed-loop-spontaneous baroreflex transfer function for the neural arc was markedly different from the open-loop transfer function (enhanced gain increase and a phase lead), and did not predict the time-series SNA dynamics (r2; 0.1 ± 0.1). However, the closed-loop-spontaneous baroreflex transfer function of the peripheral arc partially matched the open-loop transfer function in gain and phase functions, and had limited but reasonable predictability of the time-series AP dynamics (r2, 0.7 ± 0.1). A numerical simulation suggested that a noise predominantly in the neural arc under resting conditions might be a possible mechanism responsible for our findings. Furthermore, the predictabilities of the neural arc transfer functions obtained in open-loop and closed-loop conditions were validated by closed-loop pharmacological (phenylephrine and nitroprusside infusions) pressure interventions. Time-series SNA responses to drug-induced AP changes predicted by the open-loop transfer function matched closely the measured responses (r2, 0.9 ± 0.1), whereas SNA responses predicted by closed-loop-spontaneous transfer function deviated greatly and were the inverse of measured responses (r, −0.8 ± 0.2). These results indicate that although the spontaneous baroreflex transfer function obtained by closed-loop analysis has been believed to represent the neural arc function, it is inappropriate for system identification of the neural arc but is essentially appropriate for the peripheral arc under resting conditions, when compared with open-loop analysis.

The instrumental variable (IV) method is one of the most renowned methods for parameter estimation. Its bigger advantage is that it is applicable for open-loop as well as for closed-loop systems. The main difficulty in closed-loop identification is due to the correlation between the disturbances and the control signal induced by the loop. In order to overcome this problem, additional excitation signal is introduced. Non-recursive modifications of the instrumental variable method for closed-loop system identification on the base of a generalized IV method have been developed (Atanasov and Ichtev, 2009; Gilson and Van den Hof, 2001; Gilson and Van den Hof, 2003). In this paper, recursive algorithms for theses modifications are proposed and investigated. A simulation is carried out in order to illustrate the obtained results.

Steady-state and parameter tracking properties of self-tuning minimum variance regulators

Physiologia PlantarumVolume 10, Issue 2 p. 302-305 The Role of the Seedcoat in Chlorophyll Deficiency (Albinism) of Citrus Seedlings J. M. Tager, J. M. Tager Department of Subtropical Horticulture, University of California, Los Angeles 24, California Jesse D. Carr Fellow in Agriculture, 1949. Plant Physiological Research Institute, University of Pretoria, Pretoria, South Africa.Search for more papers by this authorS. H. Cameron, S. H. Cameron Department of Subtropical Horticulture, University of California, Los Angeles 24, CaliforniaSearch for more papers by this author J. M. Tager, J. M. Tager Department of Subtropical Horticulture, University of California, Los Angeles 24, California Jesse D. Carr Fellow in Agriculture, 1949. Plant Physiological Research Institute, University of Pretoria, Pretoria, South Africa.Search for more papers by this authorS. H. Cameron, S. H. Cameron Department of Subtropical Horticulture, University of California, Los Angeles 24, CaliforniaSearch for more papers by this author First published: April 1957 https://doi.org/10.1111/j.1399-3054.1957.tb06952.xCitations: 4 Jesse D. Carr Fellow in Agriculture, 1949. Plant Physiological Research Institute, University of Pretoria, Pretoria, South Africa. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Citing Literature Volume10, Issue2April 1957Pages 302-305 RelatedInformation

This article is concerned with the identification of culturally significant architectural structures and features on the archaeological sites Mapungubwe and K2, two 11th to 13th Century AD African capitals in the current Mapungubwe Cultural Landscape World Heritage Site in the Limpopo Province, South Africa. The objective of the article is to identify the typical architectural structures and features of the two sites, based on the original archaeological field research reports of the University of Pretoria (UP) as a primary source of information, for the purposes of architectural reconstruction and educational presentation. The archaeological field reports in the Mapungubwe Archive at UP are briefly reviewed as primary sources of information. Previous archaeological research of the University on Mapungubwe and K2 since 1933 resulted in the establishment of the Mapungubwe Museum and Archive at UP in 2000 where the field records are kept, and in the current reconstruction, interpretation and presentation of the architecture of Mapungubwe and K2 for the educational displays of the Museum. Observed remains of architectural structures and features on Mapungubwe include single free-standing stonewalls; terrace stonewalls, some of which are constructed with steps; stone platforms; stone mortar blocks and mortar hollows on exposed sandstone surfaces; circular stone structures; sets of game-hollows in rock surfaces; and on both sites the remains of circular pole and daub structures varying from small granaries to larger veranda type structures; as well as evidence of palisades and stockade type kraal structures. These architectural structures and features will be reconstructed and their cultural significance explained with the application of trans- disciplinary methodology in further research.