Browsing by Author "Jeon, Byoung-Ju"
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Item Open Access Closed-loop analysis with incremental backstepping controller considering measurement bias(Elsevier, 2019-11-25) Jeon, Byoung-Ju; Seo, Min-Guk; Shin, Hyo-Sang; Tsourdos, AntoniosIn this paper, closed loop system characteristics with an incremental backstepping controller are investigated through theoretical analysis when both measurement biases and model uncertainties exist. Incremental backstepping algorithm is proposed in previous studies to reduce model dependency of classical backstepping algorithm with additional measurements about state derivatives and control surface deflection angles. This research enables to have following critical understandings especially about the effects of biases on these additional measurements to system characteristics with incremental backstepping method. First, these biases do not affect a characteristic equation, so they do not have any influence about a condition for absolute stability. Second, these biases cause a steady state error, and model uncertainty in control effectiveness information starts to have an impact to it when these biases are additionally considered.Item Open Access Composite adaptive backstepping control considering computational complexity and relaxation of persistent excitation(Elsevier, 2020-11) Jeon, Byoung-Ju; Shin, Hyo-Sang; Tsourdos, AntoniosA new composite adaptive backstepping control is proposed in this paper, which achieves parameter estimation convergence without persistent excitation and reduces estimation problem dimension for less computational complexity. A composite adaptation law is utilized to improve estimation and tracking performance. Relaxation of the persistent excitation requirement for parameter convergence is accomplished by making information matrix full rank only with finite excitation. The adaptation law for the proposed composite adaptive backstepping control algorithm estimates parameters in each loop separately by taking an advantage from a cascade control structure of backstepping control. Comparing to the adaptation laws which estimate whole parameters of the dynamic system at once, the designed adaptation law deals with smaller estimation problems, resulting in reduced computational complexity.Item Open Access Understandings of classical and incremental backstepping controllers with model uncertainties(IEEE, 2019-11-11) Jeon, Byoung-Ju; Seo, Min-Guk; Shin, Hyo-Sang; Tsourdos, AntoniosThis paper suggests closed-loop analysis results for both classical and incremental backstepping controllers considering model uncertainties. First, transfer functions with each control algorithm under the model uncertainties, are compared with the ones for the nominal case. The effects of the model uncertainties on the closed-loop systems are critically assessed via investigations on stability conditions and performance metrics. Second, closed-loop characteristics with classical and incremental backstepping controllers under the model uncertainties are directly compared using derived common metrics from their transfer functions. This comparative study clarifies how the effects of the model uncertainties to the closed-loop system become different depending on the applied control algorithm. It also enables understandings about the effects of additional measurements in the incremental algorithm. Third, case studies are conducted assuming that the uncertainty exists only in one aerodynamic derivative estimate while the other estimates have true values. This facilitates systematic interpretations on the impacts of the uncertainty on the specific aerodynamic derivative estimate to the closed-loop system.Item Open Access Understandings of incremental backstepping controller considering measurement delay with model uncertainty(Elsevier, 2020-12-07) Jeon, Byoung-Ju; Seo, Min-Guk; Shin, Hyo-Sang; Tsourdos, AntoniosIn this paper, closed loop characteristics with an incremental backstepping (IBKS) controller are investigated with consideration of measurement delays and model uncertainties. To judge absolute stability of the system, a systematic analysis framework is proposed which examines the existence of unstable poles from a derived characteristic equation with high nonlinearity due to the considered measurement delays. One of the key findings from the analysis results is that the system is stable only when a specific relationship between the measurement delays is satisfied and this stability condition is affected by the model uncertainty. Critical understandings about individual and integrated effects of the measurement delays and the model uncertainties to the system are suggested through a comparative study. Verification and validation of the obtained properties from the framework are performed through simulations.Item Open Access Understandings of the incremental backstepping control through theoretical analysis under the model uncertainties(IEEE, 2018-10-29) Jeon, Byoung-Ju; Seo, Min-Guk; Shin, Hyo-Sang; Tsourdos, AntoniosIn this paper, theoretical analysis on the incremental backstepping control is suggested especially under the existence of model uncertainties. This algorithm is proposed in the previous studies by modifying the backstepping method to reduce model dependency. Because this method is a type of nonlinear control and the model uncertainties are assumed to be considered, it is difficult to have theoretical analysis, which causes lack of understandings about this algorithm. Therefore, this paper suggests closed-loop analysis with simplified dynamics under the model uncertainty. Transfer function is derived and poles, stability condition, steady state error, and settling time are presented. In addition, the effects of model uncertainties and gains are identified through analysis. Proposed analysis is meaningful in terms of establishing critical understandings about the algorithm, even though the simplified dynamics is applied for analysis purpose.