...Vikas Prasad; Rajiv Tiwari Estimating residual unbalances of a flexible rotor that is fully levitated on active magnetic bearings (AMBs) are challenging tasks due to the modeling error of AMB rotordynamic parameters. In this work, an identification algorithm has been developed for the estimation...

... identification nonlinear tracking control singular perturbation rotary hydraulic servo system The systems in which the suppression of a very small parameter is responsible for the degeneration or reduction of dimension or order of the system is labeled as singularly perturbed systems, which...

...Chris S. Schulz; Donald L. Kunz; Norman M. Wereley System identification techniques are often used to determine the parameters required to define a model of a linear time invariant (LTI) system. The Cramer–Rao bound can be used to validate those parameters in order to ensure that the system model...

... Volterra equations identification Volterra polynomial basis function (VPBF) variable mass underwater vehicle (VMUV) A number of techniques were developed for model selection and parameter estimation of nonlinear systems ( 1 2 3 ). The identification of nonlinear systems using neural...

... are problematic in the sense that the modes are of low frequency, lightly damped, and often closely spaced. The proposed identification algorithm utilizes modal contribution coefficients to monitor the data collection. The algorithm is composed of a two-step process, where the input signal for the second step...

... will be used to estimate f k − 1 1 from the input-output signals. Here, the identification model via LS-SVM approach is referred as f ̂ k − 1 1 . Using Eq. 9 , the control law can be determined directly since the increment Δ u ( k ) of the control signal appears...

...Tae-Hyoung Kim; Xiaoguang Zheng; Toshiharu Sugie This paper considers the problems of both noise tolerant iterative learning control (ILC) and iterative identification for a class of continuous-time systems with unknown bounded input disturbance and measurement noise. To this aim, we first propose...

.... This is analogous to the persistent excitation condition for identification of discrete models. The proposed instrumental variable algorithm is demonstrated within an auto-tuning algorithm for feedback controllers based on plant inversion. In this application, the algorithm is only suitable for lower-order transfer...

...Manabu Kosaka; Hiroshi Uda; Eiichi Bamba; Hiroshi Shibata This study proposes a new deterministic off-line identification method that obtains a state-space model using input and output data with steady state values. This method comprises of two methods: Zeroing the 0 ∼ N -tuple integral values...

...T.-J. Yeh; Shin-Wen Lu; Ting-Ying Wu In this paper, a model and the associated identification procedure are proposed to precisely portray the hysteresis behavior in piezoelectric actuators. The model consists of basic physical elements and utilizes a Maxwell-slip structure to describe hysteresis...

...Michael Vogt; Norbert Mu¨ller; Rolf Isermann Advanced control systems require accurate process models, while processes are often both nonlinear and time variant. After introducing the identification of nonlinear processes with grid-based look-up tables, a new learning algorithm for on-line...

... on the analysis, an algorithm is developed to recover finite length signals and its validity and efficiency are demonstrated by simulation results. When the sensor model is not available, it is shown how a model identification scheme may be incorporated into the developed scheme. Experiments performed...

...-unmatched gyroscope, in which the resonance frequency of the x axis is different from that of the y axis, has sufficient persistence of excitation to permit the identification of all major fabrication imperfections as well as “input” angular rate. Based on this analysis, new operation strategies were...

...Yi Zhang; H. Harry Asada Multichannel blind system identification (MBSI) is a technique for estimating both an unknown input and unknown channel dynamics from outputs measured at different points of the system. MBSI is a powerful tool particularly for the identification and estimation of dynamical...

...Manabu Kosaka; Hiroshi Uda; Hiroshi Shibata In this paper, we propose a deterministic off-line identification method performed by using input and output data with a constant steady-state output response. The method can directly acquire any order of reduced model without knowing the real order...

.... The stability of the estimation error is studied, and real-time results show that the proposed approach combined with a feedback linearization controller performs better than a standard sliding-mode controller. Pneumatic Systems Identification Sliding-Mode Observer Feedback Linearization...

...Mehrzad Namvar; Farhad Aghili This paper presents a combined scheme of identification and robust torque control for rotary hydraulic actuators. The composite controller consists of a dynamic feedback linearizing inner loop cascaded with an optimal l 1 - H ∞ feedback outer loop. The proposed...

.... An open-architecture experimental web platform is developed for conducting real-time control experiments using the active dancer system. The active dancer system model is experimentally identified using the standard system identification techniques available in literature. Three types of control designs...

... and Control Division, May 2002; final revision, December 2002. Associate Editor: N. Olgac. 01 May 2002 01 December 2002 04 06 2003 delay systems identification filtering theory uncertain systems statistical analysis The stochastic optimal guaranteed estimation problem...

...H. M. Park; W. J. Lee A method is developed for the recursive identification of thermal convection system governed by the Boussinesq equation using an extended Kalman filter. A computationally feasible Kalman filter is constructed by reducing the Boussinesq equation to a small number of ordinary...