The focus of this paper is to develop reliable observer and filtering techniques for finite-dimensional battery models that adequately describe the charging and discharging behaviors. For this purpose, an experimentally validated battery model taken from the literature is extended by a mathematical description that represents parameter variations caused by aging. The corresponding disturbance models account for the fact that neither the state of charge, nor the above-mentioned parameter variations are directly accessible by measurements. Moreover, this work provides a comparison of the performance of different observer and filtering techniques as well as a development of estimation procedures that guarantee a reliable detection of large parameter variations. For that reason, different charging and discharging current profiles of batteries are investigated by numerical simulations. The estimation procedures considered in this paper are, firstly, a nonlinear Luenberger-type state observer with an offline calculated gain scheduling approach, secondly, a continuous-time extended Kalman filter and, thirdly, a hybrid extended Kalman filter, where the corresponding filter gains are computed online.
In this paper, a multi-variable nonlinear control-oriented model of a twin rotor aerodynamic system (TRAS) is presented. The mathematical description of the multibody system is derived using Lagrange's equations. Based on the resulting state-space representation, a multi-variable integral sliding mode control is designed to accurately track desired trajectories for both the azimuth angle and the pitch angle. Due to unmeasurable states and uncertainties stemming from simplifications at modelling as well as disturbance torques, a discrete-time extended Kalman filter (EKF) is employed and combined with a discrete-time implementation of the nonlinear control law. The proposed control strategy allows for an excellent tracking behaviour as highlighted by experimental results.
This paper presents a nonlinear model-based control design for an electro-pneumatic clutch for heavy trucks, which is required at start-up or during gear shifts to disconnect the combustion engine from the gear box. This automated actuator disburdens the driver and provides the necessary actuation force according to the large torque transmitted through the powertrain. The proposed cascaded control structure consists of a fast inner control loop for the internal pressure, which is estimated by a nonlinear reduced-order observer, as well as an outer control loop for the clutch position. The design of the feedback part for the clutch position is based on sliding-mode techniques. A Lyapunovbased approach is used for the inner control loop of the internal pressure, which is usually not measured in truck applications. Thereby, high tracking accuracy is achievable for the piston position as controlled variable. The efficiency of the proposed control structure is demonstrated by experimental results from a dedicated test rig.
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