Tuning of extended state observer with neural network-based control performance assessment

In the literature, many methods have been proposed The extended state observer (ESO) is an inherent component for tuning bandwidth-parameterized observers. In [49] of the robust control framework that relies on the cancellation and [38], the authors presented an analytical tuning method providing of disturbances using their lumped estimate in the feedforward the best performance of the ADRC structure expressed component of the robust control law. The general idea of solely upon the control-error-dependent criteria in a noiseless such control structure was utilized in many specific robust algorithms environment. In [39] and [6], the authors considered also the such as active disturbance rejection control (ADRC) control cost as a factor that needs to be minimized to reduce the [13, 54], disturbance observer based control (DOBC) [5, 23], energy consumption of the robust control process, while in [26] or robust observer based control [16], while its applicability the observation error of the measured signals was taken into has been proven in many fields including power electronics account. Tuning procedures described in [28] and [12] have [20, 25, 46], temperature control [53], motion control [32, 42], utilized prior knowledge about the plant structure and some and robotics [30, 22]. Besides the fact that there is a wide variety known or identified model parameters to obtain assumed control of ESO architectures that deal with disadvantages of a most performance requirements. In [28] and [14], the authors commonly used Luenberger-like extended high-gain observer presented an observer tuning method that is relative to gains (HGO) [52, 8] in terms of the general disturbance observation of the selected ADRC controller. Some methods consider automatic quality [34], transient performance [40], or the robustness to tools designed for tuning the overall ADRC structure, measurement noise [37, 21], the final characteristics of the control including observer gains, to satisfy some predefined criteria determining system performance depend greatly on the appropriate tuning the robustness of the control structure [36].