On self-learning mechanism for the output regulation of second-order affine nonlinear systems

This paper studies global robust output regulation of second-order nonlinear systems with input disturbances that encompass the fully-actuated Euler-Lagrange systems. We assume the availability of relative output (w.r.t. a family of reference signals) and output derivative measurements. Based on a specific separation principle and self learning mechanism, we develop an internal model-based controller that does not require apriori knowledge of reference and disturbance signals and it only assumes that the kernels of these signals are a family of exosystems with unknown parameters (e.g., amplitudes, frequencies or time periods). The proposed control framework has a self-learning mechanism that extricates itself from requiring absolute position measurement nor precise knowledge of the feedforward kernel signals. By requiring the high-level task/trajectory planner to use the same class of kernels in constraining the trajectories, the proposed low-level controller is able to learn the desired trajectories, to suppress the disturbance signals, and to adapt itself to the uncertain plant parameters. The framework enables a plug-and-play control mechanism in both levels of control

Output regulation of Euler-Lagrange systems based on error and velocity feedback

Based on a certainty equivalence property, we propose an adaptive internal model control law that solves global robust output regulation of uncertain Euler-Lagrange (EL) systems based only on error (or relative position) and velocity feedback. The proposed controller does not require apriori knowledge of reference signal and its derivatives, which are commonly assumed in literature. It enables a self-learning mechanism of the closed-loop EL systems where the adaptive internal model-based controller is able to learn the desired trajectories and adapt itself to the uncertain plant parameters. Furthermore, the analysis offers insights to the design of internal model-based output regulation for multivariable nonlinear systems with uniform vector relative degree two

Categorising virtual water transfers through China's electric power sector

Water consumption in thermoelectric and hydropower plants in China increased from 1.6 and 6.1 billion m3, respectively, to 3.8 and 14.6 billion m3 from 2002 to 2010. Using the concept of virtual water, we attribute to different electricity users the total water consumption by the electric power sector. From 2002 to 2010, virtual water embodied in the final consumption of electricity (hereinafter referred to as VWEF) increased from 1.90 to 7.35 billion m3, whilst virtual water in electricity used by industries (hereinafter referred to as VWEI) increased from 5.82 to 11.13 billion m3. The inter-provincial virtual water trades as a result of spatial mismatch of electricity production and consumption are quantified. Nearly half (47.5% in 2010) of the physical water inputs into the power sector were virtually transferred across provincial boundaries in the form of virtual water embodied in the electricity produced, mainly from provinces in northeast, central and south China to those in east and north China. Until 2030, VWEF and VWEI are likely to increase from 5.27 and 14.89 billion m3 to 7.19 and 20.33 billion m3, respectively. Climate change mitigation and water conservation measures in the power sector may help to relieve the regional pressures on water resources imposed by the power sector

Distributed formation control for manipulator end-effectors

We present three classes of distributed formation controllers for achieving and maintaining the 2D/3D formation shape of manipulator end-effectors to cope with different scenarios due to availability of modeling parameters. We firstly present a distributed formation controller for manipulators whose system parameters are perfectly known. The formation control objective is achieved by assigning virtual springs between end-effectors and by adding damping terms at joints, which provides a clear physical interpretation of the proposed solution. Subsequently, we extend it to the case where manipulator kinematic and system parameters are not exactly known. An extra integrator and an adaptive estimator are introduced for gravitational compensation and stabilization, respectively. Simulation results with planar manipulators and with seven degree-of-freedom humanoid manipulator arms are presented to illustrate the effectiveness of the proposed approach.Comment: arXiv admin note: text overlap with arXiv:2103.1459