Nonlinear Model Reduction and Decentralized Control of Tethered Formation Flight by Oscillation Synchronization

This paper describes a fully decentralized nonlinear control law for spinning tethered formation flight, based on exploiting geometric symmetries to reduce the original nonlinear dynamics into simpler stable dynamics. Motivated by oscillation synchronization in biological systems, we use contraction theory to prove that a control law stabilizing a single-tethered spacecraft can also stabilize arbitrary large circular arrays of spacecraft, as well as the three inline configuration. The convergence result is global and exponential. Numerical simulations and experimental results using the SPHERES testbed validate the exponential stability of the tethered formation arrays by implementing a tracking control law derived from the reduced dynamics

Intelligent tracking control of a DC motor driver using self-organizing TSK type fuzzy neural networks

[[abstract]]In this paper, a self-organizing Takagi–Sugeno–Kang (TSK) type fuzzy neural network (STFNN) is proposed. The self-organizing approach demonstrates the property of automatically generating and pruning the fuzzy rules of STFNN without the preliminary knowledge. The learning algorithms not only extract the fuzzy rule of STFNN but also adjust the parameters of STFNN. Then, an adaptive self-organizing TSK-type fuzzy network controller (ASTFNC) system which is composed of a neural controller and a robust compensator is proposed. The neural controller uses an STFNN to approximate an ideal controller, and the robust compensator is designed to eliminate the approximation error in the Lyapunov stability sense without occurring chattering phenomena. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived to speed up the convergence rates of the tracking error. Finally, the proposed ASTFNC system is applied to a DC motor driver on a field-programmable gate array chip for low-cost and high-performance industrial applications. The experimental results verify the system stabilization and favorable tracking performance, and no chattering phenomena can be achieved by the proposed ASTFNC scheme.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Development and Validation of a Tokamak Skin Effect Transformer model

A control oriented, lumped parameter model for the tokamak transformer including the slow flux penetration in the plasma (skin effect transformer model) is presented. The model does not require detailed or explicit information about plasma profiles or geometry. Instead, this information is lumped in system variables, parameters and inputs. The model has an exact mathematical structure built from energy and flux conservation theorems, predicting the evolution and non linear interaction of the plasma current and internal inductance as functions of the primary coil currents, plasma resistance, non-inductive current drive and the loop voltage at a specific location inside the plasma (equilibrium loop voltage). Loop voltage profile in the plasma is substituted by a three-point discretization, and ordinary differential equations are used to predict the equilibrium loop voltage as function of the boundary and resistive loop voltages. This provides a model for equilibrium loop voltage evolution, which is reminiscent of the skin effect. The order and parameters of this differential equation are determined empirically using system identification techniques. Fast plasma current modulation experiments with Random Binary Signals (RBS) have been conducted in the TCV tokamak to generate the required data for the analysis. Plasma current was modulated in Ohmic conditions between 200kA and 300kA with 30ms rise time, several times faster than its time constant L/R\approx200ms. The model explains the most salient features of the plasma current transients without requiring detailed or explicit information about resistivity profiles. This proves that lumped parameter modeling approach can be used to predict the time evolution of bulk plasma properties such as plasma inductance or current with reasonable accuracy; at least in Ohmic conditions without external heating and current drive sources

Secondary control of microgrids based on distributed cooperative control of multi‐agent systems

This study proposes a secondary voltage and frequency control scheme based on the distributed cooperative control of multi-agent systems. The proposed secondary control is implemented through a communication network with one-way communication links. The required communication network is modelled by a directed graph (digraph). The proposed secondary control is fully distributed such that each distributed generator only requires its own information and the information of its neighbours on the communication digraph. Thus, the requirements for a central controller and complex communication network are obviated, and the system reliability is improved. The simulation results verify the effectiveness of the proposed secondary control for a microgrid test system. © The Institution of Engineering and Technology 2013