Online State Space Model Parameter Estimation in Synchronous Machines

The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is considered as the input and the rotor angle and the active power are considered as the generator outputs. In fact, the third order nonlinear state space model is converted to only two linear regression equations. Then, easy-implemented regression equations are used to estimate the unknown parameters of the nonlinear model. The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation

Cost performance based control reconfiguration in multi-agent systems

In this paper, a reconfigurable control protocol for a linear multi-agent system seeking consensus in presence of actuator faults and saturations is investigated. The control protocol consists of two parts: healthy system controller and faulty system controller. The main objective of the healthy controller that is designed off-line is to determine the protocol which guarantees team consensus and minimizes the team performance index. On the other hand, the faulty system controller is designed on-line and aims at stabilizing the consensus error signals and optimizing the faulty team performance index subject to constrained input signals. Both centralized and semi-distributed architectures for control reconfiguration are developed. In the centralized scheme, the team is considered as a single unit and the central module reconfigures the entire system controllers, while in the semi-distributed approach faulty agent uses its immediate neighbours information (i.e. measurements and control gains) to reconfigure its controller. 2014 American Automatic Control Council.Qatar National Research FundScopu

Distributed reconfigurable control strategies for switching topology networked multi-agent systems

In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable information on the estimation of faults severities. Our proposed strategies will ensure that the agents reach a consensus while an upper bound on the team performance index is ensured and satisfied. Three types of actuator faults are considered, namely: the loss of effectiveness fault, the outage fault, and the stuck fault. By utilizing quadratic and convex hull (composite) Lyapunov functions, two cooperative and distributed recovery strategies are designed and provided to select the gains of the proposed control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of autonomous underwater vehicles (AUVs) under directed switching topologies and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of our proposed distributed reconfiguration control laws in compensating for the effects of sudden actuator faults and subject to fault diagnosis module uncertainties and unreliabilities. 1 2017 ISAScopu

Robust cooperative control reconfiguration/recovery in multi-agent systems

In this paper, a reconfigurable control protocol for a linear multi-agent system seeking consensus in presence of actuator faults and saturations and environmental disturbances is investigated. Two controllers, namely the healthy controller and the reconfigured controller, are proposed for the healthy system and the system with faulty agents, respectively. The healthy controller is designed off-line and guarantees that the team achieves consensus in presence of environmental disturbances. On the other hand, the reconfigured/recovered controller is designed on-line subject to constrained control signals and based on the information that the fault detection and identification (FDI) module has provided. The FDI information are assumed to be inaccurate, however the bounds on the uncertainties are assumed to be known. 2014 EUCA.Qatar National Research FundScopu