UKACC International Conference on Control 

About: UKACC International Conference on Control is an academic conference. The conference publishes majorly in the area(s): Control theory & Control system. Over the lifetime, 1184 publications have been published by the conference receiving 7795 citations.

An LMI approach to H/sub -//H/sub /spl infin// fault detection observers

Abstract: A new approach, namely the mixed H-/H∞ estimation, to robust fault detection problem for dynamic systems is presented. The H-/H∞ fault detection observer is designed to minimise effects of disturbances on the residual of the observer whilst maximising the effects of faults on the residual signal. This takes into account the robustness of a fault detection observer against disturbances and sensitivity to faults simultaneously. The H-/H∞ fault detection observer problem is actually a mixed H-/H∞ estimation problem. The latter can be further reformulated as a constrained H∞ estimation problem and solved in a mixed linear matrix inequality (LMI) setting.

Control allocation for fault tolerant control of a VTOL octorotor

Abstract: For the fault tolerant control of an eight-rotor VTOL Unmanned Air Vehicle (UAV), a control allocation scheme is proposed. The eight-rotor configuration provides actuator redundancy to ensure safe operation under rotor/motor failures. A PD controller is used to generate total thrust and moment demands. A cascade inverse method of control allocation is proposed to allocate the controller commands to the actuators whilst ensuring that actuator saturation does not occur. If the vehicle is subjected to rotor failures, the scheme re-allocates the commands to maintain the vehicle stability and performance. Until actuator saturation occurs the response of the vehicle is the same when operating with all motors or fewer. The response of the vehicle to several combinations of complete actuator failures is investigated by simulation and it is shown that the proposed method is able to maintain control after failure of up to four actuators. The controller is invarient and the vehicle response to commands is identical until motor saturation occurs.

Support Vector Machines for System Identification

Abstract: Support vector machines (SVM) are used for system identification of both linear and nonlinear dynamic systems. Discrete time linear models are used to illustrate parameter estimation and nonlinear models demonstrate model structure identification. The VC-dimension of a trained SVM indicates the model accuracy without using separate validation data. We conclude that SVM have potential in the field of dynamic system identification, but that there are a number of significant issues to be addressed.

Local basis function networks for identification of a turbocharger

Abstract: This paper deals with nonlinear dynamic system identification by local basis function networks A special kind of local basis function network generated by a tree construction algorithm is proposed This local linear model tree (LOLIMOT) is applied for identification of a truck diesel engine exhaust turbocharger The charging pressure is modelled as the output of a nonlinear second order multiple input system with engine speed and injection rate as inputs The LOLIMOT approach was capable to identify the turbocharger with measured signals during road driving and with ten local linear models in less than one minute on a Pentium PC