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A New Approach to Robust MPC Design for LPV Systems in Input-Output Form
(
Elsevier B.V.
, 2018 , Conference Paper)
In this paper, a robust model predictive control (MPC) technique is introduced to control MIMO linear parameter-varying (LPV) systems subject to input-output constraints. The LPV system is represented in input-output form, ...
A novel particle filter parameter prediction scheme for failure prognosis
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
Particle filters are well-known as powerful tools for accomplishing state and parameter estimation and their propagation prediction in nonlinear dynamical systems. Their ability to include system model parameters as part ...
Sensor fault detection and isolation using multiple robust filters for linear systems with time-varying parameter uncertainty and error variance constraints
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
In this paper, a robust sensor fault detection and isolation (FDI) strategy is proposed by means of the multiple model (MM)-based scheme. The proposed approach is composed of robust Kalman filters (RKF) with error variance ...
Event-triggered control for discrete-time linear parameter-varying systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
This paper examines a new event-triggered control design approach for discrete-time linear parameter-varying (LPV) systems to reduce the data transmission of the scheduling variables and states to the controller. A parameter ...
Health monitoring and degradation prognostics in gas turbine engines using dynamic neural networks
(
American Society of Mechanical Engineers (ASME)
, 2015 , Conference Paper)
In this paper two artificially intelligent methodologies are proposed and developed for degradation prognosis and health monitoring of gas turbine engines. Our objective is to predict the degradation trends by studying ...
Multiple sensor fault diagnosis for non-linear and dynamic system by evolving approach
(
2012 3rd Annual IEEE Prognostics and System Health Management Conference, PHM-2012
, 2012 , Conference Paper)
Reliability of sensor measurement is vital to assure the performance of complex and nonlinear industrial operation. In this paper, the problem of designing and development of a data-driven multiple sensor fault detection ...
Multiple-model based sensor fault diagnosis using hybrid kalman filter approach for nonlinear gas turbine engines
(
2013 1st American Control Conference, ACC 2013
, 2013 , Conference Paper)
In this paper, an efficient sensor fault detection and isolation (FDI) strategy is proposed based on multiple-model (MM) approach. The scheme is composed of hybrid kalman filters (HKF) by integrating a nonlinear gas turbine ...
Reconfigurable control of linear systems based on state feedback adaptive virtual actuator
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
In this paper, design and development of fault tolerant control (FTC) of linear systems subject to loss of effectiveness and time-varying additive actuator faults as well as an external disturbance using the fault-hiding ...
Linear parameter-varying control of a copolymerization reactor
(
Elsevier B.V.
, 2015 , Conference Paper)
This paper demonstrates the application of the linear parameter-varying (LPV) framework to control a copolymerization reactor. An LPV model representation is first developed for a nonlinear model of the process. The LPV ...
Actuator fault detection and isolation of differential drive mobile robots using multiple model algorithm
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
An actuator fault detection and isolation (FDI) scheme is proposed in this paper for differential drive mobile robots based on the concept of multiple model approach. The nonlinear kinematic model of the mobile robot is ...