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This paper deals with the problem of fault estimation for linear and nonlinear systems. An adaptive proportional integral observer is designed to estimate both the system state and sensor and actuator faults which can affect the system. The model of the system is first augmented in such a manner that the original sensor faults appear as actuator faults in this new model. The faults are then considered...
In high-performance servo applications, a rapid and accurate torque control is required, preferable without the use of the motion-state sensor. The use of permanent magnet synchronous motors combined with direct torque control techniques provides many opportunities to achieve this goal. The purpose of this paper is to improve the modeling and the control of a typical tubular permanent-magnet linear...
This paper deals with the problem of fault detection and identification in noisy systems. A proportional integral observer with unknown inputs is used to reconstruct state and sensors faults. A mathematical transformation is made to conceive an augmented system, in which the initial sensor fault appear as an unknown input. The noise effect on the state and fault estimation errors is also minimized...
This paper, deals with a control method of linear multi-input multi-output (MIMO) system, developed in order to ensure the tracking of a reference trajectory. The flatness-based controller for studied system allows to solve path planning and path tracking problems. The desired trajectory is designed using the flatness property of controllable system. The flatness concept in path planning is considered...
In this paper, a combined approach of a designed controller based on flatness and fuzzy logic techniques control is proposed. The basic of this control strategy consists in planning a reference trajectory using the flatness property of linear systems. The real output desired trajectory of process will be expressed by the flat output reference trajectory. After the planning phase, the tracking of the...
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