Contribution to Robust Control Synthesis Application to Robotics or Aerodynamics Systems

Abstract This thesis contributes to the development of robust control design strategies for uncertain nonlinear mimo systems, in which a model based control approach robust control (H2,H1) framework is introduced and an intelligent control model free control is suggested. In reality an allusion to the Modelizations of the systems CE 150 and TRMS is proposed for the research seems important because they are prerequisite to test the designed robust control law. The investigation starts by a neighboring optimal control law which is coupled with estimation to solve the trajectory tracking and/or regulator problem of a twin-rotor multi-input multi-output system (TRMS) is introduced. The above mentioned technique is applied through the linearization of the TRMS model around its operating point. Since CE-150 helicopters are known for their varying operating conditions along with external disturbances, a local model network H1 control is proposed as a second alternative, for CE-150 helicopter stabilization. The proposed strategy capitalizes on recent developments on H1 control and its promising results in robust stabilization of plants under unstructured uncertainties. Using the fact that the system can be linearized at diferent operating points, a mixed sensitivity H1 controller is designed for the linearized system, and combined within a network to make transitions between them. The proposed control structure ensures robustness, decoupling of the system dynamics while achieving good performance. Alternatively, another approach interval type-2 fuzzy controller is proposed for TRMS control problem because of and owing to, respectively, the nuance existing between model based control approach and model free control, and their simplicity and e�ciency. The main strength of the proposed control algorithm is its robustness with respect to parametric uncertainties and noise measurement. The suggested approaches are validated through a set of computer simulations which illustrate the et ectiveness of the proposed control scheme; the obtained results are presented to illustrate the controller's performance in various operating conditions, and have been successfully applied. A custom real-time control platform design for a quadrotor is introduced and the control framework is designed to be universal but yet, exible for implementation of various control and navigation algorithms. The developed platform is modular and is presented in three categories: hardware, software and communication. System identification is also presented for parameters measurement and estimation. Moreover, a ground station with a graphical user interface is designed for remote control and monitoring. A wireless bidirectional communication unit is also designed to bridge the quadrotor and the ground station. The developed cost e�ective control platform is validated by simulation and experimental tes

Health management using fault detection and fault tolerant control of multicellular converter applied in more electric aircraft system

The increased cost of fuel and maintenance in aircraft system lead to the concept of more electric aircraft, moreover this concept increase the use of power electronic converters in aircraft power system. Since in this application, the reliability is a crucial feature. Therefore, the use of more efficient, reliable and robust power converter with health management capability will be a big challenge. Multicellular topology of power converters has the required performance in terms of efficiency and robustness. However, the increased complexity of control and more power components (power switches and capacitors) goes along with an increase in possibility of failure in multicellular topology. Therefore, the main contribution of this paper is the use of multicellular topology advantageous with fault diagnosis and fault tolerant control in order to increase the robustness reliability. The health management using a fault detection with Fuzzy Pattern Matching (FPM) algorithm when a failure in power switches or flying capacitors of multicellular converter and a Fault Tolerant Control (FTC) with sliding mode of second parallel three cells multicellular converters. Simulation results with Matlab show the increased efficiency and the continuity of work during failure mode in aircraft power system

Fault-Detection-Based Machine Learning Approach to Multicellular Converters Used in Photovoltaic Systems

Today, solar energy systems based on photovoltaic (PV) panels associated with power converters are increasingly used to supply isolated sites. This structure has attracted several studies as a cost-effective, freely available, efficient source of clean and low-cost energy. However, the faults in power converters can affect the stability of the control system by supplying the isolated site with unwanted current and voltage. Therefore, this paper presents a comparative study using a fault-detection-based k-nearest neighbor (KNN) approach, between sliding mode control and exact linearization control applied to an isolated PV-system-based multicellular power converter, in order to assess the robustness and the performance of the two control strategies against the flying capacitor faults. The results obtained for both control methods in different fault cases are analyzed in terms of time series and feature spaces. These results, obtained with MATLAB software, prove the superiority of sliding mode control over exact linearization control in terms of response time, precision, and oscillations of flying capacitor voltages, as well as better separation (classification) between different fault cases in feature space

Design and realization of a real-time control platform for quadrotor unmanned aerial vehicles

This paper introduces a custom real-time control platform design for a quadrotor. The control framework is designed to be universal but yet, flexible for implementation of various control and navigation algorithms. The developed platform is modular and is presented in three categories: hardware, software and communication. System identification is also presented for parameters measurement and estimation. Moreover, a ground station with a graphical user interface is designed in Labview for remote control and monitoring, which makes diagnostic easier. A wireless bidirectional communication unit is also designed to bridge the quadrotor and the ground station. The developed cost effective control platform is validated by Matlab/Simulink simulation and experiment through PID control implementation

Neural network balance control of hopping robots in flight phase under unknown dynamics

In this paper, a balance control scheme is introduced for hopping robots using neural networks. The control strategy uses a trade-off strategy to achieve both hip and body angle control simultaneously with a single controller, which yields reduced complexity. Hence, the proposed controller allows the hopping robot to track a pre-defined state trajectory in flight-phase despite its modeling uncertainties. The overall dynamics complexity is decreased so that a conventional PID controller can be used for leg extension's length tracking. Unlike other control techniques, no velocity sensor, gyroscope, camera, or body location estimation is needed. Furthermore, no offline learning or a priori system dynamics knowledge is required. Results for different situations highlight the performance of the proposed control approach in compensating for nonlinearities and disturbances