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In this paper, the problem of fault isolation and detection is treated for a particular class of linear polytopic parameter-varying system (LPV). In this context, an adaptive observer design is formulated for a given polyquadratic Lyapunov function. As a result, new sufficient conditions are given in terms of Linear Matrix Inequalities (LMIs), which guarantee asymptotic convergence to zero of the estimation error, and to detect and isolate actuator faults. A tentative application was made to show the effectiveness of the proposed algorithm.

In this paper a new topology of cascaded H-bridge (CHB) multilevel inverter employing less number of switches, is presented.

This paper deals with the control design of an asymmetrical cascaded multilevel inverter. This structure therefore provides the capability to produce higher voltages at higher speeds with low switching frequency which has inherent low switching losses and high converter efficiency. Selective harmonic elimination(SHE) for asymmetrical multilevel CHB inverter control is proposed. The technique utilized in the estimation of switching angles involves Firefly Algorithm (FFA). Compared to Newton Raphson algorithm (NR), FFA is more robust and entails less computation time. Simulation results prove the effectiveness of FFA technique compared to NR algorithm. The proposed method does effectively eliminate a number of specific low order harmonics, and the output voltage is resulted in low total harmonic distortion. FFA and NR algorithm for asymmetrical cascaded H-bridge nine level inverter control are experimentally tested on a prototype using FPGA.

This paper presents an algorithm of a robust controller used for the stabilization of biped robot walking gait. The robot is described by a kajita's model with norm bounded uncertainties to ensure a more realistic numerical model. The proposed robust dynamic controller relies on the use of predictive control theory (MPC) and the resolution of a convex optimization problem with Linear Matrix Inequalities (LMI) at every sampling period. The generated control law allows a realtime working robot even in rough ground or unknown environment.

the analysis and control of delayed systems are becoming more and more research topics in progress. This is mainly due to the fact that the delay is frequently encountered in technological systems. Most control command laws are based on current digital computers and delays are intrinsic to the process or in the control loop caused by the transmission time control sequences, or computing time. In other hand, the controls of humanoid walking robot present a common problem in robotics because it involves physical interaction between an articulated system and its environment. This close relationship is actually a common set of fundamental problems such as the implementation of robust stable dynamic control. This paper presents acomplete approach, based on switched system theory, for the stabilization of a compass gait robot subject to time delays transmission. The multiple feedback gains designed are based on multiple linear systems governed by a switching control law. The establishment of control law in real time is affected by the unknown pounded random delay. The results obtained from this method show that the control law stabilize the compass robot walk despite a varying delay reaching six times sampling period.

Problem statement: More advanced control techniques have been developed in recent decades following the great progress of calculation s means. Without considering the constraints on system variables, the response of controlled system moves away from the desired response. Hence the control strategy must provide the ability to integr ate these constraints in the design phase of the controller. Approach: This study presents a design of robust dynamic con troller which was based on the control strategy MPC for an uncertain discrete system described by a multimodel by solving an optimization problem. The Model Predictive Control (MPC) strategy uses a dynamic model of the process in order to predict its future behavior. Th is control strategy, that we propose, makes it poss ible to integrate these constraints in the design phase of the controller. The design of the robust dynamic controller must maintain the stability and performa nce of the system in the presence of uncertainties. The principle of this method was to solve, at each calculation step, a convex optimization problem tha t calculates the matrices characterizing the dynamic controller. LMI formulation of the constraints, on process variables, was introduced into the design p hase of the dynamic controller robust. The optimization study was also implemented in the MATLAB software and simulation studies had been presented. Results: Simulation results had proved the effectiveness of this study. The robust dynamic controller designed for uncertain systems guarantee s stability in closed loop systems by integrating constraints on system variables. Conclusion: The described approach explain how to integrate constraints, MPC type, during the phase of design o f the robust controller: the simulation concluded o n a benchmark proof the powerful of this approach.

Problem statement: The analysis and control of delayed systems are be coming more and more research topics in progress. This is mainly du e to the fact that the delay is frequently encounte red in technological systems. This can affect their sig nificantly operations. Most control command laws are based on current digital computers and delays a re intrinsic to the process or in the control loop caused by the transmission time control sequences, or computing time. The delay may affect one or more states of the considered system. It may also a ffect the establishment of the command. Several studies have investigated the stability of delay sy stems under the assumption that the delay is a vari able phenomenon; such variation is considered to be bounded or limited to facilitate analysis of the system . In this study we propose a modelling of delayed sys tem by using the multimodels and switched system theory. The analysis of stability is based on the u se of second Lyapunov method. The issued stability conditions are expressed as Bilinear Matrix Inequal ities impossible to resolve. That's why we propose the same original relaxations to come over this dif ficulty, an example of induction machine is given t o illustrate over approach. Approach: We propose to use the control theory developed for switched systems to synthesis a control laws for the stabili sation of delays system. Results: We stabilize the induction machine around many operating points despite the non linearities. Conclusion: The developed method is less conservative and less pess imistic than the used classical methods.

In this paper, a comparison between two observers has been made; an adaptive observer and multiobserver for linear time-varying system. This observer has been designed to estimate simultaneously the state space and faults detection (sensors and actors). The convergence of the adaptive observer is implemented under certain condition. An example of a drying blower system is used to show the effectiveness of the proposed observers.

Problem statement: The estimation of states and the unknown inputs of a nonlinear system described by a multimodel are done by a multiobserver. The stabilization of the multiobserver calls upon uses both quadratic and no quadratic functions of Lyapunov. Although the stabilization using the quadratic approach is interesting from the point of view implementation, the step showed its limits for the multimodel. However, the problem paused by the quadratic method lies in the obligation to satisfy several LMI with respect to the same Lyapunov matrix P, these results are shown very conservative. Approach: To reduce the conservatism of the quadratic approach we propose another approach which is exclusively based on Lyapunov piecewise quadratic functions. The conditions obtained by the stabilization of the multiobserver are expressed in term of matrix inequalities with constraints on the matrices rank. Results: The estimation of both states and unknown inputs of a multimodel using the quadratic approach per pieces leads to results less conservative than the quadratic approach. Academic examples illustrate the robustness of the piecewise quadratic approach. Conclusion: In this article we proposed new sufficient conditions of stability of a multiobserver able to the estimation of states and unknown inputs of a nonlinear system describes by a multimodel subjected to the influence of the unknown inputs. The study in was carried out by considering two approaches. The first approach is based on Lyapunov quadratic functions; it is significant to note the great difficulty in finding satisfying results by this approach for the multimodel systems. For this reason we proposed an approach based on piecewise quadratic functions which led to interesting results (proposition 1) and less conservative than the quadratic approach. The conditions suggested in this article concern both the multiobserver stabilization and the estimation of states and the unknown inputs of a multimodel with measurable variables of decision (µξ(k)). The synthesis of a multiobserver with no measurable variables of decision is not approached. This point can constitute an interesting prospect for this study.

In this work, we propose a novel robust dynamic controller in order to stabilize a walking biped robot with input and output constraints. Firstly, the trajectory of the robot is generated via the Zero Moment Point method based on the resolution of a convex optimization problem with Linear Matrix Inequalities. Then, the tracking of a referential trajectory is insured by the design of an optimal dynamic controller with predictive control theory. The synthesized dynamic controller allows the Lyapunov stability of the robot's walk. Moreover, it ensures the reducing of the overshoot and undershoot of the output signal, difficult to be adjusted by classical methods. This work is validated by a simulation via Matlab of some illustrative examples and results highlight the efficiency of the proposed study.

This work aims to design an optimal dynamic controller to stabilize the walk of a biped robot even in the presence of input and output constraints. In a first time, the robot's trajectory is generated via the Zero Moment Point criterion based on the resolution of a convex optimization problem with Linear Matrix Inequalities. In a second time, the tracking of a reference trajectory is insured by the design of an optimal dynamic controller based on the predictive control theory. The synthesized dynamic controller allows for the Lyapunov stability of the robot's walk. Moreover, it ensures the reducing of the overshoot and undershoot of the output signal that are difficult to be adjusted by classical methods based on solving the algebraic Riccati equation. This study is validated by a simulation via Matlab of some illustrative examples. Results are presented to prove the effectiveness of the proposed work.

The principle purpose of this paper is to integrate the generalized predictive control (GPC) in the new methodologies of synthesis of a PID controller. The GPC control is also integrated in the synthesis of state feedback control; the optimal control problem for the predictive state feedback control is reformulated in terms of linear matrix inequalities (LMIs). The both control theories are applied in the control of a bioreactor system with multi-model representation around different operating points and the obtained simulation results are compared. The advantage of the proposed PID approach is the simplicity of implementation in real-time processing.

It is well known that the biped walking gait is represented as a steady periodic gait. Investigation of such passive natural motion leads to different strategies of control; these strategies require a sharp mathematical model of the walking dynamics. One of the most used models is the Kajita's one. In this paper, we present an algorithm of controller's design used for the stabilisation of biped robot's gait. Using the Kajita's model as a reference, we include a Norm bounded uncertainties to ensure a more realistic numerical model. The modified model allows us to include constraints on both inputs, outputs and states. The synthesis of the dynamic controller relies on the use of predictive control theory (MPC) and the resolution of a convex optimisation problem with linear matrix inequalities (LMIs) at every sampling period. The generated control law allows a real-time walking robot even in rough ground or unknown environment.

The laboratory of a course is considered as a fundamental part of the education and training for engineers and scientists. Remote laboratories are increasingly finding their way into a variety of disciplines. Development and operation of remote laboratory work are specific process in several dimensions (technological, pedagogical, organizational, etc.). We present in this article some typical characteristics of this process. We will limit ourselves to consider the specificities related to communication between the remote user and the laboratory equipment. We will consider also the problems related to planning and access control and we will highlight aspects related to safety and the initialization of the state of a bench for a new experiment starting at distance.

Problem statement: This study discusses the robust stabilization of n orm bounded discrete switched systems. Approach: The proposed method is using the second Lyapunov approach and the poly-quadratic function concept. The stabilization conditions are written through linear matrix inequality relations. The control law is based on a static output feedback with the use of a switched observer. The synthesis conditions of the controlle r are written in the form of linear matrix inequali ties difficult to resolve by current numerical solvers. That's why relaxations are proposed to mitigate the pessimism of LMI conditions obtained. Results: The poly-quadratic Lyapunov approach provides a constructive way to tackle uncertainty in the switc hed framework. The feasibility is illustrated by th e example of discrete uncertain switched systems. Conclusion: With these results, the study of stability can be achieved for arbitrary switching laws, state -dependent, time dependent or generated by a controller. However, the implementation of the cont rol law is possible only if the switching status is well known in real time.