Keywords: Control algorithms implementation, Control applications, Industrial control
Abstract: In semiconductor manufacturing, when Run-To-Run (RtR) control is used to compensate for variability of the process, one faces at least two main problems: The first is related to quality characteristics which is cannot be measured on a continuous scale due to either inherent or outside constraints. The second problem is related to the update of the control input which involves the recipe changes so as to reduce operational cost. In this paper, qualitative observations can be collected alternatively [1] to deal with Run-To-Run control and the proposed control law does not regulate the process input at every run. This is the case when the output evolves within a desired specification domain. Simulation results are presented to clarify this point and show the feasibility of the approach

Keywords: Control algorithms implementation, Fuzzy and neural systems, Embedded Systems
Abstract: The industrial sector requires not only the performance of systems in terms of quality, productivity and reliability, but also in terms of security. The implementation of Fuzzy Logic Controller (FLC) in Field Programmable Gate Array (FPGA) does not allow only the system reliability and reduce the controller conception life cycle, but also ensures a safety integrity level (SIL) which is required by the field of application and related to the control system architecture. Analysis of a safety fuzzy logic controller implemented in FPGA can be performed by different methods that are related to international standards (IEC 61508 [1] and ISA TR 84.0.0.2 [2]). This paper proposes the analysis of a safety fuzzy logic controller implemented in FPGA with 2oo3 architecture [3] using a qualitative and a quantitative analysis provided by these standards. The quantitative analysis is performed by the calculation of average probability of failure on demand (PFDavg) of safety related system to define its safety integrity level (SIL). The qualitative analysis is based on the Reliability Block Diagram method [4] and [5] and Fault Three Analysis [5] and [6].

Keywords: Control algorithms implementation, Linear and nonlinear systems
Abstract: Diabetes mellitus is a chronic disorder of carbohydrate metabolism due to relative or absolute insulin deficiency. Human body is very sensitive thus, it is essential for patients that the controller used in designing be robust to any kind of disturbances and Uncertain parameters. In this paper, Bergman’s minimal model is used as a base model in an effort to regulate efficiently glucose level using a synergetic control approach which is compared to application of second order sliding mode. These two proven robust control techniques can handle adequately uncertainties to a great extent through their invariant properties. Our contribution shows that synergetic methodology provides better performance. Obtaining system parameters exact values is unrealistic in most biological systems, therefore all parameters of the model will be considered uncertain. Parametric uncertainty will be exploited in developing a control scheme based on closed-loop feedback strategy. The behavior of the obtained controller is analyzed on its ability to track a normoglycemic in presence of disturbance and perturbed parameters. A comparative study of the application of the two techniques shows trough simulation results the prevalence of synergetic approach over second sliding mode, despite disturbances such as meal and exercise.

Keywords: Control applications
Abstract: This paper is a comparative study of classic IMC controller and a new adaptive IMC recurrent neural controller. The two controllers are implemented to control the DC machine speed. The IMC neural controller is based on two neural networks, the first is a recurrent neural network that replaces the DC machine model and the second is a neural network that replaces the internal model controller. The recurrent neural algorithm is developed and applied to estimate and control the DC machine speed under various types of disturbances in order to approve the controller robustness. Simulation results are provided to show the effectiveness of the proposed controller.

Keywords: Control applications, Estimations and identification, Linear and nonlinear systems
Abstract: This paper addresses the robust stabilization problem of a permanent magnet synchronous motor (PMSM). In order to optimize the speed-control performance of the PMSM system with different disturbances and uncertainties, Sliding mode control design for the PMSM is developed. We discuss in this paper howto achieve and maintain the prospective benefits of sliding mode control (SMC) methodologycombined with theLuenberger observer design for on-line estimation of speed and position. The proposedsensorlessnonlinear control is theoretically analyzed and assessed in simulation with satisfactory results.

Keywords: Control applications, Modeling of complex systems, Renewable Energy
Abstract: The paper proposes an extremal control method through the design of a RST controller for a step-down DC-DC Buck Converter fed by a BGSP - P225 PV array. The input voltage for the converter is kept at the photovoltaic panel’s maximum value by means of search algorithms for determining the Maximum Power Point. The algorithms used are Coggin’s algorithm for the single variable dependent model P(U) and the gradient algorithm is used for the P(I,U) model. The voltage value can after that be identified again for different iradiance and temperature conditions. This gives the converter an extremal input voltage. Next, a dynamic model has been determined for the closed loop control system, starting from the converter’s electrical components equations. A numerical RST controller used to achieve the performances of the system, was designed. A robustness analyses and correction has been performed for the RST polynomial control. The achieved performances of the DC-DC converter are validated through simulation by using the MATLAB / SIMULINK environment and the WinReg dedicated software. The novelty of the paper resides in the design of the RST controller for a photovoltaic panel and the robustness analysis.

Keywords: Fault detection and Diagnostics, Renewable Energy, Linear and nonlinear systems
Abstract: This paper aims firstly at contributing to the problematic of nonlinear Takagi-Sugeno (TS) approach for state and fault estimation with unmeasurable premise variables. The second objective is the application of this method on Fuel Cell Systems (FCSs). In order to achieve the estimated value of the fault, an observer based method is essential. The development and optimization of Fuel Cell parameter estimation in parallel with fault estimation is not treated in an exhaustive manner in literature. The estimation is based on a PI observer where the estimation error is bounded, having an additional corrective sliding terms. This eliminates the inconvenient generated by the Lipschitz constant.

Keywords: Linear and nonlinear systems, Fuzzy and neural systems
Abstract: In the last decades, the linear parameter varying (LPV) and Takagi-Sugeno (TS) fuzzy paradigms have been applied successfully to nonlinear systems. Despite the strong similarities between the two paradigms, they are considered different by the academic community. This paper discusses the analogies between the two paradigms when applied to the control of non-linear systems. After establishing a link between the modelling framework, the conditions under which the obtained controllers lead to equivalent control laws are presented. The discussion is completed by an application example which serves to illustrate the analogies and equivalences presented in the paper.

Keywords: Multivariable control, Fault detection and Diagnostics, Industrial control
Abstract: The reliability and functional safety of electrical drives is necessary for the use in safety-related systems such as electrical cars and aerospace applications. In this paper, a rotor flux oriented fault tolerant control scheme for induction machines with squirrel-cage rotor using the fault hiding approach is presented. Based on a proposed physical model of the induction machine in Takagi-Sugeno form, the robust observer and fault tolerant controller is systematically designed. To achieve robustness a Takagi-Sugeno observer combined with sliding mode that deals with unmeasurable premise variables and bounded uncertainties is presented. The stability of the error dynamics is ensured by linear matrix inequality conditions.

Keywords: Robust control and Hinfty control, Transportation systems, Linear and nonlinear systems
Abstract: This paper deals with the active control in vehicle to improve the safety and its stability. Vehicle model based a roll, yaw and lateral dynamics is used. The vehicle dynamics is represented by a LPV (Linear Parameter Varying) and the corresponding state-space model is affected by both polytopic and norm-bounded uncertainties. It is aimed to compute K, associated with the static output feedback, so as to place the set of all eigenvalues of the uncertain closed-loop state matrix Acl in a clustering region, denoted by D, while minimizing the effect of the disturbances on the system and ensuring the D-stability of Acl. This paper proposes an original technique, based on the resolution of LMI, to compute K. In order to highlight the performance of the proposed control algorithm, numerical simulations are performed.

Keywords: Modeling and simulation, Robust control and Hinfty control, Time-delay systems
Abstract: The purpose of this paper is to design a congestion controller for Networks TCP/IP Routers, while the available link bandwidth is modeled as a time-variant disturbance. Considering the new uncertain TCP flow model, a memoryless H∞ robust controller is designed to guarantee the stability and performance under time-varying network conditions. The controller parameters are obtained through standard linear matrix inequality techniques. A numerical example illustrates the effectiveness of our methodology, which advances the previous related works towards less conservative results.

Keywords: Time-delay systems, Control algorithms implementation, Optimal control
Abstract: In this paper, an approach of stabilization and control based on model reference scheme is proposed and analyzed for a class of unstable first order linear systems with time delay. This approach of design controller improved the performances of conventional Smith predictor compensator considerably, by incorporating an additional component of control law to generate a suitable input plant that satisfies the model reference behaviour. The controller parameters are designed under assumptions of asymptotic stability and model matching conditions. Specifically, a control law is designed to ensure tracking error convergence and to reduce the instability region. Therefore, it’s important to note that the method does not use the exact knowledge of the plant parameters and can guarantee an asymptotic stability with unknown bounded parameters system. Finally, a numerical example is presented to show applicability and performances of the proposed approach.

Keywords: Time-delay systems, Linear and nonlinear systems, Signal processing
Abstract: This paper investigates the problem of the delay dependent stability of neutral time-varying delay systems. By decomposing the delay interval into multiple equidistant subintervals, new Lyapunov- Krasovskii functionals are introduced on these inter- vals. Numerical example illustrate that the proposed method is effective and lead to less conservative re- sults.

Keywords: Time-delay systems, Multivariable control, Mathematical systems theory
Abstract: In this work, the stability and stabilization of fractional-order time-varying-delay systems modeled in state space are considered. First, based on the indirect Lyapunov and Lyapunov-Krasovskii approaches, we provide a sufficient condition for the asymptotic stability for the fractional-order time-varying-delay systems. Then, we give a sufficient condition guaranteeing the existence and the synthesis of pseudo-state feedback stabilizing controller in a Linear Matrix Inequality (LMI) formulation. Finally, a numerical example is given to illustrate the main results.

Keywords: Time-delay systems, Signal processing, Control of telecommunications systems
Abstract: The guaranteed cost control problem is studied in this paper for a class of uncertain linear discrete-time systems with two additive delays, which represent a general class of delay systems with strong application background in network based control systems. The uncertainty in the system is assumed to be norm-bounded. The problem is to design a control law such that the closed-loop system is robustly stable and the cost function value is not more than a specified upper bound for all admissible uncertainties. Two numerical examples are given to show that the proposed result can even produce a lower guaranteed cost than other result in the literature

Keywords: Fault detection and Diagnostics
Abstract: This paper considers a problem of fault detection, isolation and identification of its values in mechatronic systems described by nonlinear dynamic models. To solve this problem logic-dynamic approach and special feedback by residual signal is suggested. This approach consists of three main steps: replacing the initial nonlinear system by certain linear logic-dynamic system, obtaining the bank of linear logic-dynamic observers, and transforming these observes into the nonlinear ones. Logic-dynamic approach allows detecting and isolating faults in nonlinear dynamic systems by using the linear methods for diagnosis in nonlinear mechatronic systems. Feedback of special form introduced in the observers after the detection and isolation of faults. It is allowing to determine the value of faults in nonlinear systems with incomplete measurability of state vector. The results of mathematical simulation fully confirm the efficiency and high performance of the proposed method.

Keywords: Fault detection and Diagnostics, Control applications, Modeling and simulation
Abstract: This paper deals with the multi-model approach for the detection and diagnosis of faults for a DC motor maintenance in order to ensure an acceptable operation in spite of the presence of faults for a certain duration. Seven models corresponding to the healthy motor and seven faults were considered. Thus, a bank of eight controllers was designed by using an optimal control law. To detect and identify a fault, the response of the motor is compared with that of each preset model. This enables the supervisor at every moment to select the adequate controller corresponding to the minimal performance index. The obtained simulation results showed the validity of this approach.

Keywords: Fault detection and Diagnostics, Estimations and identification, Linear and nonlinear systems
Abstract: This paper, concerns the model-based prognosis approach. More precisely, it is about the use of the Bayesian filtering on the prognosis problem. The aim of the proposed approach is to identify the damage function parameter by using an Ensemble Kalman Filter (EnKF), then, estimate the Remaining Useful Life (RUL) by a probabilistic analysis of this damage trajectories. The relevance of the proposed approach is illustrated through the helicopter gearbox crack propagation.

Keywords: Fault detection and Diagnostics, Fuzzy and neural systems, Estimations and identification
Abstract: Abstract— This article is dedicated to the problem of H∞ finite time state and sensor fault estimation for T-S (Takagi-Sugeno) fuzzy systems with bounded input disturbance. Using the technique of descriptor systems a states and faults are estimated simultaneously. The idea is to design in finite time a sensor fault observer by taking in consideration the H∞ disturbance attenuation effect. Based on Lyapunov functions, new sufficient conditions are formulated in terms of LMIs (Linear Matrix Inequalities). An example is proposed to shows the efficiency.

Keywords: Fault detection and Diagnostics, Fuzzy and neural systems, Modeling and simulation
Abstract: Any diagnosis procedure should be rapid and efficiency. In the presence of the noise and unknown inputs, the diagnosis procedure could generate false alarms. This paper focuses in the fault detection, isolation and identification when a fault affected the sensors of a DC motor worked in disturbance environment. The chosen technique should take account the two issues: the noise and the unknown inputs. As a solution the Artificial Neural Network is adopted in order to generate a robust residuals and therefore to minimize the false alarms. A new ANN architecture is proposed to achieve this purpose. The simulation results proved the rapidity and the efficiency of the proposed procedure.

Keywords: Fault detection and Diagnostics, Robust control and Hinfty control
Abstract: This paper deals with the problem of sensor Fault Tolerant Tracking Control (FTTC) for Takagi-Sugeno (TS) fuzzy systems with unmeasurable premise variables. The proposed method uses a Fault Detection and Isolation (FDI) block based on a bank of observers to detect, identify and accommodate sensor faults. Stability of the closed-loop system are derived by Lyapunov theory and H_infty performance in the tracking context. Then, the fuzzy observer and the controller gains are simultaneously obtained by solving a set of Linear Matrix Inequalities (LMIs). Simulation results on two tank system are given to illustrate the effectiveness of the proposed FTTC strategy.

Keywords: Robust control and Hinfty control, Fuzzy and neural systems, Linear and nonlinear systems
Abstract: This paper considers the H∞ filtering for nonlinear discrete-time systems in the Takagi-Sugeno (T-S) fuzzy model. The approach is based on the fuzzy filters in finite-frequency domain. The objective is to propose a new design with sufficient condition via LMI formulations. Less conservative results are obtained by introducing slack matrices. This method provides extra degree of freedom in optimization of the H∞ performance. Three fuzzy filters are designed to deal with noises in low-, middle- and high-frequency domain (LF,MF,HF), respectively. The efficiency of the proposed approach is shown be an example.

Keywords: Robust control and Hinfty control, Linear and nonlinear systems
Abstract: Abstract— This work deals with problem of fuzzy control stabilization for wind turbine generator with parameter uncertainties. Using Linear Matrix inequality (LMI) combined with a judicious of the famous Young relation, a new methodology of stability is proposed, which can be solved by using LMI optimization techniques . Hence the control scheme is based on a PDC structure, a fuzzy observer and a H∞ standard command to attenuate the external disturbances of the wind speed. To illustrate the proposed method and guarantee the performance the simulation on a dynamic model of the wind energy conversion

systems (WECS) is given.

Keywords: Robust control and Hinfty control, Real time systems, Optimal control
Abstract: This paper is concerned with the reduceorder H∞ filtering problem for uncertain differential linear repetitive processes (LRPs). By establishing a novel version of bounded real lemma, the polynomially parameter-dependent approach is developed to solve the addressed filtering problem, with a new linear matrix inequality condition obtained for the existence of desired H∞ reduce-order filter. Finally, illustrative example are presented to show the applicability of the proposed method.

Keywords: Stochastic control, Robust control and Hinfty control, Signal processing
Abstract: This paper tackles the H∞ filtering problem for 2-D discrete stochastic systems. The approach is based on the Fornasini-Marchisini (FM) model. The objective is to propose a new design with sufficient condition via LMI formulations. Less conservative results are obtained by introducing additional free parameters by using the projection Lemma. This method provides extra degree of freedom in optimization of the H∞ performance. The efficiency of the proposed approach is shown be several examples.

Keywords: Autonomous Ssystems, Intelligent and AI based control, Optimization
Abstract: In this paper an evolutionary strategy based on genetic algorithms are presented to optimize a hybrid Fuzzy- PID control system of mini-UAV (unmanned aerial vehicle) quad-rotor. This control system consists of two Mamdani-type fuzzy controllers for both longitudinal and lateral modes of the quad-rotor and four PID controllers are also used to control the roll, pitch, yaw angles and the altitude. Genetic algorithms are used to optimize the parameters value of the proportional, integration and derivation gains of the four PID controllers. The designed control system and the optimization phase using genetic algorithms are tested via simulation where it shows that the designed control system using genetic algorithms exhibit good performance.

Keywords: Linear and nonlinear systems, Autonomous Ssystems
Abstract: In this paper, the problem of robust stabilization of a class of time-delay nonlinear systems with Markovian jump with a triangular structure is studied. Based on backstepping method, we prove that the closed system is almost surely asymptotically stable. The controller and the associated Lyapunov function is independent of the generator of the Markov process.

Keywords: Linear and nonlinear systems, Time-delay systems, Mathematical systems theory
Abstract: The stabilization problem for continuous-time fractional linear systems with multiple delays together with the additional condition of non negativity of the states is solved. The obtained results are based on a direct Lyapunov-Krasovskii function. In particular, the synthesis of state-feedback controllers is obtained by giving conditions in terms of Linear Programs. llustrative example is provided to show the usefulness of the results.

Keywords: Mathematical systems theory
Abstract: The inverse procedure method is a technique which is relevant to a pole placement problem and state feedback control design with asymmetrical constraints on control inputs. The specified closed-loop poles represent the poles of a matrix H which should be suitably chosen to guarantee that the inverse procedure method will work. The success of the method is related to a singularity problem of some matrix which depends on the solution of a Sylvester equation and on the generalized eigenspace associated to the stable part of the system. In this paper, we propose a method to build the matrix H in order to solve the singularity problem.

Keywords: Robotics, Fuzzy and neural systems, Autonomous Ssystems
Abstract: In this paper, we have treated a mobile robot command problem using a Hierarchical Fuzzy Logic Controller HFLC. A new approach based on HFLC is presented in this paper to avoid collisions with obstacles. In fact, HFLC consists of a number of low-dimensional standard fuzzy systems connected in a hierarchical fashion. Hence, it can provide a good candidate for solving high-dimensional problems. Simulation results show that the used method is powerful and effective.