Mounir Ayadi

PID-type fuzzy logic controller tuning based on particle swarm optimization

In this paper, a new PID-type fuzzy logic controller (FLC) tuning strategy is proposed using a particle swarm optimization (PSO) approach. In order to improve further the performance and robustness properties of the proposed PID-fuzzy approach, two self-tuning mechanisms are introduced. The scaling factors tuning problem of these PID-type FLC structures is formulated and systematically resolved, using a proposed constrained PSO algorithm. The case of an electrical DC drive benchmark is investigated, within a developed real-time framework, to illustrate the efficiency and superiority of the proposed PSO-based fuzzy control approaches. Simulation and experimental results show the advantages of the designed PSO-tuned PID-type FLC structures in terms of efficiency and robustness.

DESIGN OF FUZZY FLATNESS-BASED CONTROLLER FOR A DC DRIVE

In this paper, a combined approach associating the flatness principle to the fuzzy logic control techniques is proposed and applied to a DC drive supplied by an AC―DC power converter. The basic of this control strategy consists in planning a reference trajectory using the flatness property of linear systems. The desired trajectory of the output process will be expressed by the flat output reference trajectory. After the planning step, the tracking of the reference trajectory is ensured by a PID-type fuzzy controller. The output static disturbance rejection, the tracking performances robustness under plant parameters variation and the limitation of the control signal magnitude applied to the system are improved. The hardware and software control requirements are respectively developed and the proposed control strategy is illustrated by experimental trials in real-time framework.

Fuzzy fault-tolerant-predictive control for a class of nonlinear uncertain systems

ABSTRACT In this paper, a fault-tolerant fuzzy model-predictive control with the integral action method for a class of nonlinear uncertain systems is proposed. Nonlinear uncertain systems subject to actuators and/or sensors faults are represented by the Takagi–Sugeno (T-S) fuzzy model. The objective is to design a stable, robust and efficient fault-tolerant controller based on a T-S fuzzy observer with measurable premise variables. The proposed T-S fuzzy observer estimates state vector and faults. Based on Lyapunov theory, the trajectory tracking performances and the closed-loop system stability are analysed. The gains of the fuzzy observer and the pre-stabilized control law are obtained by solving linear matrix inequalities. Simulation results illustrate the robustness of the proposed controller with respect to uncertainties on an academic mathematical system.

A PID type fuzzy controller design with flatness-based planning trajectory for a DC drive

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 reference trajectory is ensured by a PID type fuzzy controller. Flatness and fuzzy logic lead to design a controller with high performance in terms of tracking and robustness. The rejection of a static disturbance on the output signal and the limitation of the control signal magnitude applied to the system will be improved while introducing a self-tuning controller parameters. The considered control approach is applied to a linear model of a DC motor supplied by an AC-DC power converter.

Indoor prediction of propagation using dominant path: Study and calibration

In this paper, we are interested in predicting signal level inside buildings. A new model is presented and described. The free space model and the two-ray model predict the received power as a deterministic function of distance. Recently, dominant path algorithm has introduced as an alternative thanks to its low computational time. It relies on the determination of the least attenuation path, the wave guiding effects and the loss interactions. In this paper, we extend the dominant path model to take into consideration the multi-floor case and the antenna pattern radiations. Our contribution consists in a specific method to solve these problems. Moreover, a method for the indoor dominant path calibration is introduced.

Quadratic stability and LMIs for tolerance to faults: Fuzzy model predictive control

In this paper, a fault tolerant Fuzzy-Model-Predictive Control (FMPC) with integral action method for a class of nonlinear systems is proposed. Nonlinear systems subject to actuators and/or sensors faults are described by Takagi-Sugeno (T-S) fuzzy model. The objective of this approach is to design a Fault Tolerant Controller (FTC). At each sampling time, MPC solves an optimization to achieve desired set points and control objectives. The feasibility of optimization problem provides the guarantee of the nominal asymptotic stability. However the optimization can be infeasible due to faults. This motivates the development of the proposed approach to recover feasibility with the respect of constraints imposed on control inputs and system states. State vector and faults are estimated by a T-S fuzzy observer. The gains of the fuzzy observer and the pre-stabilized control law are obtained by solving a Linear Matrix Inequality (LMI) derived from the Lyapunov theory. The proposed FTC strategy with Measurable Premise Variables (MPV) is applied to an academic example. Simulation results illustrate the validity of the proposed strategy and its application to FTC.

Fuzzy Model Predictive reconfigurable control for nonlinear systems subject to actuators faults

In this paper, a fault tolerant Fuzzy-Model-Predictive Control (FMPC) method for a class of nonlinear systems is proposed. Nonlinear systems subject to actuators faults are described by Takagi-Sugeno (T-S) fuzzy model. The objective of this approach is to design a Fault Tolerant Controller (FTC). At each sampling time, MPC solves an optimization to achieve desired set points and control objectives. The feasibility of optimization problem provides the guarantee of the nominal asymptotic stability. However the optimization can be infeasible due to faults. This motivates the development of methods to recover feasibility without violating constraints imposed on control inputs and system states. The investigation is mainly concerned with robustness of the MPC regarding actuators faults. The proposed FMPC with Unmeasurable Premise Variables (UPV) is compared to classical MPC and PI controller. The effectiveness and good performances of the proposed FTC strategy and its application to faults tolerance is illustrated by an academic example.

Flatness-based control of MIMO linear systems

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 when the trajectory is fixed, to determine the control signals to apply in open-loop without integrating any differential equations. The flat output is determined using two different approaches and trajectories are designed for system variables using the DGI filter. The simulation results point out the effectiveness of the developed method.

Real-time flatness-based control of a DC motor

In this paper, an approach of design and develop a real-time system around RISC microcontroller dedicated to the DC motor speed control is proposed. A polynomial RST controller based on the flatness property of linear systems is implemented with C/C++ embedded programming language. The flatness property is used in order to design a robust controller with high performance in terms of tracking. The contribution of this paper is to present the feasibility of the proposed controller which can be implemented in target. The simulation and experimental results indicate the effectiveness of the flatness-based polynomial controller in a real-time control framework.

Design of adaptive PID controllers based on adaptive Smith predictor for ultra-local model control

In this paper, an ultra-local model control approach based on adaptive Smith predictor is proposed. The design of adaptive PID controller takes into account the estimation of variable time delay which is compensated by the addition of an adaptive Smith predictor. The purpose of this paper is to solve the online estimation problem of time delay thanks to the proposed identification method of ultra-local model parameters. A performance comparison between the proposed control approach and the Smith predictor control with classical PID is carried out. The numerical simulation results of the thermal process study with severe constraints and operating conditions show the superiority of the adaptive PID controller. The robustness with respect to noises, disturbances and system parameter uncertainties of control approaches are highlighted.