A. El Hajjaji

Bio: A. El Hajjaji is an academic researcher from University of Picardie Jules Verne. The author has contributed to research in topics: Fuzzy control system & Fuzzy logic. The author has an hindex of 18, co-authored 107 publications receiving 1262 citations.

Observer based (Q,V,R)-α-dissipative control for TS fuzzy descriptor systems with time delay

Abstract: This paper is concerned with the design of ( Q , V , R ) - α - dissipative control for continuous TS fuzzy descriptor systems with unmeasurable states and time-varying delay. Our attention is focused on the design of the fuzzy controller and the fuzzy observer such that the closed loop fuzzy descriptor system with time delay is not only regular, impulse-free and stable but also ( Q , V , R ) - α - dissipative . By using the matrix decoupling technique, new delay dependent stabilization conditions are presented in terms of Linear Matrix Inequalities (LMI). As a particular case, observer-based H ∞ control is deduced from the proposed observer-based dissipative control result. Finally, a numerical example is given to demonstrate the effectiveness of our results.

Road curvature estimation for vehicle lane departure detection using a robust Takagi–Sugeno fuzzy observer

Abstract: In this paper, a lane departure detection method is studied and evaluated via a professional vehicle dynamics software. Based on a robust fuzzy observer designed with unmeasurable premise variables with unknown inputs, the road curvature is estimated and compared with the vehicle trajectory curvature. The difference between the two curvatures is used by the proposed algorithm as the first driving risk indicator. To reduce false alarms and take into account the driver corrections, a second driving risk indicator is considered, which is based on the steering dynamics, and it gives the time to the lane keeping. The used nonlinear model deduced from the vehicle lateral dynamics and a vision system is represented by an uncertain Takagi–Sugeno fuzzy model. Taking into account the unmeasured variables, an unknown input fuzzy observer is then proposed. Synthesis conditions of the proposed fuzzy observer are formulated in terms of linear matrix inequalities using Lyapunov method. The proposed approach is evaluated...

Improved fuzzy sliding mode control for a class of MIMO nonlinear uncertain and perturbed systems

Abstract: In this paper, a stable adaptive fuzzy sliding mode based tracking control is developed for a class of nonlinear MIMO systems that are represented by input output models involving system uncertainties and external disturbances. The main contribution of the proposed method is that the structure of the controller system is partially unknown and does not require the bounds of uncertainties and disturbance to be known. First, a fuzzy logic system is designed to estimate the unknown function. Secondly, in order to eliminate the chattering phenomenon brought by the conventional variable structure control, the signum function is replaced by an adaptive Proportional Derivative (PD) term in the proposed approach. All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis, so that convergence to zero of tracking errors and boudedness of all signals in the closed-loop system can be guaranteed. Finally, a mass-spring-damper system is simulated to demonstrate the validity and the effectiveness of the proposed controller.

Observer-based robust fuzzy control for vehicle lateral dynamics

Abstract: In this paper, the robust fuzzy control for four wheels steering (4WS) vehicle dynamics is studied via a Takagi-Sugeno (T-S) uncertain fuzzy model when the road adhesion conditions change and the sideslip angle is unavailable for measurement. After giving the nonlinear model of the vehicle, its representation by a T-S uncertain fuzzy model is discussed. Next, based on the uncertain fuzzy model of the 4WS Vehicle a fuzzy controller and a fuzzy observer are developed. The closed loop stability conditions of a vehicle with the fuzzy controller and the observer are parameterized in terms of linear matrix inequality (LMI) problem which can be solved very efficiently using the convex optimization techniques. The numerical simulation of the vehicle handling with and without the use of the developed observer and controller has been carried out. The simulation results obtained indicate that considerable improvements in the vehicle handling can be achieved whenever the vehicle is governed by the proposed fuzzy observer and fuzzy controller.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

Abstract: This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

Applications of fuzzy logic in renewable energy systems – A review

Abstract: In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates.

Tracking control of unicycle-modeled mobile robots using a saturation feedback controller

Abstract: The tracking control problem with saturation constraint for a class of unicycle-modeled mobile robots is formulated and solved using the backstepping technique and the idea from the LaSalle's invariance principle. A global result is presented in which several constraints on the linear and the angular velocities of the mobile robot from recent literature are dropped. The proposed controller can simultaneously solve both the tracking and regulation problems of a unicycle-modeled mobile robot. With the proposed control laws, the robot can globally follow any path specified by a straight line, a circle or a path approaching the origin using a single controller. As demonstrated, the circular and parallel parking control problem are solved using the proposed controller. Computer simulations are presented which confirm the effectiveness of the proposed tracking control law. Practical experimental results validate the simulations.