Solving Harmonics Elimination Problem in Three-Phase Voltage controlled Inverter using Artificial Neural Networks

A novel concept of application of Artificial Neural Networks (ANN) for generating the optimum switching functions for the voltage and harmonic control of DC-to-AC bridge inverters is presented. In many research, the neural network is trained off line using the desired switching angles given by the classic harmonic elimination strategy to any value of the modulation index. This limits the utilisability and the precision in other modulation index values. In order to avoid this problem, a new training algorithm is developed without using the desired switching angles but it uses the desired solution of the elimination harmonic equation, i.e. first harmonics are equal to zero. Theoretical analysis of the proposed solving algorithm with neural networks is provided, and simulation results are given to show the high performance and technical advantages of the developed modulator

Adaptive observer-based fault estimation for a class of Lipschitz nonlinear systems

Fault input channels represent a major challenge for observer design for fault estimation. Most works in this field assume that faults enter in such a way that the transfer functions between these faults and a number of measured outputs are strictly positive real (SPR), that is, the observer matching condition is satisfied. This paper presents a systematic approach to adaptive observer design for joint estimation of the state and faults when the SPR requirement is not verified. The proposed method deals with a class of Lipschitz nonlinear systems subjected to piecewise constant multiplicative faults. The novelty of the proposed approach is that it uses a rank condition similar to the observer matching condition to construct the adaptation law used to obtain fault estimates. The problem of finding the adaptive observer matrices is formulated as a Linear Matrix Inequality (LMI) optimization problem. The proposed scheme is tested on the nonlinear model of a single link flexible joint robot system

Design and experimentation of a self-tuning PID control applied to the 3DOF helicopter

The paper presents design and experimental validation of a stable self-tuning PID controller for three degrees of freedom (3-DOF) helicopter. At first, it is proposed a self-tuned proportional-integral-derivative (PID) controller for a class of uncertain second order multiinput multi-output nonlinear dynamic systems to which the 3-DOF helicopter dynamic model belongs. Within this scheme, the PID controller is employed to approximate unknown ideal controller that can achieve control objectives. PID controller gains are the adjustable parameters and they are updated online with a stable adaptation mechanism designed to minimize the error between the unknown ideal controller and the used by PID controller. The stability analysis of the closed-loop system is performed using Lyapunov approach. It is proven that all signals in the closed-loop system are uniformly ultimately bounded. The proposed approach can be regarded as a simple and effective model-free control since the mathematical model of the system is assumed unknown. Experimental results are presented to verify the effectiveness of the proposed controller

Fuzzy control for Electric Power Steering System with assist motor current input constraints

Friction and disturbances of the road are the main sources of nonlinearity in the Electric Power Steering (EPS) System. Consequently, conventional linear controllers design based on a simplified linear model of the EPS system will result in poor dynamic performance or system instability. On the other hand, a brush-type DC motor is more used in EPS control with an input current that is limited in practice. The control laws designed without taking into account the saturation effect may have undesirable consequences on the system stability. In this paper, a Takagi-Sugeno (T-S) fuzzy is used to represent the nonlinear behavior of an EPS system, and stabilization conditions for nonlinear EPS system with both constrained and saturated control input cases are proposed in terms of linear matrix inequalities (LMI). Simulation results show that both the saturated and constrained controls can stabilize the resulting closed-loop EPS system and provide a stable driving in the presence of nonlinear friction, disturbance of the road and actuator saturation

Fuzzy Control of DC-DC Converters with Input Constraint

This paper proposes a method for designing fuzzy control of DC-DC converters under actuator saturation. Because linear control design methods do not take into account the nonlinearity of the system, a T-S fuzzy model and a controller design approach is used. The designed control not only handles the external disturbance but also the saturation of duty cycle. The input constraint is first transformed into a symmetric saturation which is represented by a polytopic model. Stabilization conditions for the state feedback system of DC-DC converters under actuator saturation are established using the Lyapunov approach. The proposed method has been compared and verified with a simulation example

Precision Glycodendrimers for DC-SIGN Targeting**

Multivalent ligands of the C-type lectin receptor DC-SIGN have emerged as effective antiadhesive agents against various pathogens. Some years ago, we described a hexavalent DC-SIGN ligand, Polyman-26, designed to bridge two of the four binding sites displayed by the receptor. In this work, we present our efforts to accomplish simultaneous coordination of all four carbohydrate binding sites of DC-SIGN through the synthesis of cross-shaped glycodendrimers. The tailored rigid scaffold allowed multivalent presentation of glycomimetics in a spatially defined fashion, while providing good water solubility to the constructs. Evaluation of the biological activity by SPR assays revealed strong binding avidity towards DC-SIGN and increased selectivity over langerin. Inhibition of DC-SIGN binding to SARS-CoV-2 spike protein and of DC-SIGN mediated Ebola virus trans-infection testifies for the glycodendrimers potential application in infection diseases. The tetravalent platform described here is easily accessible and can be used in modular fashion with different ligands, thus lending itself to multiple applications