Rached Dhaouadi

Efficiency Optimization of a DSP-Based Standalone PV System Using Fuzzy Logic and Dual-MPPT Control

This paper presents a new digital control scheme for a standalone photovoltaic (PV) system using fuzzy-logic and a dual maximum power point tracking (MPPT) controller. The first MPPT controller is an astronomical two-axis sun tracker, which is designed to track the sun over both the azimuth and elevation angles and obtain maximum solar radiation at all times. The second MPPT algorithm controls the power converter between the PV panel and the load and implements a new fuzzy-logic (FLC)-based perturb and observe (P&O) scheme to keep the system power operating point at its maximum. The FLC-MPPT is based on a voltage control approach of the power converter with a discrete PI controller to adapt the duty cycle. The input reference voltage is adaptively perturbed with variable steps until the maximum power is reached. The proposed control scheme achieves stable operation in the entire region of the PV panel and eliminates therefore the resulting oscillations around the maximum power operating point. A 150-Watt prototype system is used with two TMS320F28335 eZdsp boards to validate the proposed control scheme performance.

A new dynamic model of hysteresis in harmonic drives

In this paper, we propose a new dynamic model to describe the hysteresis phenomenon in harmonic drives. The experimental observation of the dynamic torque-displacement relationship for a harmonic drive shows a hysteresis characteristic indicating the simultaneous presence of energy storage and energy dissipation mechanisms. To completely characterize these mechanisms and yet have a simple representation for control, we develop a new hysteresis model using the heredity concept of dynamic systems. This model represents the hysteresis phenomenon by a combination of a nonlinear stiffness component and a nonlinear damping component leading to a mathematically well-posed nonlinear differential equation. The parameters of the model are identified using optimization techniques. We present some important mathematical properties of the model that give insight into model behavior and thus establish a mathematical basis for control. Numerical simulations in comparison with experimental data using our Harmonic Drive Test Apparatus verify the accuracy of the proposed model to represent the complex hysteresis dynamics of harmonic drives.

Indirect adaptive tracking control of a nonholonomic mobile robot via neural networks

This paper presents the design and implementation of a novel adaptive trajectory tracking controller for a nonholonomic wheeled mobile robot (WMR) with unknown parameters and uncertain dynamics. The learning ability of neural networks is used to design a robust adaptive backstepping controller that does not require the knowledge of the robot dynamics. The kinematic controller gains are tuned on-line to minimize the velocity error and improve the trajectory tracking characteristics. The performance of the proposed control algorithm is verified and compared with the classical backstepping controller through simulation and experiments on a commercial mobile robot platform.

Adaptive control of a nonlinear dc motor drive using recurrent neural networks

A model-following adaptive control structure is proposed for the speed control of a nonlinear motor drive system and the compensation of the nonlinearities. A recurrent artificial neural network is used for the online modeling and control of the nonlinear motor drive system with high static and Coulomb friction. The neural network is first trained off-line to learn the inverse dynamics of the motor drive system using a modified form of the decoupled extended Kalman filter algorithm. It is shown that the recurrent neural network structure combined with the inverse model control approach allows an effective direct adaptive control of the motor drive system. The performance of this method is validated experimentally on a dc motor drive system using a standard personal computer. The results obtained confirm the excellent disturbance rejection and tracking performance properties of the system.

A fuzzy learning-Sliding mode controller for direct field-oriented induction machines

This paper presents a direct field-oriented induction motor drive system with two distinct features: a sliding mode voltage mode flux observer (SMVMFO) and a fuzzy model reference learning controller (FMRLC). The speed of the induction motor is regulated using an FMRLC, which does not require rigorous tuning of the controllers parameters. The rotor flux estimation for the direct field orientation (DFO) is realized by a newly proposed SMVMFO, which is insensitive to the stator resistance variation. The complete drive system is shown to have very good speed tracking performance, accurate flux estimation and field orientation, and high robustness to stator resistance variation, which has been a long-standing problem in the area of motor drives. Extensive simulations are presented for performance evaluation and validation of the proposed control scheme.

Smart home gateway for smart grid

This paper presents a smart home computing platform architecture that extends smart home network to be compatible for smart grid integration. The proposed hardware architecture along with a tailored software algorithm empowers utility companies and homeowners to communicate bi-directionally with home appliances via a public mobile network to monitor and manage power consumption of home appliances. The platform also enables homeowners to operate, monitor and control their home appliances locally via a control panel and remotely via their mobile phones.

ARF60 AUS-UAV modeling, system identification, guidance and control: Validation through hardware in the loop simulation

Automatic control of Unmanned Aerial Vehicles (UAVs) has been a growing area of research in aerospace technology for a long time, yet this area needs a great deal of development in order to get a reliable autonomous system capable of performing all types of maneuvers with high degree of stability and desired performance. In this paper, the development and building of a fully functioning test bed UAV platform is illustrated. The test-bed includes an enhanced hardware in the loop simulation “HILS” system to facilitate the development of the flight control system (FCS). Furthermore, the design of the guidance laws, autopilots implementation on the embedded system were integrated with the Hardware in the Loop Simulation (HILS). Finally, trajectory following results were demonstrated.

Robust Control of Elastic Drives Through Immersion and Invariance

This paper presents a new robust control method to suppress the torsional vibrations in flexible drive systems. The position control of a nonlinear two-mass-model system (2MM) is designed using the immersion and invariance (I&I) approach. First, appropriate mapping functions are derived to convert the actual nonlinear 2MM system into an equivalent reduced order system with rigid dynamics. This reduced order model is used as a target system to design a position controller, which is based on the standard proportional-integral-type control technique. Next, through I&I, the reduced order controller is applied to the nonlinear 2MM system to suppress the torsional vibrations and yield an overdamped response similar to the target system. The control law derivation and stability analysis of the target system are described and discussed. Simulations and experiments using a 2MM drive system are used to validate the proposed control methodology. The performance of the proposed I&I control scheme is also compared with the standard input/output feedback linearization technique.

Single input fuzzy controller (SFLC) based maximum power point tracking

This paper presents a single input fuzzy controller (SFLC) for adjusting the duty cycle of a photovoltaic (PV) charger to extract the maximum power out of a PV panel. The algorithm is based on maximum power point tracking (MPPT) and is compared with two conventional MPPT techniques, namely the Hill climbing method and the two input fuzzy controller method. The PV system design and modeling is described for a 150 watt standalone PV system with a buck converter charger. The performance of the proposed system is analyzed through numerical simulation and compared to the conventional methods.

Virtual SCADA Simulation System for Power Substation

With the recent development of industrial computing systems and human machine interface software packages, power systems research and development engineers ceased the opportunity to come up with virtual simulation tools to emulate the operation of power systems. The paper describes the development of a virtual SCADA (V-SCADA) system tool for testing and training purposes. Design engineers can test their system before the actual implementation. Fresh graduate engineers and senior students can be trained using this tool to visualize the pseudo real-time power substation equipment, operations procedures, and fault management. The virtual SCADA system is based on real experience of the authors in this field, which will help giving hands on field experience. Moreover, training on real system involves special permissions and testing procedures of a welcoming utility that can be done but for very few site visits.