Multiple distribution static synchronous compensators for distribution feeder voltage support

The potential of multiple distribution static synchronous compensators (DSTATCOMs) to improve the voltage profile of radial distribution networks has been reported in the literature by few authors. However, the operation of multiple DSTATCOMs across a distribution feeder may introduce control interactions and/or voltage instability. This study proposes a control scheme that alleviates interactions among controllers and enhances proper reactive power sharing among DSTATCOMs. A generalised mathematical model is presented to analyse the interactions among any number of DSTATCOMs in the network. The criterion for controller design is developed by conducting eigenvalue analysis on this mathematical model. The proposed control scheme is tested in time domain on a sample radial distribution feeder installed with multiple DSTATCOMs and test results are presented.

System identification, estimation and control for a cost effective open-source quadcopter

This paper describes system identification, estimation and control of translational motion and heading angle for a cost effective open-source quadcopter — the MikroKopter. The dynamics of its built-in sensors, roll and pitch attitude controller, and system latencies are determined and used to design a computationally inexpensive multi-rate velocity estimator that fuses data from the built-in inertial sensors and a low-rate onboard laser range finder. Control is performed using a nested loop structure that is also computationally inexpensive and incorporates different sensors. Experimental results for the estimator and closed-loop positioning are presented and compared with ground truth from a motion capture system.

A 3D collision avoidance strategy for UAVs in a non-cooperative environment

This paper presents a feasible 3D collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs). The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D. The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided. The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading. A switching controller is designed to achieve the spatial collision avoidance strategy. Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs.

Nonlinear H_infinity control of UAVs for collision avoidance in gusty environments

This paper proposes a nonlinear H_infinity controller for stabilization of velocities, attitudes and angular rates of a fixed-wing unmanned aerial vehicle (UAV) in a windy environment. The suggested controller aims to achieve a steady-state flight condition in the presence of wind gusts such that the host UAV can be maneuvered to avoid collision with other UAVs during cruise flight with safety guarantees. This paper begins with building a proper model capturing flight aerodynamics of UAVs. Then a nonlinear controller is developed with gust attenuation and rapid response properties. Simulations are conducted for the Shadow UAV to verify performance of the proposed con- troller. Comparative studies with the proportional-integral-derivative (PID) controllers demonstrate that the proposed controller exhibits great performance improvement in a gusty environment, making it suitable for integration into the design of flight control systems for cruise flight of UAVs.

Rough fuzzy control of SVC for power system stability enhancement

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

Calculation of volume from crank angle using reconfigurable hardware

Fast calculation of quantities such as in-cylinder volume and indicated power is important in internal combustion engine research. Multiple channels of data including crank angle and pressure were collected for this purpose using a fully instrumented diesel engine research facility. Currently, existing methods use software to post-process the data, first calculating volume from crank angle, then calculating the indicated work and indicated power from the area enclosed by the pressure-volume indicator diagram. Instead, this work investigates the feasibility of achieving real-time calculation of volume and power via hardware implementation on Field Programmable Gate Arrays (FPGAs). Alternative hardware implementations were investigated using lookup tables, Taylor series methods or the CORDIC (CoOrdinate Rotation DIgital Computer) algorithm to compute the trigonometric operations in the crank angle to volume calculation, and the CORDIC algorithm was found to use the least amount of resources. Simulation of the hardware based implementation showed that the error in the volume and indicated power is less than 0.1%.

Adaption and use of a compressible flow code for turbomachinery design

The present paper presents and discusses the use of dierent codes regarding the numerical simulation of a radial-in ow turbine. A radial-in ow turbine test case was selected from published literature [1] and commercial codes (Fluent and CFX) were used to perform the steady-state numerical simulations. An in-house compressible- ow simulation code, Eilmer3 [2] was also adapted in order to make it suitable to perform turbomachinery simulations and preliminary results are presented and discussed. The code itself as well as its adaptation, comprising the addition of terms for the rotating frame of reference, programmable boundary conditions for periodic boundaries and a mixing plane interface between the rotating and non-rotating blocks are also discussed. Several cases with dierent orders of complexity in terms of geometry were considered and the results were compared across the dierent codes. The agreement between these results and published data is also discussed.

Computational experiments involving population size for FPGA-based implementation of a GA for the TSP

The feasibility of using an in-hardware implementation of a genetic algorithm (GA) to solve the computationally expensive travelling salesman problem (TSP) is explored, especially in regard to hardware resource requirements for problem and population sizes. We investigate via numerical experiments whether a small population size might prove sufficient to obtain reasonable quality solutions for the TSP, thereby permitting relatively resource efficient hardware implementation on field programmable gate arrays (FPGAs). Software experiments on two TSP benchmarks involving 48 and 532 cities were used to explore the extent to which population size can be reduced without compromising solution quality, and results show that a GA allowed to run for a large number of generations with a smaller population size can yield solutions of comparable quality to those obtained using a larger population. This finding is then used to investigate feasible problem sizes on a targeted Virtex-7 vx485T-2 FPGA platform via exploration of hardware resource requirements for memory and data flow operations.

An evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles with tactical and kinematic constraints

This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

Calculation of engine parameters using reconfigurable hardware

The feasibility of real-time calculation of parameters for an internal combustion engine via reconfigurable hardware implementation is investigated as an alternative to software computation. A detailed in-hardware field programmable gate array (FPGA)-based design is developed and evaluated using input crank angle and in-cylinder pressure data from fully instrumented diesel engines in the QUT Biofuel Engine Research Facility (BERF). Results indicate the feasibility of employing a hardware-based implementation for real-time processing for speeds comparable to the data sampling rate currently used in the facility, with acceptably low level of discrepancies between hardware and software-based calculation of key engine parameters.

Advanced battery storage control for an autonomous microgrid

A new control method for battery storage to maintain acceptable voltage profile in autonomous microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.

Power system sensitivity analysis considering induction motor loads

Power system operation and planning are facing increasing uncertainties especially with the deregulation process and increasing demand for power. Probabilistic power system stability assessment and probabilistic power system planning have been identified by EPRI as one of the important trends in power system operations and planning. Probabilistic small signal stability assessment studies the impact of system parameter uncertainties on system small disturbance stability characteristics. Researches in this area have covered many uncertainties factors such as controller parameter uncertainties and generation uncertainties. One of the most important factors in power system stability assessment is load dynamics. In this paper, composite load model is used to consider the uncertainties from load parameter uncertainties impact on system small signal stability characteristics. The results provide useful insight into the significant stability impact brought to the system by load dynamics. They can be used to help system operators in system operation and planning analysis.

TS-fuzzy controlled DFIG based wind energy conversion system

This paper focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the active power and the DC capacitor voltage control of the Doubly Fed Induction Generator (DFIG) based wind generator. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings of the DFIG system is also investigated. The results of the time domain simulation studies are presented to elucidate the effectiveness of the TS-fuzzy controller compared with conventional PI controller in the DFIG system. The proposed TS-fuzzy controller can improve the fault ride through capability of DFIG compared to the conventional PI controller

Active and reactive power control of synchronous generator for the realization of a virtual power plant

This paper presents a novel power control strategy that decouples the active and reactive power for a synchronous generator connected to a power network. The proposed control paradigm considers the capacitance of the transmission line along with its resistance and reactance as-well. Moreover the proposed controller takes into account all cases of R-X relationships, thus allowing it to function in Virtual Power Plant (VPP) structures which operate at both medium voltage (MV) and low voltage (LV) levels. The independent control of active and reactive power is achieved through rotational transformations of the terminal voltages and currents at the synchronous generator's output. This paper details the control technique by first presenting the mathematical and electrical network analysis of the methodology and then successfully implementing the control using MATLAB-SIMULINK simulation.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.