Primary voltage control of a single-phase inverter using linear quadratic regulator with integrator

This paper proposes a linear quadratic regulator with integral action, ensuring fast dynamic response and resisting capability of voltage deviation from instantaneous reference grid voltage, to control the inverter voltage that can also be used in a microgrid. The proposed control strategy is based on a linear quadratic regulator, minimizing the cost function of the system, with integral action used to impede voltage degradation from a reference voltage for outside disturbances of the system, such as abrupt load change. The combined integral term assists to recover the voltage difference between grid and reference grid voltage. The validity of the proposed controller has been tested with linear and non-linear loads under various conditions. In both cases, the effectiveness of the controller has been proved. The result of the proposed controller is good to track the instantaneous reference grid voltage.

Robust optimal motion cueing algorithm based on the linear quadratic regulator method and a genetic algorithm

The aim of this paper is to design and develop an optimal motion cueing algorithm (MCA) based on the genetic algorithm (GA) that can generate high-fidelity motions within the motion simulator's physical limitations. Both, angular velocity and linear acceleration are adopted as the inputs to the MCA for producing the higher order optimal washout filter. The linear quadratic regulator (LQR) method is used to constrain the human perception error between the real and simulated driving tasks. To develop the optimal MCA, the latest mathematical models of the vestibular system and simulator motion are taken into account. A reference frame with the center of rotation at the driver's head to eliminate false motion cues caused by rotation of the simulator to the translational motion of the driver's head as well as to reduce the workspace displacement is employed. To improve the developed LQR-based optimal MCA, a new strategy based on optimal control theory and the GA is devised. The objective is to reproduce a signal that can follow closely the reference signal and avoid false motion cues by adjusting the parameters from the obtained LQR-based optimal washout filter. This is achieved by taking a series of factors into account, which include the vestibular sensation error between the real and simulated cases, the main dynamic limitations, the human threshold limiter in tilt coordination, the cross correlation coefficient, and the human sensation error fluctuation. It is worth pointing out that other related investigations in the literature normally do not consider the effects of these factors. The proposed optimized MCA based on the GA is implemented using the MATLAB/Simulink software. The results show the effectiveness of the proposed GA-based method in enhancing human sensation, maximizing the reference shape tracking, and reducing the workspace usage.

Identifying the predictors of employee health and satisfaction in an NPM environment : testing a comprehensive and non-linear demand-control-support model

The Demand-Control-Support (DCS) model is investigated in the context of police officers working within an organization that has relatively widespread uptake of New Public Management (NPM) practices. A survey of 479 police officers from two geographic regions was undertaken and the results indicate that the DCS offers a simple, yet powerful, framework for identifying the conditions to be managed in an NPM-oriented environment. Job control and work-based support predict all four target variables, strengthening the view that decision-making latitude and support from supervisors and colleagues represent critical resources for promoting the well-being, satisfaction and commitment of public sector employees.

Terminal approach navigation for autonomous robots in a sensory network

In this paper we present a technique based on precision guidance approach for the sensor delivery and reception problem between two mobile robots. A slave robot is employed to collect sensors and slack them on a tray carried by the mobile master robot. We define the terminal attitude of the slave robot with respect to the master and present a LQR control approach to solving the problem of achieving a desired terminal approach angle necessary for the appropriate sensor delivery. The approach criteria is defined in terms of both minimizing the miss distance and controlling the slave robot's body attitude with respect to the master robot at the terminal point.

A control methodology for DFIG type wind turbines connected to distribution networks

This paper proposes a decentralised controller design for doubly-fed induction generators (DFIGs) to enhance dynamic performance of distribution networks. The change in the output power due to the variable nature of wind is considered as an uncertain term in the design algorithm. In addition, the interconnection effect of the other subsystems are considered in the design process. The H norm of the uncertain system is found out and simultaneous output-feedback linear controllers are designed based controller is verified on a 16 bus distribution test system for severe disturbances. Simulation results indicate that the designed controller is robust against uncertainties in operating conditions

D-STATCOM control in distribution networks with composite loads to ensure grid code compatible performance of photovoltaic generators

This paper proposes an optimal linear quadratic Gaussian (LQG) controller for D-STATCOM to improve the dynamic performance of distribution networks with photovoltaic generators. The controller is designed based on the H∞ norm of the uncertain system. The change in system model due to the variation of load compositions in the composite load is considered as an uncertain term in the design algorithm. The performance of the designed controller is demonstrated on a widely used test system. Simulation results indicate that the proposed controller can be a potential solution for improving the voltage stability of distribution networks.

Enhancement of transient stability limit and voltage regulation with dynamic loads using robust excitation control

In stressed power systems with large induction machine component, there exist undamped electromechanical modes and unstable montonic voltage modes. This article proposes a sequential design of an excitation controller and a power system stabiliser (PSS) to stabilise the system. The operating region, with induction machines in stressed power systems, is often not captured using a linearisation around an operating point, and to alleviate this situation a robust controller is designed which guaruntees stable operation in a large region of operation. A minimax linear quadratic Gaussian design is used for the design of the supplementary control to automatic voltage regulators, and a classical PSS structure is used to damp electromechanical oscillations. The novelty of this work is in proposing a method to capture the unmodelled nonlinear dynamics as uncertainty in the design of the robust controller. Tight bounds on the uncertainty are obtained using this method which enables high-performance controllers. An IEEE benchmark test system has been used to demonstrate the performance of the designed controller

Swing-up and stability control of Wheeled Acrobot (WAcrobot)

In this paper the Wheeled Acrobot (WAcrobot), a novel mechanical system consisting of an underactuated double inverted pendulum robot (Acrobot) equipped with actuated wheels, is described. This underactuated and highly nonlinear system has potential applications in mobile manipulators and leg-wheeled robots. It is also a testbed for researchers studying advanced methodologies in nonlinear control. The control system for swing-up of the WAcrobot based on collocated or non-collocated feedback linearisation to linearise the active or passive Degree Of Freedom (DOF) followed by Linear Quadratic Regulator (LQR) to stabilise the robot is discussed. The effectiveness of the proposed scheme is validated with numerical simulation. The numerical results are visualised by graphical simulation to demonstrate the correlation between the numerical results and the WAcrobot physical response.

Active power control in an islanded microgrid using DC link voltage status

This paper proposes a power balancing strategy for dispatchable and non-dispatchable sources in an islanded microgrid. This control method enables energy storage system that employs a voltage-band at a dc busbar to maintain grid voltage stability for short period disturbances in a network. This voltage-band, applied to obtain maximum benefit from the storage system, depends on a storage capacity feature to avoid voltage limit violation. In addition, a linear quadratic regulator is employed as a voltage controller to track the reference grid voltage that is obtained from the proposed P/V droop control strategy. In the proposed control method, a long-term energy storage element, such as a battery, also can be used to regulate voltage and deliver insufficient power in a microgrid. It is concluded that the proposed control method exhibits an effective result in voltage and power issue during transient.

Stability enhancement of DFIG wind turbine using LQR pitch control over rated wind speed

A novel pitch control design method is proposed for the doubly fed induction generator (DFIG) wind turbine (WT) using linear quadratic regulator (LQR). A seven-order model represents the DFIG WT which is linearized by truncated Taylor series expansion. A systematic approach is adopted to determine the weighting matrices in LQR design for the optimal solution. Simulations have been carried out to compare the performance of the proposed LQR pitch control method against a PI pitch control for small and large disturbances. It is shown that the proposed control method enhances low-voltage ride-through capability and improves system damping under large disturbances.

Using geometric shape variations to create an inverse model for a sheet metal process

The output of the sheet metal forming process is subject to much variation. This paper develops a method to measure shape variation in channel forming and relate this back to the corresponding process parameter levels of the manufacturing set-up to create an inverse model. The shape variation in the channels is measured using a modified form of the point distribution model (also known as the active shape model). This means that channels can be represented by a weighting vector of minimal linear dimension that contains all the shape variation information from the average formed channel.

The inverse models were created using classifiers that related the weighting vectors to the process parameter levels for the blank holder force (BHF), die radii (DR) and tool gap (TG) of the parameters. Several classifiers were tested: linear, quadratic Gaussian and artificial neural networks. The quadratic Gaussian classifiers were the most accurate and the most consistent type of classifier over all the parameters.

Design of a norm-bounded LQG controller for power distribution networks with distributed generation

This paper presents a novel excitation control design to improve the voltage profile of power distribution networks with distributed generation and induction motor loads. The system is linearised by perturbation technique. Controller is designed using the linear-quadratic-Gaussian (LQG) controller synthesis method. The LQG controller is addressed with norm-bounded uncertainty. The approach considered in this paper is to find the smallest upper bound on the H∞ norm of the uncertain system and to design an optimal controller based on this bound. The design method requires the solution of a linear matrix inequality. The performance of the controller is tested on a benchmark power distribution system. Simulation results show that the proposed controller provides impressive oscillation damping compared to the conventional excitation controller.