Controller structure and design of firing angle controllers for (unit connected) HVDC systems

This paper investigates the control of a HVDC link, fed from an AC source through a controlled rectifier and feeding an AC line through a controlled inverter. The overall objective is to maintain maximum possible link voltage at the inverter while regulating the link current. In this paper the practical feedback design issues are investigated with a view of obtaining simple, robust designs that are easy to evaluate for safety and operability. The investigations are applicable to back-to-back links used for frequency decoupling and to long DC lines. The design issues discussed include: (i) a review of overall system dynamics to establish the time scale of different feedback loops and to highlight feedback design issues; (ii) the concept of using the inverter firing angle control to regulate link current when the rectifier firing angle controller saturates; and (iii) the design issues for the individual controllers including robust design for varying line conditions and the trade-off between controller complexity and the reduction of nonlinearity and disturbance effects

Anti-wind-up designs for dynamic positioning of marine vehicles with control allocation

This paper presents a framework for the design of a joint motion controller and a control allocation strategy for dynamic positioning of marine vehicles. The key aspects of the proposed designs are a systematic approach to deal with actuator saturation and to inform the motion controller about saturation. The proposed system uses a mapping that translates the actuator constraint sets into constraint sets at the motion controller level. Hence, while the motion controller addresses the constraints, the control allocation algorithm can solve an unconstrained optimisation problem. The constrained control design is approached using a multivariable anti-wind-up strategy for strictly proper controllers. This is applicable to the implementation of PI and PID type of motion controllers.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

A robust controller design method for feedback substitution schemes using genetic algorithms

Controllers for feedback substitution schemes demonstrate a trade-off between noise power gain and normalized response time. Using as an example the design of a controller for a radiometric transduction process subjected to arbitrary noise power gain and robustness constraints, a Pareto-front of optimal controller solutions fulfilling a range of time-domain design objectives can be derived. In this work, we consider designs using a loop shaping design procedure (LSDP). The approach uses linear matrix inequalities to specify a range of objectives and a genetic algorithm (GA) to perform a multi-objective optimization for the controller weights (MOGA). A clonal selection algorithm is used to further provide a directed search of the GA towards the Pareto front. We demonstrate that with the proposed methodology, it is possible to design higher order controllers with superior performance in terms of response time, noise power gain and robustness.

A finite-time stability theorem of stochastic nonlinear systems and stabilization designs

This paper focuses on the finite-time stability and stabilization designs of stochastic nonlinear systems. We first present and discuss a definition on the finite-time stability in probability of stochastic nonlinear systems, then we introduce a stochastic Lyapunov theorem on the finite-time stability, which has been established by Yin et al. We also employ this theorem to design a continuous state feedback controller that makes a class of stochastic nonlinear systems to be stable in finite time. An example and a simulation are given to illustrate the theoretical analysis.

Multiloop controller and reference generator for a dynamic voltage restorer implementation

This paper deals with the design and analysis of a Dynamic Voltage Restorer output voltage control. Such control is based on a multiloop strategy, with an inner current PID regulator and an outer P+Resonant voltage controller. The inner regulator is applied on the output inductor current. It will be also demonstrated how the load current behavior may influence in the DVR output voltage, which justifies the need for the resonant controller. Additionally, it will be discussed the application of a modified algorithm for the identification of the DVR voltage references, which is based on a previously presented positive sequence detector. Since the studied three-phase DVR is assumed to be based on three identical H-bridge converters, all the analysis and design procedures were realized by means of single-phase equivalent circuits. The discussions and conclusions are supported by theoretical calculations, nonlinear simulations and some experimental results. ©2008 IEEE.

Extracting FSA descriptions of robot behaviours from the dynamics of automatically designed controller networks

Automatic design has become a common approach to evolve complex networks, such as artificial neural networks (ANNs) and random boolean networks (RBNs), and many evolutionary setups have been discussed to increase the efficiency of this process. However networks evolved in this way have few limitations that should not be overlooked. One of these limitations is the black-box problem that refers to the impossibility to analyze internal behaviour of complex networks in an efficient and meaningful way. The aim of this study is to develop a methodology that make it possible to extract finite-state automata (FSAs) descriptions of robot behaviours from the dynamics of automatically designed complex controller networks. These FSAs unlike complex networks from which they're extracted are both readable and editable thus making the resulting designs much more valuable.

Home automation controller for a water-flow window

Facing the EU energy efficiency and legal scenarios related to buildings (2010/31 EU directive), new sustainable advanced concepts for envelopes are required. These innovative designs must be able to offer an elevated level of energy efficiency based on a high performance architecture. According to this, smart glazings, and particularly active water-flow glazings, represent a promising alternative to other solar control glazings, since they can reduce the building energy demand avoiding well known drawbacks as high cost, glare problems and high response time that affect to other smart glazings. This kind of glazing, as any other active one, needs to be operated by a control system. In order to operate a water-flow based window, a new controller based on an inexpensive microcontroller board has been developed

Formal verification of ASM designs using the MDG tool

In this paper, we present a formal hardware verification framework linking ASM with MDG. ASM (Abstract State Machine) is a state based language for describing transition systems. MDG (Multiway Decision Graphs) provides symbolic representation of transition systems with support of abstract sorts and functions. We implemented a transformation tool that automatically generates MDG models from ASM specifications, then formal verification techniques provided by the MDG tool, such as model checking or equivalence checking, can be applied on the generated models. We support this work with a case study of an Island Tunnel Controller, which behavior and structure were specified in ASM then using our ASM-MDG tool successfully verified within the MDG tool.

A Low Cost Controller Board for Teaching Robotics

This paper presents the Smarty Board; a new micro-controller board designed specifically for the robotics teaching needs of Australian schools. The primary motivation for this work was the lack of commercially available and cheap controller boards that would have all their components including interfaces on a single board. Having a single board simplifies the construction of programmable robots that can be used as platforms for teaching and learning robotics. Reducing the cost of the board as much as possible was one of the main design objectives. The target user groups for this device are the secondary and tertiary students, and hobbyists. Previous studies have shown that equipment cost is one of the major obstacles for teaching robotics in Australia. The new controller board was demonstrated at high-school seminars. In these demonstrations the new controller board was used for controlling two robots that we built. These robots are available as kits. Given the strong demand from high-school teachers, new kits will be developed for the next robotic Olympiad to be held in Australia in 2006.

Robust Controller Design of Networked Control Systems with Nonlinear Uncertainties

We address robust stabilization problem for networked control systems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.

Security metrics for object-oriented class designs

Measuring quality attributes of object-oriented designs (e.g. maintainability and performance) has been covered by a number of studies. However, these studies have not considered security as much as other quality attributes. Also, most security studies focus at the level of individual program statements. This approach makes it hard and expensive to discover and fix vulnerabilities caused by design errors. In this work, we focus on the security design of an object oriented application and define a number of security metrics. These metrics allow designers to discover and fix security vulnerabilities at an early stage, and help compare the security of various alternative designs. In particular, we propose seven security metrics to measure Data Encapsulation (accessibility) and Cohesion (interactions) of a given object-oriented class from the point of view of potential information flow.