Jonathon C. Ralston

Identification of a class of nonlinear systems under stationary non-Gaussian excitation

This paper provides new solutions to the nonlinear system identification problem when the input to the system is a stationary non-Gaussian process. We propose the use of a model called the Hammerstein series, which leads to significant reductions in both the computational requirements and the mathematical tractability of the nonlinear system identification problem. We show that unlike the Volterra series, one can obtain closed-form expressions for the Hammerstein series kernels and the quadratic coherence function in the non-Gaussian case. Estimation of the kernels and quadratic coherence function is discussed. A comparison with a nonlinear system identification approach that uses the Volterra series is provided. An automotive engineering application illustrates the usefulness of the proposed method.

Longwall mining automation an application of minimum-variance smoothing [Applications of Control]

This article reviews the development of the minimum-variance smoother and describes its use in longwall automation. We describe both continuous- and discrete-time smoother solutions. It is shown, under suitable assumptions, that the two-norm of the smoother estimation error is less than that for the Kalman filter. A simulation study is presented to compare the performance of the minimum-variance smoother with the methods of H.E. Rauch et al. (1965), and D.C. Fraser and J.E. Potter (1969).

Optimizing Wireless LAN for Longwall Coal Mine Automation

A significant development in underground longwall coal mining automation has been achieved with the successful implementation of wireless LAN (WLAN) technology for communication on a longwall shearer. WIreless-FIdelity (Wi-Fi) was selected to meet the bandwidth requirements of the underground data network, and several configurations were installed on operating longwalls to evaluate their performance. Although these efforts demonstrated the feasibility of using WLAN technology in longwall operation, it was clear that new research and development was required in order to establish optimal full-face coverage. By undertaking an accurate characterization of the target environment, it has been possible to achieve great improvements in WLAN performance over a nominal Wi-Fi installation. This paper discusses the impact of Fresnel zone obstructions and multipath effects on radio frequency propagation and reports an optimal antenna and system configuration. Many of the lessons learned in the longwall case are immediately applicable to other underground mining operations, particularly wherever there is a high degree of obstruction from mining equipment

Recent advances in remote coal mining machine sensing, guidance, and teleoperation

This paper presents some recent applications of sensing, guidance and telerobotic technology in the coal mining industry. Of special interest is the development of semi or fully autonomous systems to provide remote guidance and communications for coal mining equipment. We consider the use of radar and inertial based sensors in an attempt to solve the horizontal and lateral guidance problems associated with mining equipment automation. We also describe a novel teleoperated robot vehicle with unique communications capabilities, called the Numbat, which is used in underground mine safety and reconnaissance missions.

Application of ground penetrating radar for coal depth measurement

This paper describes the development of a new ground penetrating radar system for measuring coal thickness in underground mining operations. Although subsurface radar exhibits significant potential for depth measurement, the raw signals are complicated and cannot be readily interpreted by mining personnel. We show how real-time digital signal processing plays a key role in transforming the raw radar signals into a form that can be readily understood. We also indicate some of the unique challenges encountered when implementing a radar processing system in a harsh underground mining environment.

Identification of time-varying Hammerstein systems

We consider the identification of systems which are both time-varying and nonlinear. This class of systems is more likely to be encountered in practice, but is often avoided due to the difficulties that arise in modelling and estimation. We attempt to address this problem by considering a new time-varying nonlinear model, the time-varying Hammerstein model, which effectively characterises time-variation and nonlinearity in a simple manner. Using this model we formulate a procedure to find least-squares estimates of the coefficients. The model is general and can be used when little is known about the time-variation of the system. In addition, we do not require that the input is stationary or Gaussian. Finally, an application to automobile knock modelling is presented, where a time-varying nonlinear model is seen to more accurately characterise the system than a time-varying linear one.

Software defined radar: An open source platform for prototype GPR development

This discussion paper explores the potential of Software Defined Radio (SDR) technology to provide flexible and low-cost subsurface radar prototypes for the GPR community. Unlike traditional fixed hardware implementations, SDR uses software configurable RF modules which can be used to implement customized signal encoding, decoding and processing. However, the full potential of SDR has not yet been fully understood or exploited for radar-based applications, and so is of special interest for GPR development. This paper introduces the fundamental concepts behind SDRs and describes the underlying hardware and software architectures that are used to implement them. It also provides a simple reference design using open source GNU Radio software and the Universal Software Radio Peripheral (USRP) hardware to indicate how low-cost radar configurations can be designed and evaluated. The benefits and challenges of SDR-based radar architectures are highlighted, and opportunities discussed for new and enhanced subsurface sensing capabilities. Overall, SDR technology is seen to provide new opportunities to boost future radar research and development to provide enhanced GPR system capabilities.

The Numbat: A Remotely Controlled Mine Emergency Response Vehicle

The Numbat is a remotely controlled vehicle used to convey information on the condition of underground mines in situations where it is too hazardous for manual exploration. The Numbat integrates a diverse range of communications, actuation, mobility, power, control and software technologies. This paper reports on technical aspects of the Numbat and describes how the management of technologies solves a range of practical problems.

An optimal window length for the PWVD with application to passive acoustic parameter estimation

This paper considers the derivation of an optimal window length for the fourth-order polynomial Wigner-Ville distribution (PWVD/sub 4/), for the purpose of instantaneous frequency (IF) estimation. The optimal window length represents a compromise between the estimator IF error and statistical consistency. The criterion of optimality that we employ is the minimum mean square IF estimation error. The PWVD/sub 4/ optimal window length theory is then applied to the problem of estimating the time-varying acoustic IF of an over-flying aircraft. In the high SNR case, the windowed PWVD/sub 4/ is seen to provide a more accurate IF estimate than those given by the Wigner-Ville Distribution (WVD) and the short-time Fourier transform (STFT).<<ETX>>

A practical procedure for identifying time-varying nonlinear systems using basis sequence approximations

We approximate a class of time-varying nonlinear models, called the time-varying Hammerstein series, using basis sequences in order to reduce the number of coefficients required in system modelling. The problem is motivated by the practical need to parsimoniously characterise time-varying nonlinear systems. A significant advantage of the approach is that only a single input-output record is required to obtain least-squares estimates of the model parameters. The judicious selection of basis sequence is also discussed. The method represents a simple and practical time-varying nonlinear system identification procedure. Examples are presented to demonstrate the usefulness of the technique.