Model-based control of a Rijke tube combustion instability

A Rijke tube is used to demonstrate model-based control of a combustion instability, where controller design is based on measurement of the unstable system. The Rijke tube used was of length 0.75m and had a grid-stabilised laminar flame in its lower half. A microphone was used as a sensor and a loudspeaker as an actuator for active control. The open loop transfer function (OLTF) required for controller design was that from the actuator to the sensor. This was measured experimentally by sending a signal with two components to the actuator. The first was a control component from an empirically designed controller, which was used to stabilise the system, thus eliminating the non-linear limit cycle. The second was a high bandwidth signal for identification of the OLTF. This approach to measuring the OLTF is generic and can be applied to large-scale combustors. The measured OLTF showed that only the fundamental mode of the tube was unstable; this was consistent with the OLTF predicted by a mathematical model of the tube, involving 1-D linear acoustic waves and a time delay heat release model. Based on the measured OLTF, a controller to stabilise the instability was designed using Nyquist techniques. This was implemented and was seen to result in an 80dB reduction in the microphone pressure spectrum. A robustness study was performed by adding an additional length to the top of the Rijke tobe. The controller was found to achieve control up to an increase in tube length of 19%. This compared favourably with the empirical controller, which lost control for an increase in tube length of less than 3%.

A modular planar robotic manipulandum with end-point torque control.

Robotic manipulanda are extensively used in investigation of the motor control of human arm movements. They permit the application of translational forces to the arm based on its state and can be used to probe issues ranging from mechanisms of neural control to biomechanics. However, most current designs are optimized for studying either motor learning or stiffness. Even fewer include end-point torque control which is important for the simulation of objects and the study of tool use. Here we describe a modular, general purpose, two-dimensional planar manipulandum (vBOT) primarily optimized for dynamic learning paradigms. It employs a carbon fibre arm arranged as a parallelogram which is driven by motors via timing pulleys. The design minimizes the intrinsic dynamics of the manipulandum without active compensation. A novel variant of the design (WristBOT) can apply torques at the handle using an add-on cable drive mechanism. In a second variant (StiffBOT) a more rigid arm can be substituted and zero backlash belts can be used, making the StiffBOT more suitable for the study of stiffness. The three variants can be used with custom built display rigs, mounting, and air tables. We investigated the performance of the vBOT and its variants in terms of effective end-point mass, viscosity and stiffness. Finally we present an object manipulation task using the WristBOT. This demonstrates that subjects can perceive the orientation of the principal axis of an object based on haptic feedback arising from its rotational dynamics.

Asymptotic Recovery for Discrete-Time Systems

An asymptotic recovery design procedure is proposed for square, discrete-time, linear, time-invariant multivariable systems, which allows a state-feedback design to be approximately recovered by a dynamic output feedback scheme. Both the case of negligible processing time (compared to the sampling interval) and of significant processing time are discussed. In the former case, it is possible to obtain perfect. © 1985 IEEE.