Auto-tuning for high performance autopilot design

A novel auto-tuning method for the RIDE controller algorithm is presented. The RIDE controller is applied to a high performance aircraft model. The tuner utilises a constrained genetic algorithm to automate the tuning process. The results of the tuner are compared with that of another tuning method which utilises unconstrained optimisation so as to highlight the efficacy of constrained optimisation for this application. It is shown from the results that the constrained genetic algorithm optimisation scheme offers a highly effective tuning solution which can be used to attain safe and high performance control with the RIDE control algorithm

Finite Size Effect on Nanomechanical Mass Detection: Role of Surface Elasticity

Nanomechanical resonators have recently been highlighted because of their remarkable ability to perform the sensing and detection. Since the nanomechanical resonators are characterized by large surface-to-volume ratio, it is implied that the surface effect plays a substantial role on not only the resonance but also the sensing performance of nanomechanical resonators. In this work, we have studied the role of surface effect on the detection sensitivity of a nanoresonator that undergoes either harmonic vibration or nonlinear oscillation based on the continuum elastic model such as beam model. It is shown that surface effect makes an impact on both harmonic resonance and nonlinear oscillations, and that the sensing performance is dependent on the surface effect. Moreover, we have also investigated the surface effect on the mechanical tuning of resonance and sensing performance. It is interestingly found that the mechanical tuning of resonance is independent of surface effect, and that the mechanical tuning of sensing performance is determined by surface effect. Our study sheds light on the importance of surface effect on the sensing performance of nanoresonators

Embedded Network Test-Bed for Validating Real-Time Control Algorithms to Ensure Optimal Time Domain Performance

The paper presents a Stateflow based network test-bed to validate real-time optimal control algorithms. Genetic Algorithm (GA) based time domain performance index minimization is attempted for tuning of PI controller to handle a balanced lag and delay type First Order Plus Time Delay (FOPTD) process over network. The tuning performance is validated on a real-time communication network with artificially simulated stochastic delay, packet loss and out-of order packets characterizing the network.Comment: 6 pages, 12 figure

Notch Filtering Suitable for Real Time Removal of Power Line Interference

This paper presents a high performance notch filtering for real time suppression of power line interference in a general signal. The disturbing signal is suppressed using an optimal notch FIR filter with tunable notch frequency. The tuning of the filter preserves its selectivity, most importantly the specified attenuation at the notch frequency. One example and two Matlab functions demonstrate the performance, robustness and usefulness of the proposed procedure for the design and tuning of optimal notch FIR filters suitable in the real time notch filtering