Steady-state optimal controller with actuator noise variancelinearly related to actuator signal variance

The linear-quadratic-Gaussian (LQG) method assumes that the covariance matrix of the actuator noise is given before the design of the feedback matrix. However, in practice, the actuator-noise covariance matrix may depend on the actuator signal energy, which depends on the feedback. Consequently, the feedback from LQG theory degrades the system performance. The authors investigate the steady-state optimal controller when the noise variance of an actuator is linearly related to the variance of an actuator signal. This control system could be much more precise and/or spend much less control energy than the one obtained through the use of the ordinary LQG method     

Probing the interface behaviour of injection molded thermoplastics by micro-thermal analysis and temperature-modulated differential scanning calorimetry

Micro-thermal analysis (μTA™) and temperature-modulated differential scanning calorimetry (TMDSC) are emerging as powerful instruments for identifying the existence and quantities of phases in multi-component systems, as well as interfacial properties. In this study, these two complimentary techniques are utilised to probe the interphase behaviour of a polycarbonate/acrylonitrile-styrene-acrylate (PC/ASA) blend as they develop during injection molding. Micro-thermal analysis revealed that parts manufactured at high injection time, pack pressure and melt temperature show a densely packed bulk morphology, a significant amount of particle agglomeration as well as the formation of styrene-acrylonitrile/PC (SAN/PC) interphases. TMDSC qualitatively and quantitatively characterized the PC/ASA's multi-phase morphology and its interfacial properties both before and after injection molding, indicating a greater amount of PC entering the interphase than SAN.