Closed-loop control of a 2-D mems micromirror with sidewall electrodes for a laser scanning microscope system

This article presents the development and implementation of a robust nonlinear control scheme for a 2-D micromirror-based laser scanning microscope system. The presented control scheme, built around sliding mode control approach and augmented an adaptive algorithm, is proposed to improve the tracking accuracy in presence of cross-axis effect. The closed-loop controlled imaging system is developed through integrating a 2-D micromirror with sidewall electrodes (SW), a laser source, NI field-programmable gate array (FPGA) hardware, the optics, position sensing detector (PSD) and photo detector (PD). The experimental results demonstrated that the proposed scheme is able to achieve accurate tracking of a reference triangular signal. Compared with open-loop control, the scanning performance is significantly improved, and a better 2-D image is obtained using the micromirror with the proposed scheme.     

Theory of confocal fluorescence imaging in the programmable array microscope (PAM)

The programmable array microscope (PAM) uses a spatial light modulator (SLM) to generate an arbitrary pattern of conjugate illumination and detection elements. The SLM dissects the fluorescent light imaged by the objective into a focal conjugate image, I_c, formed by the ‘in-focus’ light, and a nonconjugate image, I_nc, formed by the ‘out-of-focus’ light. We discuss two different schemes for confocal imaging using the PAM. In the first, a grid of points is shifted to scan the complete image. The second, faster approach, uses a short tiled pseudorandom sequence of two-dimensional patterns. In the first case, I_c is analogous to a confocal image and I_nc to a conventional image minus I_c. In the second case I_c and I_nc are the sum and the difference, respectively, of a conventional and a confocal image. The pseudorandom sequence approach requires post-processing to retrieve the confocal part, but generates significantly higher signal levels for an equivalent integration time.     

A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics

In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern.