As the road conditions are completely unknown in the design of a suspension controller, an improved linear quadratic and Gaussian distributed (LQG) controller is proposed for active suspension system without considering road input signals. The main purpose is to optimize the vehicle body acceleration, pitching angular acceleration, displacement of suspension system, and tire dynamic deflection comprehensively. Meanwhile, it will extend the applicability of the LQG controller. Firstly, the half-vehicle and road input mathematical models of an active suspension system are established, with the weight coefficients of each evaluating indicator optimized by using genetic algorithm (GA). Then, a simulation model is built in Matlab/Simulink environment. Finally, a comparison of simulation is conducted to illustrate that the proposed LQG controller can obtain the better comprehensive performance of vehicle suspension system and improve riding comfort and handling safety compared to the conventional one.
In this Letter, we present a photonic compressive sampling scheme based on optical sampling and random demodulation for microwave spectral analysis. A novel (to our knowledge) approach to realizing the multiplication of a pseudorandom binary sequence and the input microwave signal of interest in the optical domain is proposed, which largely simplifies the implementation of the compressive sampling. A spectrally sparse signal can be successfully captured by an electrical digitizer with a sampling rate much lower than the Nyquist rate with the help of random demodulation and the sparse reconstruction algorithm. Identification of the signals with multiple frequency components is successfully demonstrated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.