The design and performance of a WR-5 band 135-150-GHz Schottky diode-based frequency tripler which uses waveguide resonator filters for low loss impedance matching is presented in this paper. The filters used in this paper provide filtering, impedance matching, and microstrip (MS) to waveguide transitions in one structure. The matching optimization is achieved by scaling the external quality factors and adjusting the resonance frequency of the filter cavities. This approach transfers most of the tripler's matching networks from MS circuitry to lower loss rectangular waveguide resonators. This is desirable and useful in particular for submillimeter wave and terahertz frequencies. The device presented is a 47.5 to 142.5 GHz biasless frequency tripler with a 15-GHz output bandwidth. The tripler was measured to have a conversion loss of 13.1-14 dB across the band, at an input power of 17 dBm. The measured S 11 at the input port is better than 15 dB and all the reflection zeros from the filter resonances are distinct. The good agreement between measurements and simulations verifies the accuracy of the filter-based design approach.
Differential evolution (DE) is a well-known algorithm for global optimization over continuous search spaces. However, choosing the optimal control parameters is a challenging task because they are problem oriented. In order to minimize the effects of the control parameters, a Gaussian bare-bones DE (GBDE) and its modified version (MGBDE) are proposed which are almost parameter free. To verify the performance of our approaches, 30 benchmark functions and two real-world problems are utilized. Conducted experiments indicate that the MGBDE performs significantly better than, or at least comparable to, several state-of-the-art DE variants and some existing bare-bones algorithms.
Landing on a moving platform is an essential requirement to achieve high-performance autonomous flight with various vehicles, including quadrotors. We propose an efficient and reliable autonomous landing system, based on model predictive control, which can accurately land in the presence of external disturbances. To detect and track the landing marker, a fast two-stage algorithm is introduced in the gimbaled camera, while a model predictive controller with variable sampling time is used to predict and calculate the entire landing trajectory based on the estimated platform information. As the quadrotor approaches the target platform, the sampling time is gradually shortened to feed a re-planning process that perfects the landing trajectory continuously and rapidly, improving the overall accuracy and computing efficiency. At the same time, a cascade incremental nonlinear dynamic inversion control method is adopted to track the planned trajectory and improve robustness against external disturbances. We carried out both simulations and outdoor flight experiments to demonstrate the effectiveness of the proposed landing system. The results show that the quadrotor can land rapidly and accurately even under external disturbance and that the terminal position, speed and attitude satisfy the requirements of a smooth landing mission.
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