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Push carts have been widely used as a convenient tool for luggage transport. However, the vibration of the loading platform caused by uneven surfaces hinders transportation of products that are ...sensitive to vibration, such as precision devices. Therefore, in this study, the authors aimed to address this problem using the center of percussion and active vibration control. Our conventional experiments were conducted with a push cart with three wheels, of which only one was equipped with a low shock and low vibration caster; center of percussion and active vibration control were applied. Therefore, for practical application, a prototype four-wheel push cart equipped with four low-shock, low-vibration casters were created to development a vibration control system design. The design utilizes direct inertia force control (DIFC) for vibration control. DIFC requires an inertia force generator (IFG) with acceleration control. The design of the IFG controller is mainly described in the paper. IFG needs both superior target tracking performance and disturbance suppression performance need to be desirable for IFG. Therefore, two degrees of a freedom control system was configured by utilizing the dual model matching method proposed by Tagawa. Furthermore, because disturbances can be measured, disturbance suppression performance was further enhanced using a disturbance feedforward controller. The designed controllers were implemented, and their target tracking performance and disturbance suppression performance were experimentally evaluated. It was confirmed that the designed acceleration tracking increased from 0.5 to 200 Hz. Therefore, performance enhancement of disturbance suppression around the band of the cart resonance frequency as well as the design intentions were confirmed to be achieved.
Evolution strategies(ESs)are search algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems numerically.The effectiveness and simplicity of ...ES algorithms have lead many people to believe that they are the methods of choice for difficult, real-life problems superseding traditional search techniques.However, the inherent strength of the ES algorithms largely depends upon the choice of a suitable crossover and mutation technique in their application domains.This paper discusses a new ES in which both a subpopulationbased arithmetical crossover(SBAC)and a time-variant mutation(TVM)operator are used.the SBAC operator explores promising areas in the search space with different directivity while the TVM operator exploits fast(but not premature)convergence with high precision results.Thus, a balance between exploration and exploitation is achieved in the evolutionary process with these combined efforts.The TVM also acts as a fine local tuner at the converging stages for high precision solutions.Its action depends upon the age of the populations, and its performance is quite different from the Uniform Mutation(UM)operation.The efficacy of the proposed methods is illustrated by solving discrete-time optimal control models which are frequently used in the applications.
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