Modeling the minimum cost consensus problem in an asymmetric costs context

The roles of biological springs in vertebrate animals and their implementations in compliant legged robots offer significant advantages over the rigid legged ones in certain types of scenarios. A large number of robotics institutes have been attempting to work in conjunction with biologists and incorporated these principles into the design of biologically inspired robots. The motivation of this review is to investigate the most published compliant legged robots and categorize them according to the types of compliant elements adopted in their mechanical structures. Based on the typical robots investigated, the trade-off between each category is summarized. In addition, the most significant performances of these robots are compared quantitatively, and multiple available solutions for the future compliant legged robot design are suggested. Finally, the design challenges for compliant legged robots are analysed. This review will provide useful guidance for robotic designers in creating new designs by inheriting the virtues of those successful robots according to the specific tasks.

https://iopscience.iop.org/article/10.1088/1748-3182/7/4/041001/pdf

A survey of bio-inspired compliant legged robot designs

Periodic charging planning for a mobile WCE in wireless rechargeable sensor networks based on hybrid PSO and GA algorithm

Genetic learning particle swarm optimization (GL-PSO) improves the performance of particle swarm optimization (PSO) by breeding superior exemplars to guide the motion of particles. However, GL-PSO adopts a global topology for exemplar generation and cannot preserve sufficient diversity to enhance exploration, and therefore, its performance on complex optimization problems is unsatisfactory. To further improve GL-PSO's performance and adaptability, two modifications are incorporated into the original GL-PSO. A ring topology is adopted in exemplar generation to enhance diversity and exploration, while a global learning component (GLC) with linearly adjusted control parameters is employed to improve the algorithm's adaptability. The resultant algorithm is referred to as global genetic learning particle swarm optimization with diversity enhancement by ring topology (GGL-PSOD). To validate the effectiveness of these two modifications, they are combined with GL-PSO separately and together and further tested experimentally. The comparison results on the CEC2017 test suite show that the adoption of the ring topology in exemplar generation can enhance the diversity and exploration capability of GL-PSO, while combining GLC alone with GL-PSO cannot achieve significant improvement. Incorporating both modifications into GL-PSO, the resultant GGL-PSOD exhibits high performance and strong adaptability on different types of CEC2017 functions. It outperforms seven representative PSO variants and five non-PSO meta-heuristics, including GL-PSO, SL-PSO, HCLPSO, EPSO, ABC, CMA-ES and CS.

Global genetic learning particle swarm optimization with diversity enhancement by ring topology

Decoupling control of steering and driving system for in-wheel-motor-drive electric vehicle

Improvement of valve seating performance of engine’s electromagnetic valvetrain

In an electromagnetic valve actuator (EMVA), precise motion control is desired to achieve fully variable valve actuation, so that the fuel economy, the emissions, and the torque output performance ...

Motion control of an electromagnetic valve actuator based on the inverse system method

This paper presents a control strategy to improve the output power for a single-cylinder two-stroke free-piston linear generator (FPLG). The comprehensive simulation model of this FPLG is established and the operation principle is introduced. The factors that affect the output power are analyzed theoretically. The characteristics of the piston motion are studied. Considering the different features of the piston motion respectively in acceleration and deceleration phases, a ladder-like electromagnetic force control strategy is proposed. According to the status of the linear electric machine, the reference profile of the electromagnetic force is divided into four ladder-like stages during one motion cycle. The piston motions, especially the dead center errors, are controlled by regulating the profile of the electromagnetic force. The feasibility and advantage of the proposed control strategy are verified through comparison analyses with two conventional control strategies via MatLab/Simulink. The results state that the proposed control strategy can improve the output power by around 7–10% with the same fuel cycle mass.

A Free-Piston Linear Generator Control Strategy for Improving Output Power

Free-piston engine coupled with linear generator is a new kind of thermoelectric energy converter. It has been highly concerned due to its high efficiency and low emission in recent years. In this paper, a tubular moving-coil linear generator is developed for the application of free-piston engines. The two-dimensional finite-element model of the linear generator is established, and its electromagnetic characteristics are analyzed. A power converter is designed to control the operating state and the electric current of the linear generator. A prototype is developed and used in a free-piston engine with a bore of 102 mm, and the main performance parameters are tested. According to the simulated and tested results, the linear generator can realize the stable running of free-piston engines. The peak power of the linear generator in a cycle is about 16.77 kW, and the averaged generating power of a cycle is 3.37 kW at the working frequency of 10 Hz. The generating efficiency at peak power of a cycle is about 95.2%, the averaged generating efficiency of a cycle is about 87.5%.

A Tubular PM Linear Generator With a Coreless Moving-Coil for Free-Piston Engines

Energy management strategy is very important for hydraulic hybrid vehicles to improve fuel economy. The rule-based energy management strategies are widely used in engineering practice due to their simplicity and practicality. However, their performances differ a lot from different parameters and control actions. A rule-based energy management strategy is designed in this paper to realize real-time control of a novel hydraulic hybrid vehicle, and a control parameter selection method based on dynamic programming is proposed to optimize its performance. Firstly, the simulation model of the hydraulic hybrid vehicle is built and validated by the data tested from prototype experimental platform. Based on the simulation model, the optimization method of dynamic programming is used to find the global optimal solution of the engine control for the UDDS drive cycle. Then, the engine control parameters of the rule-based energy management strategy are selected according to the engine control trajectory of the global optimal solution. The simulation results show that the 100 km fuel consumption of the proposed rule-based energy management strategy is 12.7L, which is very close to the global optimal value of 12.4L and is suboptimal.

/pdf/a-rule-based-energy-management-strategy-based-on-dynamic-54mj6ippb6.pdf

Liang Liu

Papers

Improvement of valve seating performance of engine’s electromagnetic valvetrain

Motion control of an electromagnetic valve actuator based on the inverse system method

A Free-Piston Linear Generator Control Strategy for Improving Output Power

A Tubular PM Linear Generator With a Coreless Moving-Coil for Free-Piston Engines

A Rule-Based Energy Management Strategy Based on Dynamic Programming for Hydraulic Hybrid Vehicles