Randomized Optimal Design of Parallel Manipulators

This work intends to deal with the optimal kinematic synthesis problem of parallel manipulators under a unified framework. Observing that regular (e.g., hyper-rectangular) workspaces are desirable for most machines, we propose the concept of effective regular workspace, which reflects simultaneously requirements on the workspace shape and quality. The effectiveness of a workspace is characterized by the dexterity of the mechanism over every point in the workspace. Other performance indices, such as manipulability and stiffness, provide alternatives of dexterity characterization of workspace effectiveness. An optimal design problem, including constraints on actuated/passive joint limits and link interference, is then formulated to find the manipulator geometry that maximizes the effective regular workspace. This problem is a constrained nonlinear optimization problem without explicitly analytical expression. Traditional gradient based approaches may have difficulty in searching the global optimum. The controlled random search technique, as reported robust and reliable, is used to obtain an numerical solution. The design procedure is demonstrated through examples of a Delta robot and a Gough-Stewart platform. Note to Practitioners-The kinematic/dynamic performance of a parallel manipulator highly depends on its geometry, e.g., link lengths, positions of fixed actuator, shape and size of end-effector. In designing a parallel manipulator, it is a crucial step to determine the best geometry that satisfies practical design requirements. For a general parallel manipulator, this paper provides a unified framework to formulate the optimal design problem by considering some key kinematic criteria, regularity and volume of workspace and dexterity. The latter one is closely related to stiffness and control accuracy. Since the optimal design problem is a nonlinear optimization problem without analytic expression, traditional gradient based search algorithms have difficulty to solve the problem. The controlled random search technique is used to search the global optimum. The design procedure is applicable for general parallel manipulators. Other design criteria, such as stiffness and accuracy, can be readily included in the design formulation

Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model

Constructing commonsense knowledge graphs (CKGs) has attracted wide research attention due to its significant importance in cognitive intelligence. Nevertheless, existing CKGs are typically oriented to English, limiting the research in non-English languages. Meanwhile, the emergence of foundation models like ChatGPT and GPT-4 has shown promising intelligence with the help of reinforcement learning from human feedback. Under the background, in this paper, we utilize foundation models to construct a Chinese CKG, named Snowman. Specifically, we distill different types of commonsense head items from ChatGPT, and continue to use it to collect tail items with respect to the head items and pre-defined relations. Based on the preliminary analysis, we find the negative commonsense knowledge distilled by ChatGPT achieves lower human acceptance compared to other knowledge. Therefore, we design a simple yet effective self-instruct filtering strategy to filter out invalid negative commonsense. Overall, the constructed Snowman covers more than ten million Chinese commonsense triples, making it the largest Chinese CKG. Moreover, human studies show the acceptance of Snowman achieves 90.6\%, indicating the high-quality triples distilled by the cutting-edge foundation model. We also conduct experiments on commonsense knowledge models to show the usability and effectiveness of our Snowman.Comment: tech repor

Gain scheduled torque compensation of PMSG-based wind turbine for frequency regulation in an isolated grid

Frequency stability in an isolated grid can be easily impacted by sudden load or wind speed changes. Many frequency regulation techniques are utilized to solve this problem. However, there are only few studies designing torque compensation controllers based on power performances in different Speed Parts. It is a major challenge for a wind turbine generator (WTG) to achieve the satisfactory compensation performance in different Speed Parts. To tackle this challenge, this paper proposes a gain scheduled torque compensation strategy for permanent magnet synchronous generator (PMSG) based wind turbines. Our main idea is to improve the anti-disturbance ability for frequency regulation by compensating torque based on WTG speed Parts. To achieve higher power reserve in each Speed Part, an enhanced deloading method of WTG is proposed. We develop a new small-signal dynamic model through analyzing the steady-state performances of deloaded WTG in the whole range of wind speed. Subsequently, H∞ theory is leveraged in designing the gain scheduled torque compensation controller to effectively suppress frequency fluctuation. Moreover, since torque compensation brings about untimely power adjustment in over-rated wind speed condition, the conventional speed reference of pitch control system is improved. Our simulation and experimental results demonstrate that the proposed strategy can significantly improve frequency stability and smoothen power fluctuation resulting from wind speed variations. The minimum of frequency deviation with the proposed strategy is improved by up to 0.16 Hz at over-rated wind speed. Our technique can also improve anti-disturbance ability in frequency domain and achieve power balance

Molecular analysis of phosphomannomutase (PMM) genes reveals a unique PMM duplication event in diverse Triticeae species and the main PMM isozymes in bread wheat tissues

BACKGROUND: Phosphomannomutase (PMM) is an essential enzyme in eukaryotes. However, little is known about PMM gene and function in crop plants. Here, we report molecular evolutionary and biochemical analysis of PMM genes in bread wheat and related Triticeae species. RESULTS: Two sets of homoeologous PMM genes (TaPMM-1 and 2) were found in bread wheat, and two corresponding PMM genes were identified in the diploid progenitors of bread wheat and many other diploid Triticeae species. The duplication event yielding PMM-1 and 2 occurred before the radiation of diploid Triticeae genomes. The PMM gene family in wheat and relatives may evolve largely under purifying selection. Among the six TaPMM genes, the transcript levels of PMM-1 members were comparatively high and their recombinant proteins were all enzymatically active. However, PMM-2 homoeologs exhibited lower transcript levels, two of which were also inactive. TaPMM-A1, B1 and D1 were probably the main active isozymes in bread wheat tissues. The three isozymes differed from their counterparts in barley and Brachypodium distachyon in being more tolerant to elevated test temperatures. CONCLUSION: Our work identified the genes encoding PMM isozymes in bread wheat and relatives, uncovered a unique PMM duplication event in diverse Triticeae species, and revealed the main active PMM isozymes in bread wheat tissues. The knowledge obtained here improves the understanding of PMM evolution in eukaryotic organisms, and may facilitate further investigations of PMM function in the temperature adaptability of bread wheat