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Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model

机译：基于归零神经网络的机器人臂的活跃感应：一种生物学 - 启发式优化模型

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摘要

Conventional biological-heuristic solutions via zeroing neural network (ZNN) models have achieved preliminary efficiency on time-dependent nonlinear optimization problems handling. However, the investigation on finding a feasible ZNN model to solve the time-dependent nonlinear optimization problems with both inequality and equality constraints still remains stagnant because of the nonlinearity and complexity. To make new progresses on the ZNN for time-dependent nonlinear optimization problems solving, this paper proposes a biological-heuristic optimization model, i.e., inequality and equality constrained optimization ZNN (IECO-ZNN). Such a proposed IECO-ZNN breaks the conditionality that the solutions via ZNN for solving nonlinear optimization problems can not consider the inequality and equality constraints at the same time. The time-dependent nonlinear optimization problem subject to inequality and equality constraints is skillfully converted to a time-dependent equality system by exploiting the Lagrange multiplier rule. The design process for the IECO-ZNN model is presented together with its new architecture illustrated in details. In addition, the conversion equivalence, global stability as well as exponential convergence property are theoretically proven. Moreover, numerical studies, real-world applications to robot arm active sensing, and comparisons sufficiently verify the effectiveness and superiority of the proposed IECO-ZNN model for the time-dependent nonlinear optimization with inequality and equality constraints.
机译：通过归零神经网络（ZnN）模型的传统生物启发式解决方案已经实现了处理处理时间依赖性非线性优化问题的初步效率。然而，由于非线性和复杂性，查找可行ZnN模型以解决不平等和平等约束的时间依赖性非线性优化问题仍然仍然停滞。为了对ZnN进行新的进展，用于解决时间依赖的非线性优化问题，提出了生物启发式优化模型，即不等式和平等约束优化ZnN（Ieco-ZnN）。这种提出的IECO-ZnN打破了通过ZnN解决非线性优化问题的解决方案不能同时考虑不等式和平等约束。通过利用拉格朗日乘数规则，熟练地将不等式和平等约束受到不等式和平等约束的时间依赖的非线性优化问题。 IECO-ZNN模型的设计过程与详细说明的新架构一起呈现。此外，理论上证明了转换等价，全局稳定性以及指数收敛性。此外，数值研究，真实世界应用于机器人臂的主动感测，以及比较充分验证所提出的IECO-ZNN模型的有效性和优越性，以便与不等式和平等约束的时间依赖性非线性优化。

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