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A holistic optimization approach for inverted cart-pendulum control tuning

机译:倒车摆锤控制调谐的整体优化方法

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The inverted cart-pendulum (ICP) is a nonlinear underactuated system, which dynamics are representative of many applications. Therefore, the development of ICP control laws is important since these laws are suitable to other systems. Indeed, many nonlinear control strategies have emerged from the control of the ICP. For these reasons, the ICP remains a canonical and fundamental benchmark problem in control theory and robotics that is of interest to the scientific community. Till now, the trial-and-error method is still widely applied for ICP controller tuning as well as the sequential tuning referring to tune the swing-up controller and thereafter, the stabilization controller. Therefore, the aim of this paper is to automate and facilitate the ICP control in one step. Thus, this paper proposes to holistically optimize ICP controllers. The holistic optimization is performed by a simplified Ant Colony Optimization method with a constrained Nelder-Mead algorithm (ACO-NM). Holistic optimization refers to a simultaneous tuning of the swing-up, stabilization and switching mode parameters. A new cost function is designed to minimize swing-up time, achieve high stabilization performance and consider system constraints. The holistic approach optimizes four controller structures, which include controllers that have never been tuned by a specific method besides by the trial-and-error method. Simulation results on a ICP nonlinear model show that ACO-NM in the holistic approach is effective compared to other algorithms. In addition, contrary to the majority of work on the subject, all the optimized controllers are validated experimentally. The simulation and experimental results obtained confirm that the holistic approach is an efficient optimization tool and specifically responds to the need of optimization technique for the potential-well controller structure and for the Q [diagonal of the matrix and the full matrix] in the linear-quadratic regulator (LQR) technique. Moreover, ICP experimental response analysis demonstrates that using the full Q provides greater experimental stabilization performance than using its diagonal terms in the LQR technique.
机译:倒车 - 摆锤(ICP)是非线性欠扰系统的,动力学是许多应用的代表。因此,由于这些法律适合其他系统,因此ICP控制法的发展是重要的。实际上,许多非线性控制策略从ICP的控制中出现了。由于这些原因,ICP仍然是科学界的控制理论和机器人中的规范和基本的基准问题。到目前为止,试验和错误方法仍然广泛应用于ICP控制器调整以及参考曲调旋转控制器的顺序调整,然后稳定控制器。因此,本文的目的是在一步中自动化和促进ICP控制。因此,本文提出全能优化ICP控制器。通过具有约束的Nelder-Mead算法(ACO-NM)的简化蚁群优化方法来执行整体优化。整体优化是指同时调整摆动,稳定和切换模式参数。一种新的成本函数旨在最大限度地减少挥杆时间,实现高稳定性能并考虑系统约束。整体方法优化了四个控制器结构,包括除了试验和错误方法之外从未通过特定方法调整的控制器。 ICP非线性模型上的仿真结果表明,与其他算法相比,整体方法中的ACO-NM是有效的。此外,与对象的大多数工作相反,所有优化的控制器都经过实验验证。获得的仿真和实验结果证实,整体方法是一种有效的优化工具,具体响应潜在井控制器结构的优化技术以及线性 - 二次调节器(LQR)技术。此外,ICP实验响应分析表明,使用完整Q提供更大的实验稳定性能,而不是在LQR技术中使用其对角线。

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