Adaptive Receding Horizon Control For Nonlinear Systems Exemplified by Two Coupled van der Pol Oscillators

Awudu Atinga, Amensisa Wirtu, J. Tar
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Abstract

A heuristic “Adaptive Receding Horizon Controller” (ARHC) approach was recently suggested in which tracking the “nominal trajectory” was formulated as minimizing a cost term by the use of a “heavy dynamic model”, and the so obtained “optimized path“ was adaptively tracked by the use of a “less heavy” engine for which only an approximate model was available. For tracking this optimized trajectory a Fixed Point Iteration-based solution was suggested on the basis of Banach's Fixed Point Theorem. For reducing the computational burden of optimization the heavy dynamic model was not taken into account as a constraint (as usually it used to be), but it was directly used in building up the horizon with forward differences. As a consequence the number of the free variables of optimization was drastically decreased, and the computational burden of gradient reduction was spared, too. In this paper this method is further investigated by the use of two nonlinearly coupled van der Pol oscillators as a paradigm of nonlinear dynamical system. Furthermore, the usual quadratic cost functions were substituted by much simpler ones. In the paper simulation results exemplify the operation of the method that seems to be promising for breaking out of the realm of the traditional quadratic cost functions, and linear time-invariant dynamic models.
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以双耦合范德波勒振子为例的非线性系统自适应后退水平控制
最近提出了一种启发式的“自适应渐退地平线控制器”(ARHC)方法,该方法通过使用“重动态模型”将跟踪“标称轨迹”表述为最小化成本项,并使用只有近似模型可用的“轻重”引擎自适应跟踪所获得的“优化路径”。基于Banach不动点定理,提出了一种基于不动点迭代的优化轨迹跟踪方法。为了减少优化的计算量,不像过去那样将重动态模型作为约束考虑,而是直接用于建立具有前向差分的视界。因此,优化的自由变量的数量大大减少,也避免了梯度缩减的计算负担。本文以两个非线性耦合范德宝尔振子作为非线性动力系统的范例,进一步研究了该方法。此外,通常的二次代价函数被更简单的代价函数所取代。本文的仿真结果表明,该方法有望突破传统的二次代价函数和线性时不变动态模型的领域。
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