The multiobjective optimal control method optimizes the performance indexes of nonlinear systems to obtain setpoints, and designs a controller to track the setpoints. However, the stepwise optimal control method that independently analyzes the optimization process may obtain unfeasible and difficult to track setpoints, which will reduce the operation and control performance of the systems. To solve this problem, a multiobjective integrated optimal control (MIOC) strategy is proposed for nonlinear systems in this article. The main contributions of MIOC are threefold. First, in the framework of multiobjective model predictive control, an integrated control structure with a comprehensive cost function and a collaborative optimization algorithm is designed to achieve the coordinate optimal control. Second, for the time inconformity of setpoints and control laws caused by the characteristic of tracking control, the different prediction horizons are designed for the comprehensive cost function. Then, the collaborative optimization algorithm is proposed for the comprehensive cost function to achieve the integrated solution of setpoints and control laws to enhance the operation and control performance of nonlinear systems. Third, the stability and control performance analysis of MIOC is provided. Finally, the proposed MIOC method is applied for a nonlinear system to demonstrate its effectiveness.

中文翻译：

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非线性系统的多目标集成最优控制。

多目标最优控制方法优化非线性系统的性能指标以获得设定点，并设计控制器来跟踪设定点。然而，独立分析优化过程的逐步优化控制方法可能会获得不可行且难以跟踪的设定值，从而降低系统的运行和控制性能。为了解决这个问题，本文提出了一种针对非线性系统的多目标综合最优控制（MIOC）策略。MIOC 的主要贡献有三方面。首先，在多目标模型预测控制的框架下，设计了具有综合成本函数和协同优化算法的集成控制结构，以实现协调最优控制。其次，针对跟踪控制的特点造成的设定值与控制规律的时间不一致，为综合成本函数设计了不同的预测时域。然后，针对综合成本函数提出协同优化算法，实现设定值和控制律的集成求解，从而增强非线性系统的运行和控制性能。第三，提供了MIOC的稳定性和控制性能分析。最后，将所提出的 MIOC 方法应用于非线性系统以证明其有效性。