Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller.

Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems: The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). The synthesized discrete-time optimal controller can be directly implemented in real-time systems. The book also proposes the use of recurrent neural networks to model discrete-time nonlinear systems. Combined with the inverse optimal control approach, such models constitute a powerful tool to deal with uncertainties such as unmodeled dynamics and disturbances.

Learn from Simulations and an In-Depth Case Study: The authors include a variety of simulations to illustrate the effectiveness of the synthesized controllers for stabilization and trajectory tracking of discrete-time nonlinear systems. An in-depth case study applies the control schemes to glycemic control in patients with type 1 diabetes mellitus, to calculate the adequate insulin delivery rate required to prevent hyperglycemia and hypoglycemia levels.

The discrete-time optimal and robust control techniques proposed can be used in a range of industrial applications, from aerospace and energy to biomedical and electromechanical systems. Highlighting optimal and efficient control algorithms, this is a valuable resource for researchers, engineers, and students working in nonlinear system control.

非线性系统的离散时间逆向优化控制提出了一种新的逆向优化控制方案，用于离散时间非线性系统的稳定和轨迹跟踪。这避免了解决相关的Hamilton-Jacobi-Bellman方程的需要，并使成本函数最小化，从而产生了一个更有效的控制器。

为离散-时间非线性系统的稳定和轨迹跟踪设计更有效的控制器。本书介绍了两种控制器合成方法：第一种基于被动性理论，第二种基于控制李亚普诺夫函数（CLF）。合成的离散时间最优控制器可以直接在实时系统中实现。本书还提出了使用递归神经网络对离散时间非线性系统进行建模。与逆向最优控制方法相结合，这种模型构成了处理不确定因素的有力工具，如未建模的动态和干扰。

从模拟和深入的案例研究中学习。作者包括各种模拟，以说明合成的控制器对离散时间非线性系统的稳定和轨迹跟踪的有效性。一个深入的案例研究将控制方案应用于1型糖尿病患者的血糖控制，以计算出防止高血糖和低血糖水平所需的足够的胰岛素输送率。

提出的离散时间最优和稳健控制技术可用于一系列工业应用，从航空航天和能源到生物医学和机电系统。本书强调了最优和高效的控制算法，是从事非线性系统控制的研究人员、工程师和学生的宝贵资源。