Event‐triggered guaranteed cost fault‐tolerant optimal tracking control for uncertain nonlinear system via adaptive dynamic programming

Abstract

In this article, an event-triggered guaranteed cost optimal tracking control problem is investigated for a class of uncertain nonlinear system with partial loss of actuator effectiveness faults. To begin with, an augmented system consisted of error system and reference system is constructed to simplify the tracking controller design. Then, in order to consider both actuator faults and system uncertainties in optimal tracking control, an improved discounted cost function is developed. Furthermore, a single critic neural network adaptive dynamic programming algorithm is utilized to implement the event-based approximate optimal controller design. Different from static event-triggered mechanism, the dynamic event-triggered mechanism proposed in this article with an internal dynamic signal can further improve execution efficiency. A Lyapunov-based stability analysis is given to demonstrate the uniformly ultimately bounded stability of the closed-loop system. Finally, two typical nonlinear simulations are presented to verify the developed control method.

Adaptive fault‐tolerant optimized formation control for perturbed nonlinear multiagent systems

“…Among them, optimal control has been focused on in the past several decades because it considers the stability for the controlled systems and reduces the energy consumption simultaneously 21‐24 . The optimal control focuses on minimizing the value function, which can be obtained from the Hamilton–Jacobi–Bellman (HJB) equation 25‐27 . While, owing to its strong nonlinearity, solving the HJB equation by analytical solution becomes intractable.…”

“…[21][22][23][24] The optimal control focuses on minimizing the value function, which can be obtained from the Hamilton-Jacobi-Bellman (HJB) equation. [25][26][27] While, owing to its strong nonlinearity, solving the HJB equation by analytical solution becomes intractable. Thus, the reinforcement learning (RL) has gradually utilized to obtain the approximate solution of HJB equation by learning networks.…”

Stability of nonlinear distributed delay system with parameter uncertainties: Integral‐based event‐triggered impulsive control strategy

“…The stability analysis of nonlinear systems has received a great deal of attention in the literature in recent decades 1‐7 . Successful applications of nonlinear systems have been established in many areas such as robotic control, image encryption, confidential communication, and combinatorial optimization 8‐10 .…”

“…The stability analysis of nonlinear systems has received a great deal of attention in the literature in recent decades. [1][2][3][4][5][6][7] Successful applications of nonlinear systems have been established in many areas such as robotic control, image encryption, confidential communication, and combinatorial optimization. [8][9][10] Modeling inaccuracies and changes in the environment often result in the existence of parameter uncertainties in real systems.…”

Event-triggered optimal control for nonlinear stochastic systems via adaptive dynamic programming

“…According to event-trigger mechanism and ADP approaches, a new optimal control method for unknown nonlinear continuous-time systems was proposed in [22]. Guo et al [23] studied the event-triggered guaranteed cost optimal tracking control problem for a class of uncertain nonlinear system by using ADP approaches. However, there is no research for Itô-type stochastic systems with ETOC based on ADP methods.…”