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• The event-triggered distributed FTC problem of uncertain nonlinear interconnected systems subjected to unmatched interconnections and time-varying actuator faults is solved by integrating the ADP approach and the dynamic event-triggered control strategy for the first time. • A new cost function is introduced to handle the unmatched interconnections and actuator faults simultaneously. • A new dynamic event-triggered mechanism is established, which has the advantage of enlarging sampling interval. Moreover, the restriction on initial admissible control policy for each auxiliary subsystem is obviated by introducing a robust term into the weight learning law of critic NN. • Theoretical analysis shows that the adverse effects of actuator faults on the stability can be eliminated and the cost function of overall interconnected system can be guaranteed to have an upper bound. A novel dynamic event-triggered distributed fault tolerant control (FTC) scheme with guaranteed cost is proposed for uncertain nonlinear interconnected systems suffering from time-varying actuator faults. The event-triggered FTC problem of uncertain interconnected system is first converted to a series of equivalent event-triggered optimal control designs of isolated fault-free auxiliary subsystems by defining a modified cost function for each auxiliary subsystem. The equivalence of problem transformation is demonstrated meanwhile the upper bound of cost function of overall interconnected system is analyzed. Subsequently, for the isolated auxiliary subsystem, a dynamic event-triggered adaptive dynamic programming (DET-ADP) algorithm is proposed to obtain the optimal control policy, which can remove the restriction of initial admissible control, eliminate the actor network, and save more communication resources. Furthermore, we prove that the closed-loop auxiliary subsystems are ensured to be uniform ultimate bounded based on Lyapunov approach. Finally, simulation results are presented to validate the developed dynamic event-triggered distributed guaranteed cost FTC scheme. [ABSTRACT FROM AUTHOR]

• Few people consider the data-driven parameter adaptive control in the tracking control of AUV. Based on the traditional sliding mode control, a novel adaptive tracking control considering the external environment interference and uncertainty is designed using a data-based online ADHDP method. • The Lyapunov function of ADHDP algorithm considering experience replay is designed to obtain the stability results and ensure the convergence of data-driven neural network weights. • The weighted experience replay method is considered, and the historical data is weighted with a novel parameter λ and is used for the control strategy online real-time update. At present, there are few simultaneous studies. A novel adaptive trajectory tracking control method is proposed in this paper for autonomous underwater vehicle systems with external disturbances. The control action is composed of sliding mode control and action-depended heuristic dynamic programming (ADHDP) controller to track the expected sailing position and angle in the horizontal coordinate system with fixed depth. As an auxiliary control of sliding mode control, the ADHDP controller observes the difference between the actual sailing position/angle and the expected sailing position/angle, and adaptively provides corresponding supplementary control actions using a data-driven fashion. At the same time, we design a weight-related priority experience replay (PER) technology to update the online weight network by using the relevant historical data stored in the database to improve the learning rate. The proposed algorithm can adjust parameters online under various conditions. Furthermore, it is very suitable for underwater vehicle systems with parameter uncertainties and external disturbances. Based on Lyapunov stability method, the stability of closed-loop system state and network weight error is analyzed. Finally, the validity of our control strategy is verified by simulation. [ABSTRACT FROM AUTHOR]

• Compared with the classical Janbu method, the addition of an adaptive dynamic programming algorithm has the following advantages. • In the limit equilibrium analysis of each slice, the individual safety factor is directly added to solve the critical instability trajectory iteratively. Instead of first solving the fractional average and safety factor of the sliding surface, judging the rationality, and then searching for the critical sliding surface, the computational task is vast. • When dealing with a complex engineering background, the reconstructed framework is based on a neural network to complete an iterative solution. The fuzzy relationship of safety factors between adjacent strips can be simplified and integrated into the model network. The interactive iterative update of the action and critic networks can complete the boundary curve corresponding to the limit sliding state. At the same time, in order to further simplify the calculation, the critic network uses a dual network design. Notwithstanding the rich research on the slicing method, it is still impossible to accomplish the limit equilibrium analysis of all phases before the evaluation of the safety factor. Bearing this dilemma in view, in this paper, the Janbu method is optimized and reformulated by introducing adaptive dynamic programming (ADP). The fractional average safety factor is no longer used; instead, a sequence of safety factors is used. The critical slip state is chosen as the equilibrium point, the nonlinearity of safety coefficients of adjacent blocks is approximated by the neural network, and the remaining variables and constraints of the system are added to assist in transforming the original redundant safety coefficient evaluation-finding optimal solution problem into a Janbu-qualified cost function. The action network and critic network of ADP accomplish the boundary trajectory solving and safety evaluation, respectively. The validity of the method is verified when the optimized and reorganized framework is applied to solve the critical slip surface of a clay slope. [ABSTRACT FROM AUTHOR]