Approximate/adaptive dynamic programming (ADP) has been studied extensively in recent years for its potential scalability to solve large state and control space problems, including those involving continuous states and continuous controls. The applicability of ADP algorithms, especially the adaptive critic designs has been demonstrated in several case studies. Direct heuristic dynamic programmi...

This paper addresses the problem of adaptive fuzzy tracking control for aclass of nonlinearly parameterized systems with unknown control directions.In this paper, the nonlinearly parameterized functions are lumped into the unknown continuous functionswhich can be approximated by using the fuzzy logic systems (FLS) in Mamdani type. Then, the Nussbaum-type function is used to de...

In this paper, an online optimal control scheme for a class of unknown discrete-time (DT) nonlinear systems is developed. The proposed algorithm using current and recorded data to obtain the optimal controller without the knowledge of system dynamics. In order to carry out the algorithm, a neural network (NN) is constructed to identify the unknown system. Then, based on the estimated system mod...

In this paper, a novel adaptive dynamic programming (ADP)-based event-triggered safe control method is proposed to solve the zero-sum game problem of nonlinear safety-critical systems with safety constraints and input saturation. First, barrier function-based system transformation, saturation transformed into an equivalent problem, so as guarantee that does not violate constraints. Furthermore,...

In recent times, a variety of reinforcement learning (RL) algorithms have been proposed for optimal tracking problem continuous time nonlinear systems with input constraints. Most these are based on the notion uniform ultimate boundedness (UUB) stability, in which normally higher rates avoided order to restrict oscillations state error smaller values. However, this comes at cost convergence cri...

Compared with most existing results concerning unmanned aerial vehicles (UAVs) wherein two-degree or only attitude/longitudinal dynamics are considered, this paper proposes an event-based fault-tolerant coordinated control (FTC) for multiple fixed-wing UAVs such that the consensus tracking of velocity and attitude is achieved in presence actuator faults, external disturbances modeling uncertain...

This letter proposes an adaptive neural network-based backstepping controller that uses rigid graph theory to address the distance-based formation control problem and target tracking for nonlinear multi-agent systems with bounded time-delay disturbance. The radial basis function network (RBFNN) is used overcome compensate unknown nonlinearity disturbance in system dynamics. effect of state agen...

This paper examines saturated control of a general class of uncertain nonlinear systems with timedelayed actuation and additive bounded disturbances. The bound on the control is known a priori and can be adjusted by changing the feedback gains. A Lyapunov-based stability analysis utilizing Lyapunov–Krasovskii (LK) functionals is provided to prove uniformly ultimately bounded tracking despite un...

This paper presents a neural network adaptive controller for diving control of an autonomous underwater vehicle (AUV). In general, while deriving the diving equations of an AUV, the pitch angle of the vehicle is often assumed to be small in the diving motion. This is a somewhat strong restricting condition in many practical applications, and would be broken in this paper. Furthermore, because t...