Search

• An event based ADP method is first put forward to study the finite horizon ZS differential game. • The data driven identifier and a single CNN are employed to simplify system structures and network architectures by using a plug n play scheme. • The missile target intercept system is introduce to demonstrate the validity of the proposed event based optimal controller. This paper proposes a robust optimal control strategy for finite-horizon two-player Zero-Sum(ZS) differential games with partially unknown dynamics by incorporating an event-triggered scheme and the critic-only adaptive dynamic programming(ADP) method. Firstly, an online identifier is designed to reconstruct unknown system dynamics based on the data-driven technique. The identifier is running in the solving process rather than as a priori part of the solution, which simplifies the system structure and decreases the computational cost. To deal with the finite-horizon constraints, a time-varying value function and a additional term are considered to such that the terminal constraint error is minimised. A critic neural network(CNN) is used to solve the event-triggered Hamilton–Jacob—Isaacs (HJI) equation under a plug-n-play structure, which reduces the redundant information transmission as well as receives all measurement information immediately. According to the Lyapunov theory, the uniformly ultimately bounded (UUB) for the event-triggered closed-loop system and the CNN weight error are demonstrated, in the meantime the asymptotic stability of the identifier weight error is proved. Finally, the application in the missile-target interception system validates the feasibility and efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the distributed fuzzy learning sliding mode cooperative control issue for non-affine nonlinear multi-missile guidance systems. The dynamics of each follower is non-affine form with unknown lumped factor. To estimate the unknown lumped factor, a generalized fuzzy hyperbolic model (GFHM) based prescribed performance observer (PPO) is proposed. Different from the traditional disturbance observers, a residual set of error transient behavior is incorporated additionally so that the peak phenomenon can be avoided. Meanwhile, an auxiliary system is employed to convert the system of each follower to augmented affine form. Then, a distributed fuzzy learning sliding mode cooperative control approach is designed which consists of two parts. The adaptive sliding mode control (SMC) part is designed to force the states to move along the predefined integral sliding surface. For the equivalent sliding dynamics, the distributed optimal control part with GFHM is developed to minimize the cooperative performance function. Thus, the stability and the optimality of the closed-loop system are guaranteed synchronously. Finally, all signals of closed-loop system are rigorously proved bounded and the multi-missile cooperative guidance scenario is applied to verify the effectiveness of proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a fault-tolerant control allocation scheme is proposed for a class of over-actuated discrete-time systems. Firstly, an indirect adaptive controller is designed which consists of a parameter updating law to estimate unknown model parameters and a control law based on the estimated model parameters to achieve a desired tracking performance. Meanwhile, the control law is treated as the input of control allocation module to carry out an effective distribution to the physical actuators. Then, a control allocation algorithm is developed, which includes a fixed allocation law and an adaptive allocation law to compensate for actuator faults, uncertainties and actuator saturations. Finally, a numerical example and an aircraft model are used to illustrate the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]