Neuro-Optimal Guidance Control for Lunar Soft Landing

Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.

On the Solutions of the Matrix Equations in Optimal Stochastic Control

In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.

Guest Editorial for Special Issue on Control and Optimization in Renewable Energy Systems

I.I NTRODUCTION W ITH the advent of low-carbon economy,there has been a growing interest in harnessing renewable energy resources particularly for electricity generation.Renewable energy resources are advocated for the economic and environ-

Optimization of projectile state and trajectory of reentry body considering attainment of carrying aircraft

As an improvement of traditional maximum range trajectory optimization, both the projectile state and control sequence of reentry body are optimized to achieve the maximum range. To ensure the optimal projectile state is in the reachable domain of the carrying aircraft, the climb of the carrying aircraft and the flight of reentry body are optimized as a whole based on the hp-adaptive pseudospectral method. Meanwhile, the path constraints, control constraints and initial/terminal states constraints are considered in the optimization as well. In face of the fact that the range of the optimal control solution resulted from the pseudospectral method may be unsmooth, virtual control variables (second derivatives of the angle of attack and bank angle) are proposed in the optimization, while the angle of attack and bank angle are treated as the virtual state variables to guarantee the smoothness of the optimal control solution. The validity of the virtual control variables in smoothing the optimal control solution is verified by simulation, and the optimality of the resulting projectile state and control sequence for reaching the maximum range is confirmed using the indirect approach. ? 1990-2011 Beijing Institute of Aerospace Information.

Generalized Norm Optimal Iterative Learning Control with Intermediate Point and Sub-interval Tracking

Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. This problem addresses the practical needs of many applications, including industrial automation, crane control, satellite positioning and motion control within a medical stroke rehabilitation context. This paper provides a substantial generalization of this framework by providing a solution to the problem of convergence at intermediate points with simultaneous tracking of subsets of outputs to reference trajectories on subintervals. This formulation enables the NOILC paradigm to tackle tasks which mix "point to point" movements with linear tracking requirements and hence substantially broadens the application domain to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments. A solution to the problem is presented in the framework of NOILC and inherits NOILC s well-defined convergence properties. Design guidelines and supporting experimental results are included.

NUMERICAL MODEL FOR DYNAMIC SIMULATION OF TRAFFIC FLOW

For the purpose of practical application in traffic engineering, especially in automatic control of traffic systems, in this paper a numerical model for the dynamic simulation of traffic flow was presented, involving difference schemes, boundary conditions and their discrete forms, expressions of traffic behavior parameters and technique of modelling parameter identification. The analysis of numerical simulation for several realistic examples shows the usefulness and advantages of the model.