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In this paper, we propose an efficient power control algorithm for the downlink wireless CDMA systems. The goal of our paper is to achieve the optimum and fair resource utilization by maximizing a weighted sum utility with the power constraint. In fact, the objective function in the power optimization problem is always nonconcave, which makes the problem difficult to solve. We make progress in solving this type of optimization problem using PSO (particle swarm optimization). PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. It's proved that the proposed algorithm converges to the global optimal solutions in this paper. Numerical examples show that our algorithm can guarantee the fast convergence and fairness within a few iterations. It also demonstrates that our algorithm can efficiently solve the nonconvex optimization problems when we study the different utility functions in more realistic settings.

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SUMMARYAnti-disturbance control and estimation problem are investigated for nonlinear system subject to multisource disturbances. The disturbances classified model is proposed based on the error and noise analysis of priori knowledge. The disturbance observers are constructed separately from the controller design to estimate the disturbance with partial known information. By integrating disturbance-observer-based control with discrete-time sliding-mode control (DSMC), a novel type of composite stratified anti-disturbance control scheme is presented for a class of multiple-input-multiple-output discrete-time systems with known and unknown nonlinear dynamics, respectively. Simulations for a flight control system are given to demonstrate the effectiveness of the results compared with the previous schemes.