Zhang Danhong

Fuzzy-immune PID control for AMB systems

In order to improve the dynamic performance of active magnetic bearing systems with highly nonlinear and naturally unstable dynamics, a new nonlinear fuzzy-immune proportional-integral-derivative (PID) controller is proposed by combining the immune feedback law with linear PID control. This controller consists of a PID controller and a basic immune proportional controller in cascaded connection, the nonlinear function of the immune proportional controller is realized by using fuzzy reasoning. Simulation results demonstrate that the active magnetic bearing system with the proposed controller has better dynamic performance and disturbance rejection ability than using the linear PID controller.

The optimization of controller parameters for three phases PLL tracking system

In order to improve the performance of the three phases PLL system, this paper designs an algorithm to optimize the PI controller parameters based on the integral of squared error theory. First, it analyzes the nonlinear character of the three phases PLL which uses the d-q coordinate transformation theory to lock the voltage phase, and deduces the closed loop transfer function of the PLL system with PI controller. In the second part, it analyzes the harmonic component of the voltage projected on q axis, and designs a reasonable filter to eliminate the effect of the harmonic voltage. With the linearizated closed loop transfer function, it establishes the cost function of the controller parameters optimization problem based on the ISE theory, and provides a rule that how to design the reference trajectory. For the cost function optimization, it deduces the partial derivative of the cost function and uses conjugate gradient method to solve the optimization problem. In the last part, it applies the optimized PI controller to unbalanced grid and voltage distortion conditions, the simulation results indicate that the optimized PI controller obtains robust and fast tracking ability.

Magnetic Bearings Control Using Fuzzy Logic and a Single Neuron

Linear controllers cannot get satisfactory results for active magnetic bearings (AMB) due to the highly nonlinear and open-loop unstable electromechanical dynamics. This paper proposes a combined controller which integrates a fuzzy logic controller (FLC) with a single neuron controller for AMB. The FLC operates with a small single neuron control component when the system error is big; the FLC and the single neuron controller operate simultaneously when the system error is small. The proposed controller overcomes the defect of the FLC which has a steady state error, and the defect of a single neuron controller which has unsatisfied dynamic performance. Simulation results demonstrate that the proposed controller has improved the dynamic performance and the disturbance rejection ability of AMB.