A single-input fuzzy PID (SIF-PID) controller is proposed in this paper to improve the dynamic performance of dc-dc buck converter. The fuzzy logic adjusts the three parameters of PID controller adaptively by detecting the output voltage. Establishment of double-input rule table with Toeplitz structure is presented by analysising the system response curve. One-dimension rule vectors are derived based on the slope λ of the parallel diagonal lines in rule table to reduce the computational burden. The genetic algorithm is utilized to optimize the coefficient λ to guarantee the simplified rule vectors are equivalent to the original rule table in terms of control performance. Effectiveness of the proposed controller is validated by simulation results.

On the basis of the conventional PID control algorithm, a modified adaptive PID (MA-PID) control algorithm is presented to improve the steady-state and dynamic performance of closed-loop systems. The proposed method has a straightforward structure without excessively increasing the complexity and cost. It can adaptively adjust the values of the control parameters (K p , K i and K d ) by following a new control law. Simulation results show that the line transient response of the MA-PID is better than that of the adaptive digital PID because the differential coefficient K d is introduced to changes. In addition, experimental results based on a FPGA indicate that the MA-PID control algorithm reduces the recovery time by 62.5% in response to a 1V line transient, 50% in response to a 500mA load transient, and 23.6% in response to a steady-state deviation, when compared with the conventional PID control algorithm.