A Top-Down Optimization Methodology for SC Filter Circuit Design Using Varying Goal Specifications

Abstract

The design of Switched-Capacitor (SC) filters can be an arduous process, which becomes even more complex when the high gain amplifier is replaced by a low gain amplifier or a voltage follower. This eliminates the virtual ground node, requiring the compensation of the parasitic capacitances during the design phase. This paper proposes an automatic procedure for the design of SC filters using low gain amplifiers, based on a Genetic Algorithm (GA) using hybrid cost functions with varying goal specifications. The cost function first uses equations to estimate the filter transfer function, the gain and settling-time of the amplifier and the RC time constants of the switches. This reduces the computation time, thus allowing the use of large populations to cover the entire design space. Once all specifications are met, the GA uses transient electrical simulations of the circuit in the cost functions, resulting in the accurate determination of the filter’s transfer function and allowing the accurate compensation of the parasitic capacitances, obtaining the final design solution within a reasonable computation time.