The design (synthesis) of analog electrical circuits starts with a highlevel statement of the circuit's desired behavior and requires creating a circuit that satisfies the specified design goals. Analog circuit synthesis entails the creation of both the topology and the sizing (numerical values) of all of the circuit's components. The difficulty of the problem of analog circuit synthesis is well known and there is no previously known general automated technique for synthesizing an analog circuit from a high-level statement of the circuit's desired behavior. This paper presents a single uniform approach using genetic programming for the automatic synthesis of both the topology and sizing of a suite of eight different prototypical analog circuits, including a lowpass filter, a crossover (woofer and tweeter) filter, a source identification circuit, an amplifier, a computational circuit, a timeoptimal controller circuit, a temperature-sensing circuit, and a voltage reference circuit. The problem-specific information required for each of the eight problems is minimal and consists primarily of the number of inputs and outputs of the desired circuit, the types of available components, and a fitness measure that restates the highlevel

Lisp is the world's greatest programming language---or so its proponents think. The structure of Lisp makes it easy to extend the language or even to implement entirely new dialects without starting from scratch. Overall, the evolution of Lisp has been guided more by institutional rivalry, one-upsmanship, and the glee born of technical cleverness that is characteristic of the "hacker culture" than by sober assessments of technical requirements. Nevertheless this process has eventually produced both an industrialstrength programming language, messy but powerful, and a technically pure dialect, small but powerful, that is suitable for use by programming-language theoreticians. We pick up where McCarthy's paper in the first HOPL conference left off. We trace the development chronologically from the era of the PDP-6, through the heyday of Interlisp and MacLisp, past the ascension and decline of special purpose Lisp machines, to the present era of standardization activities. We then examine...

The Constraint Logic Programming Scheme defines a class of languages designed for programming with constraints using a logic programming approach. These languages are soundly based on a unified framework of formal semantics. In particular, as an instance of this scheme with real arithmetic constraints, the CLP(R) language facilitates and encourages a concise and declarative style of programming for problems involving a mix of numeric and non-numeric computation. In this paper we illustrate the practical applicability of CLP(R) with examples of programs to solve electrical engineering problems. This field is particularly rich in problems that are complex and largely numeric, enabling us to demonstrate a number of the unique features of CLP(R). A detailed look at some of the more important programming techniques highlights the ability of CLP(R) to support well-known, powerful techniques from constraint programming. Our thesis is that CLP(R) is an embodiment of these techniques in a langu...

We present a method of evolving analog electronic circuits using a linear representation and a simple unfolding technique. While this representation excludes a large number of circuit topologies, it is capable of constructing many of the useful topologies seen in hand-designed circuits. Our system allows circuit size, circuit topology, and device values to be evolved. Using a parallel genetic algorithm we present initial results of our system as applied to two analog filter design problems.

A constraint is a relation among program variables that is maintained throughout execution. Type declarations and a very general form of aliasing can be expressed as constraints. A proof system based upon the interpretation of Hoare triples as temporal logic formulas is given for reasoning about programs with constraints. The proof system is shown to be sound and relatively complete, and example program proofs are given. 1 Introduction Type declarations and aliasing relations have traditionally been thought of as unrelated concepts. However, both can be viewed as specifying properties that do not change during program execution. This view leads to a uniform method for reasoning about types and aliasing in which the usual Hoare logic triples are regarded as temporal logic formulas. Aliasing two variables x and y means they always have the same value. This is usually implemented by allocating the same memory location to x # Work supported in part by the National Science Foundation unde...

Qualitative simulation is a useful method for predicting the possible qualitatively distinct behaviors of an incompletely known mechanism described by a system of qualitative differential equations (QDEs). Under some circumstances, sparse information about the derivatives of variables can lead to intractable branching (or "chatter") representing uninteresting or even spurious distinctions among qualitative behaviors. The problem of chatter stands in the way of real applications such as qualitative simulation of models in the design or diagnosis of engineered systems. One solution to this problem is to exploit information about higherorder derivatives of the variables. We demonstrate automatic methods for identification of chattering variables, algebraic derivation of expressions for second-order derivatives, and evaluation and application of the sign of second- and third-order derivatives of variables, resulting in tractable simulation of important qualitative models. Caution is requir...

Abstract—This paper presents an implementation of a decoupled optimization technique for design of switching regulators using genetic algorithms (GAs). The optimization process entails the selection of component values in a switching regulator, in order to meet the static and dynamic requirements. Although the proposed method inherits characteristics of evolutionary computations that involve randomness, recombination, and survival of the fittest, it does not perform a whole-circuit optimization. Thus, intensive computations that are usually found in stochastic optimization techniques can be avoided. Similar to many design approaches for power electronics circuits, a regulator is decoupled into two components, namely the power conversion stage (PCS) and the feedback network (FN). The PCS is optimized with the required static characteristics, whilst the FN is optimized with the required static and dynamic behaviors of the whole system. Systematic optimization procedures will be described and the technique is illustrated with the design of a buck regulator with overcurrent protection. The predicted results are compared with the published results available in the literature and are verified with experimental measurements. Index Terms—Circuit optimization, circuit simulation, computer-aided design, genetic algorithms, power electronics. I.

Abstract—Ant colony optimization (ACO) is typically used to search paths through graphs. The concept is based on simulating the behavior of ants in finding paths from the colony to food. Its searching mechanism is applicable for optimizing electric circuits with components, like resistors and capacitors, available in discrete values. However, power electronic circuits (PECs) generally consist of components, like inductors, manufactured in continuous values. Therefore, the traditional ACO algorithm cannot be applied directly. In this paper, an extended ACO (eACO) that can search the optimal values of components manufactured in discrete and continuous values is presented. The idea is based on using the orthogonal design method (ODM) to dynamically update the database of the components available with continuous values, so that these components will have pseudo-discrete values in the search space. To speed up the optimization process, the ODM performs local search of the best combination around the best ant. The eACO also takes the component tolerances into account in evaluating the fitness value of each ant. The proposed algorithm has been successfully used to optimize the design of a buck regulator. The predicted results have been compared with the published results available in the literature and verified with experimental measurements. Index Terms—Ant colony optimization (ACO), circuit optimization, orthogonal design method (ODM), power electronics circuits

We present an interactive system organized around networks of constraints rather than the programs whlch manipulate them. We describe a language of hierarchical constraint networks. We descrlbe one method of deriving useful consequences of a set of constraints whlch we all propagation. Dependency analysis is used to spot and track down inconsistent subsets of a constraint set. Propagation of constraints is most flexible and useful when coupled with the abi1ty to perform symbolic manipulations on algebraic expressions. Such manipulatons are in turn best expressed as alterations or augmentations of the constraint network. Numerous diagrams ornament the text.

We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.