A nice feature of the LEGO system is that, although the mechanical, electrical, and structural construction is good enough for successful results, there are enough discrepancies between theory and practice to introduce the student to real-world problems of controller. This article concentrates on implementing the feedback controller within the RCX, with the host computer used for compiling, downloading, and data display. However, an interesting research project is to implement part of the controller on the host computer and communicate by means of the IR channel. The bandwidth restriction that this approach imposes can provide the basis for a research project on control through a restricted bandwidth channel.

In this article, the optimisation of the weighting functions for an H _∞ controller using genetic algorithms and structured genetic algorithms is considered. The choice of the weighting functions is one of the key steps in the design of an H _∞ controller. The performance of the controller depends on these weighting functions since poorly chosen weighting functions will provide a poor controller. One approach that can solve this problem is the use of evolutionary techniques to tune the weighting parameters. The article presents the improved performance of structured genetic algorithms over conventional genetic algorithms and how this technique can assist with the identification of appropriate weighting functions’ orders.

A genetic algorithm (GA) optimization application is presented in this paper. It involves the performance optimization of a navigation system for a nonlinear tanker model. This navigation system is fully autonomous and regulates the heading of the vessel with reference to a desired course made up of waypoints. The system consists of two components. The first is a line of sight (LOS) autopilot, which determines the desired heading of the tanker from positional information. The second is a heading control system that is derived from sliding mode (SM) control theory. In this investigation the GA is used to optimize the parameters for the SM controller so that the performance of the complete system satisfies specific design criteria. The resulting optimized navigation system is evaluated for different operating conditions for the tanker, e.g., different course, different forward velocities.