Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Managing large-enrollment courses in hybrid instruction mode

This essay addresses the hitches and glitches in the hybrid instruction system of teaching and learning for large-enrollment courses. This new instructional methodology asks facilitators to redesign their entire traditional teaching and learning practices. The nature of subject to be taught via the hybrid mode further affects the success rate of the modules from the time of inception to launch to actual delivery and completion of the course. The entire process involves undoing the old habits and methodologies and instructors picking up new skills, along with the right motivation to take up the task. The course planning and delivery require a substantial commitment in terms of hours from the instructors catering to large-enrollment courses, along with pursuing their routine roles at the campuses. From the pupil’s perspective, the response varies, as hybrid learning seeks self-discipline and time management skills from the learner. After the initial roadblocks, students enjoy hybrid learning if the course structure and instructions are simple and the course content flexible and varied. We will study the problems and possible solutions to the success of the hybrid teaching–learning system at each stage where large number of students enrolled for a specific course.