Douglas C Hittle

Title: Innovations of Douglas C. Hittle

Introduction

Douglas C. Hittle is an accomplished inventor based in Fort Collins, Colorado. He has made significant contributions to the field of control systems, holding three patents that showcase his innovative approach to integrating neural networks with traditional control methods.

Latest Patents

One of Hittle's latest patents is the "Combined proportional plus integral (PI) and neural network (nN) controller." This invention features a neural network controller that operates in parallel with a proportional-plus-integral feedback controller. The system includes at least one input port for receiving signals that represent the condition of a process. During its operation, the neural network enhances the output of the PI controller when specific triggering events occur, allowing for more responsive control of the process being managed.

Another notable patent is the "Control system and technique employing reinforcement learning having stability and learning phases." This feedback control system is designed for automatic on-line training of a controller for a plant. It incorporates a reinforcement learning agent that works alongside the controller, determining multi-dimensional boundaries of values during stability phases and generating updated weight values during learning phases. This innovative approach allows for continuous improvement in the control system's performance.

Career Highlights

Douglas C. Hittle is affiliated with the Colorado State University Research Foundation, where he applies his expertise in control systems and neural networks. His work has significantly advanced the understanding and application of these technologies in various industrial processes.

Collaborations

Hittle has collaborated with notable colleagues such as Charles Anderson and Peter Michael Young. Their combined efforts have contributed to the development of cutting-edge technologies in the field of control systems.

Conclusion

Douglas C. Hittle's innovative patents and contributions to control systems demonstrate his commitment to advancing technology in this field. His work continues to influence the integration of neural networks with traditional control methods, paving the way for more efficient and responsive systems.