Autonomous Mini Rally Car Teaches Itself to Powerslide
A mini rally car with high-power graphics processing unit (GPU) that the vehicle carries is able to control and decide the trajecoryaround a muddy/dirty racing ground, see this video.
They call the algorithm Model Predictive Path Integral (MPPI) Control which continuously samples data coming from global positioning system (GPS) hardware, inertial motion sensors, and other sensors. The onboard hardware-software system performs real-time analysis of a vast number of possible trajectories (2560) and relays optimal handling decisions to the vehicle moment by moment. If you look at the video it is able to power slide in the corners. The MPPI approach combines both the planning and execution of optimized handling decisions into a single highly efficient phase. It’s regarded as the first technology to carry out this computationally demanding task; in the past, optimal- control data inputs usually is not processed in real time.
A very large scale application of control theory
One way to reduce the impact of climate change is called geo-engineering, which could be a controversial topic. However, one branch is called ”solar radiation management”. This paper uses control theory to address the topic of uncertainty in the process model, in this case the planet earth. The main idea is to use feedback to reduce the large amount of uncertainty in the model.See this paper
Control before the ”digital control” era
Torpedoes was using a pendulum-and-hydrostat controller for the , which was a PD-controller for the right depth. The hydrostat sensor measured the pressure and the pendulum the angle to the gravity vector (derivative action), see this article.