[Jason] learned a lot by successfully automating this meat smoker. This is just the first step in [Jason’s] smoker project. He decided to begin by hacking a cheaper charcoal-fed unit first, before setting his sights on building his own automatic pellet-fed smoker. With a charcoal smoker it’s all about managing the airflow to that hot bed of coals.
[Jason] started by making sure the bottom was sealed off from stray airflow, then he cut a hole into the charcoal pan and attached a length of steel pipe. The opposite end of the pipe has a fan. Inside the pipe there is a baffle separating the fan from the charcoal pan. The servo motor shown here controls that valve.
The pipe is how air is introduced into the smoker, with the fan and valve to control the flow rate. The more air, the higher the temperature. The hunk of pipe was left uncut and works fine but is much longer than needed; [Jason says] the pipe is perfectly cool to the touch only a foot and a half away from the smoker.
With the actuators in place he needed a feedback loop. A thermocouple installed into the lid of the smoker is monitored by an Arduino running a PID control loop. This predicts the temperature change and adjusts the baffle and fan to avoid overshooting the target temp. The last piece of hardware is a temperature probe inside the meat itself. With the regulation of the smoker’s temperature taken care of and the meat’s internal temperature being monitored, the learning (and cooking) process is well underway.
There are many, many smoker automation projects out there. Some smokers are home-made electric ones using flower pots, and some focus more on modifying off the shelf units. In a way, every PID controlled smoker is the same, yet they end up with different problems to solve during their creation. There is no better way to learn PID than putting it into practice, and this way to you get a tasty treat for your efforts.
The Brasilia Lady comes with a 300 ml brass boiler, a pump and four buttons for power, coffee, hot water and steam. A 3-way AC solenoid valve, wired directly to the buttons, selects one of the three functions, while a temperamental bimetal switch keeps the boiler roughly between almost there and way too hot.
To reduce the temperature swing, [Rhys] decided to add a PID control loop, and on the way, an OLED display, too. He designed a little shield for the Arduino Nano, that interfaces with the present hardware through solid state relays. Two thermocouples measure the temperature of the boiler and group head while a thermal cut-off fuse protects the machine from overheating in case of a malfunction.
Also, the Lady’s makeup received a complete overhaul, starting with a fresh powder coating. A sealed enclosure along with a polished top panel for the OLED display were machined from aluminum. [Rhys] also added an external water tank that is connected to the machine through shiny, custom lathed tube fittings. Before the water enters the boiler, it passes through a custom preheater, to avoid cold water from entering the boiler directly. Not only does the result look fantastic, it also offers a lot more control over the temperature and the amount of water extracted, resulting in a perfect brew every time. Enjoy [Rhys’s] video where he explains his build:
Your quad-copter is hovering nicely 100 feet north of you, its camera pointed exactly on target. The hover is doing so well all the RC transmitter controls are in the neutral position. The wind picks up a bit and now the ‘copter is 110 feet north. You adjust its position with your control stick but as you do the wind dies and you overshoot the correction. Another gust pushed it away from target in more than one direction as frustration passes your lips: ARGGGHH!! You promise yourself to get a new flight computer with position hold capability.
How do multicopters with smart controllers hold their position? They use a technique called Proportional – Integral – Derivative (PID) control. It’s a concept found in control systems of just about everything imaginable. To use PID your copter needs sensors that measure the current position and movement.
The typical sensors used for position control are a GPS receiver and an Inertial Management Measurement Unit (IMU) made up of an accelerometer, a gyroscope, and possibly a magnetometer (compass). Altitude control would require a barometer or some other means of measuring height above ground. Using sensor fusion techniques to combine the raw data, a computer can determine the position, movement, and altitude of the multicopter. But calculating corrections that will be just right, without over or undershooting the goal, is where PID comes into play. Continue reading “Flying with Proportional – Integral – Derivative Control”→
If you have a good sense of balance, you can ride a unicycle or get on TV doing tricks with ladders. We don’t know if [Hanna Yatco] has a good sense of balance or not, but we do know her Arduino does. Her build uses the ubiquitous HC-SR04 SONAR sensor and a servo.
This is a great use for a servo since a standard servo motor without modifications only moves through part of a circle, and that’s all that’s needed for this project. A PID algorithm measures the distance to the ball and raises or lowers a beam to try to get the ball to the center.
Laying hands on the supplies for most hacks we cover is getting easier by the day. A few pecks at the keyboard and half a dozen boards or chips are on an ePacket from China to your doorstep for next to nothing. But if hacking life is what you’re into, you’ll spend a lot of time and money gathering the necessary instrumentation. Unless you roll your own mini genetic engineering lab from scratch, that is.
Taking the form of an Arduino mega-shield that supports a pH meter, a spectrophotometer, and a PID-controlled hot plate, [M. Bindhammer]’s design has a nice cross-section of the instruments needed to start biohacking in your basement. Since the shield piggybacks on an Arduino, all the data can be logged, and decisions can be made based on the data as it is collected. One example is changing the temperature of the hot plate when a certain pH is reached. Not having to babysit your experiments could be a huge boon to the basement biohacker.
This makeover didn’t end with hiding wires and locking out noobs, though. [Cameron] added a float switch that will disable the pump when the water level gets too low. This is a nice touch. Otherwise, machines like this one will try to brew when the tank is dry, and then the pump has to be primed once the tank is refilled. [Cameron] also replaced the buttons’ back-lighting bulbs with bright LEDs. A small LCD mounted on the front of the machine shows the boiler temperature and shot-pulling duration.
If you’ve add PID temperature control to your espresso machine but have done nothing to improve the steam wand, why not add a pressure gauge?
PID control loops are everywhere, found in flight controllers for drones and the temperature control code for 3D printers. How do you teach PID control loops? [Tim] has a great demonstration for this, and it’s also a semifinalist for the Hackaday Prize.
[Tim]’s Sab3t is an educational tool designed to illustrate how PID control loops work. It’s a robotic table on which a large ball bearing sits perfectly balanced. On this table is a resistive touch screen from a display providing feedback for the location of the ball bearing. By adjusting PID values, the ball bearing either sits stationary on the table or flails wildly around, depending on the values in the PID algorithm being used.
As a teaching tool, it’s great; with a python script displaying a log of the PID values and the position of the ball on the plate, anyone can easily visualize how oscillations happen, what a well-tuned control loop looks like, and have some fun moving the ball bearing around to different locations.