Basics of control engineering, this and that


In Japanese

■At first
I will explain the basics of control engineering such as PID control and modern control, and the physics, mathematics, tools, etc, required for control engineering. To briefly explain my profile, I work for an automobile-related company, where I design and develop while using control engineering. I think that the content explained here should be understood at least when dealing with control theory and actually implementing it in things. I would be delighted if I could contribute to the improvement of everyone's academic ability and the development of humankind.

I keep the following in mind when explaining the content.

1. Make it as simple as possible. I will explain the content accurately with less sentences.

2. I don't increase the volume of one-page articles

3. The font of the characters is not too big and there is no space between lines.(If the screen scrolls frequently, it becomes difficult to understand information)

4. I don't post image diagrams that are not directly related to the explanation of the contents.

This site is link-free. However, please note that if there is a mistake in the content, we will not be responsible for any disadvantage caused by using the information. And I'm not good at English.

■Crassical Control
【PID Gain tuning】Ultimate sensitivity method , Step response method , Pole placement method:2nd order delay + PID 【Application】I-PD type control , PD-D type control , Velocity type PID , Internal Model Control , Filtered derivative

■Modern Control Modern control is
【State equation】Derivation of state equation 【Observer】State observer , Disturbance observer , Kalman filter , Kalman gain , Transfer function of the state equation

■Control theory
Transfer function , Transfer function synthesis , Closed-loop/Open-loop transfer function 【Low-pass filter】first-order delay:transfer function , bode plot , second-order delay:Bode plot , Butterworth Filter , Bessel Filter 【All-pass filter】transfer function , Pade approximation 【Band-stop filter】Notch filter , Band-pass filter

■Digital signal processing
Frequency analysis method, Calculate the Fourier transform, Detrending method , Sampling theorem, DC component, Floating point number, Bilinear transform, Resolution, sampling period , Fixed point number , Digital filter

■Electrical/Electronic circuit
Freewheeling Diode , Alternating Current, Termination resistor, IC related terms, Adders, Subtractors , H-bridge , Motor type , ROM, RAM, register, cash, Open/short circuit failures , High/low-side driver, Mechanism of electric shock , Zener diode , Rectifier circuit , Pull-up/pull-down resistors , Joule heat , DC-DC converter , AC-DC converter , Inverter , Solenoid valves, relay , Comparator

■Communication technology
【Serial communication】CAN,LIN communication, SENT communication , USB communication, Ethernet, SPI, Data transfer speed, Parity check, Check sum, Cyclic redundancy check , Clock synchronous, Asynchronous methods , Differential Signaling 【Network communication】Message authentication, Digital signature

■Mechanics
Force, torque, work, power , Aacceleration, angular acceleration , Mass-spring-damper model , Moment of inertia , inverted pendulum , Differential eq. for motors and disks , Slope angle , Frictional force

■Thermodynamics, fluid mechanics
Heat transfer coefficient, Heat quantity

■Electromagnetism
Electromagnetic induction

■Mathematics
Exponential, Power function , Arctangent and Hyperbolic Tangent , Matrix multiplication , Transposed matrix , Fourier Transform , Fast Fourier Transform , Matrix derivative , Manhattan/Euclidean distance , Centroid , Vertical bar , Gaussian integral formula , Cosine similarity , summation Σ, product Π , Decibel , Numerical differentiation , induction, deduction, abduction , Spline curve

■Probability / Statistics
Expected value , Weighted/moving average , Root Mean Square , Variance, Standard deviation, Covariance , least squares formula , Joint probability, Conditional probability , Weibull distribution , Gaussian process regression , Basis functions , Kernel function

■Machine learning
ε-greedy method , Reinforcement learning , Temporal Difference learning , Regression vs Classification vs Clustering , Parametric model vs Nonparametric model , LSTM , Error function , Experience replay

■Software
Horner's rule , Web image download , Validation, Verification , Affine transformation

■Automotive engineering
Fuel injection amount , Running resistance , Vehicle acceleration , Alternator , IMEP vs BMEP , Model year , Roll, Pitch, Yaw , Turning radius of vehicle , Torque and Power , Engine vs vehicle speed , WLTP, WLTC , OBD , Tire size , Failsafe, failproof , Water/Buttock/Transverse Line , Gears, splines

■Chemistry
Lithium ion batteries , Polarization, overpotential, OCV, CCV , Voltaic battery, Daniel battery

■Python
【library】pip , MeCab 【numpy】digitize , mgrid , pad , polyfit , prod , shape 【matplotlib】figure , pcolormesh , scatter 【pytorch】BCELoss, MSELoss, device, Embedding, TensorDataset, Dataloader, RNN, LSTM 【sklearn】SVC 【scipy】interpolate 【tkinter】postscript , image display , frame, grid 【OpenAI gym】CartPole-v0 【other】linear interpolation

■Excel
【Setting】Added Data Analysis tab