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
【High-pass filter】 Lagged derivative
【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 , Octave analysis
■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 , Transformer , DC-DC converter , AC-DC converter , Inverter , Solenoid valves, relay , Switch type , 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 , Lagrange's Method of Undetermined Multipliers
■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 , Program, script , Image filter, padding
■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 ,
Radial and thrust directions , Air conditioner, chiller , Cornering force
■Chemistry
Lithium ion batteries , Polarization, overpotential, OCV, CCV , Voltaic battery, Daniel battery
■Python
【library】 pip , MeCab
【common】 pickle , class
【numpy】 digitize , mgrid , pad , poly1d , 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
■Scilab
Basic usage of XCOS
■Excel
【Setting】 Added Data Analysis tab