Robotics represents today's highly integrated, representative high-tech field, which combines multiple disciplines. Including mechanical engineering, computer technology, control engineering, electronics, biology and other multidisciplinary intersections and integrations, reflecting the advanced level of today's practical science and technology.
In general, the robot consists of several parts, which are mechanical parts (generally referred to as mechanical arms connected by joints), sensing parts (including measuring devices for measuring position, speed, etc.), and control parts (for transmission The measurement signal from the sensing part is processed and given the corresponding control function).
As the "brain" of robots, the importance of robot control technology is self-evident.
It mainly uses the information transmitted by the sensing and other parts, and adopts the control algorithm to make the mechanical part complete the target operation and bear the corresponding part of the corresponding control function. The ultimate goal is to minimize the deviation of the actual motion trajectory of the robot from the desired target to achieve the desired motion accuracy.
The robot controller is a computer control system based on the theory of robot control technology, coupled with the kinematics and dynamics modeling of the robot. At this time, we transform a complex and abstract physical model into a relatively clear and concrete mathematical model. Once established, we will separate the control problem from the specific robot device to a certain extent. Make further understanding.
With the evolution of robot-related science and technology, control algorithms have gradually become richer, resulting in many new control strategies such as adaptive control, self-tuning control, robust control, variable structure control, nonlinear system control, and predictive control.
However, among the many excellent control algorithms, the most active ones are PID (proportional, integral, differential) control, and many advanced control strategies are also developed based on PID control algorithms.
In the development process of system control in production process, PID control is one of the oldest and most powerful basic control methods in history. It was the only control method before the 1940s, except that switch control could be used in the simplest case.
In the 20th century, communication technology and electronic technology began to develop. At the same time, war and industry have also become the driving force, and the theory of automatic control technology and automatic control has begun to develop rapidly. The birth of PID stems from human research on feedback systems.
In the 1920s, scientists at the Bell Telephone Laboratory in the United States gradually established a frequency characteristic analysis method for the feedback control system. Engineers with a communications background in Bell Labs are often familiar with the frequency domain approach.
In 1932, H. Nyquist published a paper using a graphical method to judge the stability of the system. This method was later used for the analysis and design of automatic control systems. After that, the feedback control principle began to be applied to industrial processes.
(American physicist Nyquist)
In 1934, the MIT MIT professor founded the servo control theory and first proposed the importance of trajectory tracking in feedback control. Two years later, British A. Callender and A. Stevenson gave the PID controller method.
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