"The objective is to develop a model or algorithm governing the application of system inputs to drive the system to a desired state, while minimizing any delay, overshoot, or steady-state error and ensuring a level of control stability; often with the aim to achieve a degree of optimality."
The study of systems that use feedback to control the behavior of physical and electrical systems. Includes feedback systems, PID controllers, and other control theory techniques.
System Modeling: The process of creating mathematical representations of dynamic systems.
Laplace Transform: The mathematical tool used for transforming differential equations of continuous-time systems.
Transfer Function: The mathematical representation of the relationship between the input and output signals of a control system.
Block Diagrams: Graphical representation of a control system using interconnected blocks to represent the system components.
Feedback Control: The process of adjusting system output based on measured or calculated errors.
Closed-Loop Control: A system in which the output is compared to the reference input signal and fed back to the system's input to reduce errors.
Open-Loop Control: A system in which the output is not compared to the reference input signal and no feedback mechanism is employed.
Stability Analysis: The study of a control system's stability in response to disturbances and variations in input or feedback signals.
Root Locus: Graphical representation of a control system's poles and zeros in the s-plane, used to analyze stability and performance.
Frequency Response: The relationship between a control system's output and input signals over a range of frequencies.
Bode Plot: A graphical representation of a control system's frequency response, used to analyze stability and performance.
Nyquist Plot: A graphical representation of a control system's frequency response in the complex plane, used to analyze stability and performance.
State-Space Analysis: A method for analyzing control systems in terms of their internal states and their evolution over time.
Design of Controllers: The process of designing and implementing controllers to achieve desired system performance.
PID Controllers: A popular class of controllers that use proportional, integral, and derivative terms to adjust the system output.
Robust Control: A control system design philosophy that aims to ensure stability and performance in the presence of uncertainty and/or disturbances.
Adaptive Control: A control system design philosophy that aims to adjust system parameters dynamically based on changes in the control system or environment.
Nonlinear Control: A set of techniques used to control nonlinear systems, which cannot be effectively controlled using linear control techniques.
Open-loop control system: A control system in which the output is not fed back to the input.
Closed-loop control system: A control system in which the output is fed back to the input to regulate the system's performance.
Linear control system: A control system that follows the principle of superposition, which means that the output is proportional to the input.
Nonlinear control system: A control system that does not follow the principle of superposition.
Time-invariant control system: A control system whose characteristics do not change with time.
Time-varying control system: A control system whose characteristics change with time.
Feedback control system: A control system that uses feedback loops to regulate the system's performance.
Feedforward control system: A control system that anticipates changes and adjusts the output before the changes occur.
Proportional control system: A control system that varies the output proportionally to the input.
Integral control system: A control system that eliminates steady-state errors.
Derivative control system: A control system that reacts to the rate of change of the input.
Proportional-integral-derivative (PID) control system: A control system that combines proportional, integral, and derivative control to achieve optimal performance.
Fuzzy control system: A control system that uses fuzzy logic to regulate the output.
Adaptive control system: A control system that adjusts its performance based on changes in the system.
Robust control system: A control system that is designed to operate in non-ideal conditions.
Optimal control system: A control system that achieves optimal performance with limited resources.
Predictive control system: A control system that predicts future changes and adjusts the output accordingly.
Model-based control system: A control system that uses a mathematical model of the system to regulate the output.
State-space control system: A control system that represents the system's behavior in terms of state variables.
Digital control system: A control system that operates on discrete-time signals.
"To do this, a controller with the requisite corrective behavior is required. This controller monitors the controlled process variable (PV), and compares it with the reference or set point (SP)."
"The difference between actual and desired value of the process variable, called the error signal, or SP-PV error, is applied as feedback to generate a control action to bring the controlled process variable to the same value as the set point."
"Other aspects which are also studied are controllability and observability."
"Control theory is used in control system engineering to design automation that have revolutionized manufacturing, aircraft, communications and other industries, and created new fields such as robotics."
"Extensive use is usually made of a diagrammatic style known as the block diagram."
"In it the transfer function, also known as the system function or network function, is a mathematical model of the relation between the input and output based on the differential equations describing the system."
"Control theory dates from the 19th century, when the theoretical basis for the operation of governors was first described by James Clerk Maxwell. Control theory was further advanced by Edward Routh in 1874, Charles Sturm and in 1895, Adolf Hurwitz, who all contributed to the establishment of control stability criteria; and from 1922 onwards, the development of PID control theory by Nicolas Minorsky."
"Although a major application of mathematical control theory is in control systems engineering, which deals with the design of process control systems for industry, other applications range far beyond this."
"Control theory also has applications in life sciences, computer engineering, sociology and operations research."