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Open and closed-loop control systems

Open and closed-loop control systems

Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...

Time-Domain Interpretation of PD Control

Time-Domain Interpretation of PD Control

Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...

PD Controller: Design

PD Controller: Design

In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...

Controller Configurations

Controller Configurations

Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...

Control System Problem

Control System Problem

In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...

Feedback control systems

Feedback control systems

Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...

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Related Experiment Video

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Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

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Published on: August 15, 2016

A double-loop structure in the adaptive generalized predictive control algorithm for control of robot end-point

Shuhuan Wen¹, Jinghai Zhu¹, Xiaoli Li¹

¹Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China.

ISA Transactions

|June 29, 2014

Summary

This study introduces an adaptive control algorithm for robot force control systems. The new method enhances robot end-effector performance and robustness when interacting with uncertain environments.

Keywords:

Contact force Generalized predictive control Quantitative feedback theory

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Area of Science:

Robotics
Control Systems Engineering
Artificial Intelligence

Background:

Robot force control is critical for intelligent robotics.
High uncertainty exists when robot end-effectors interact with environments, influenced by environmental stiffness.

Purpose of the Study:

To design an adaptive generalized predictive control (GPC) algorithm for robot end-point contact force systems.
To address uncertainties in robot-environment interactions using Quantitative Feedback Theory (QFT).

Main Methods:

Designed an internal loop controller using QFT to manage system uncertainty.
Developed an external loop controller utilizing an adaptive GPC algorithm.
Implemented a two-closed-loop design for enhanced system performance and robustness.

Main Results:

Simulation results demonstrate the effectiveness of the proposed control algorithm.
The dual-loop controller successfully improved system performance and robustness.

Conclusions:

The adaptive GPC algorithm based on QFT is effective for robot end-effector contact force control.
The proposed control strategy enhances robotic system reliability in uncertain environments.