Proportional-integral-derivative Control Loops Research Articles

Backswimmer‐Inspired Miniature 3D‐Printed Robot with Buoyancy Autoregulation through Controlled Nucleation and Release of Microbubbles

The backswimmer is an aquatic insect, capable of regulating its buoyancy underwater. When it enters the water, it entraps an air bubble in a superhydrophobic hairy structure covering its abdomen. While this bubble is mainly used for respiration, it also functions as an external inflatable gas reservoir for buoyancy regulation. Namely, hemoglobin is used to store and release oxygen to the entrapped bubble, reversibly. This way, it can reach neutral buoyancy without further energy consumption. Herein, a small, centimeter‐scale, backswimmer‐inspired untethered robot (BackBot) with autobuoyancy regulation through controlled nucleation and release of microbubbles is developed. The bubbles nucleate and grow directly on onboard electrodes through electrolysis, regulated by low voltage. A bubble‐entrapping 3D‐printed canopy is introduced to create a stable external gas reservoir. To reduce buoyancy forces, the bubbles are released through linear mechanical vibrations of the canopy, decoupled from the robot's body. Through pressure sensing and a proportional integral derivative control loop mechanism, the robot autoregulates its buoyancy to reach neutral floatation underwater within seconds. This mechanism can promote the replacement of traditional, and physically larger, buoyancy regulation systems such as pistons and pressurized tanks, and enables the miniaturization of autonomous underwater vehicles.

An efficient PID-based optimizer loop and its application in De Jong’s functions minimization and quadratic regression problems

The Proportional–Integral–Derivative (PID) control law has been commonly used for process control in control engineering applications. However, it has potential to work as a solver in optimization problems. This study introduces a PID-based optimizer loop that is designed to solve nonlinear, unconstrained, multi-parameter optimization problems. To achieve the minimization of multi-parameter positive real objective functions by using a closed loop PID control loop, a slope sentient objective function model is suggested to allow zero-crossing of the error signal. Thus, this objective function model enhances the convergence efficiency of the PID-based optimizer loop by indicating slope direction of the objective function and operating in both positive and negative error regions. The boundedness and convergence theorems for the proposed PID optimizer loop are presented, and a theoretical background for the PID-based minimization is established. To demonstrate practical minimization performance, numerical applications of the proposed PID optimizer loops are illustrated in the solution of two fundamental optimization problems. These are the minimization of 30 parameters De Jong’s functions and the solution of quadratic regression problems. Also, an experimental study is presented for the quadratic regression modeling of measurement data from a hole-drilling experiment. Optimization results reveal that the proposed PID-based optimizer system can improve convergence speed and accuracy compared to performances of fundamental nonlinear optimization techniques. • A novel closed loop PID-based optimizer system is proposed to solve optimization problems. • The proposed PID optimizer loop uses a slope sentient objective function model. • The slope sentient objective function model provides slope direction info. • The PID optimizer loop is compared with gradient-based optimization methods. • Test results indicate improved minimization performance of PID optimizer loops.

Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations

Due to unpredictable and fluctuating conditions in real-world control system applications, disturbance rejection is a substantial factor in robust control performance. The inherent disturbance rejection capacity of classical closed loop control systems is limited, and an increase in disturbance rejection performance of single-loop control systems affects the set-point control performance. Multi-loop control structures, which involve model reference control loops, can enhance the inherent disturbance rejection capacity of classical control loops without degrading set-point control performance; while the classical closed Proportional Integral Derivative (PID) control loop deals with stability and set-point control, the additional model reference control loop performs disturbance rejection control. This adaptive disturbance rejection, which does not influence set-point control performance, is achieved by selecting reference models as transfer functions of real control systems. This study investigates six types of multi-loop model reference (ML-MR) control structures for PID control loops and presents straightforward design schemes to enhance the disturbance rejection control performance of existing PID control loops. For this purpose, linear and non-linear ML-MR control structures are introduced, and their control performance improvements and certain inherent drawbacks of these structures are discussed. Design examples demonstrate the benefits of the ML-MR control structures for disturbance rejection performance improvement of PID control loops without severely deteriorating their set-point performance.

Assessment of Proportional Integral Derivative Control Loops for Large Dominant Time Constant Processes

Abstract This manuscript deals with the assessment of parallel form of proportional integral derivative (PID) control structure for tracking the reference input designed for large dominant time constant processes whose dynamics are slow (integrating processes). The theoretical bound of integral absolute error (IAE) which is established for unstable first order process is extended to pure integrating process without using any approximations. This relies on direct synthesis tuning (DS) and the theoretical bound is obtained from the transfer function of closed loop system subjected to ramp input changes. An error based performance index is formulated on the basis of this IAE theoretical bound and actual IAE, to measure the behaviour of the controller employed for non self regulating (integrating) processes. This error based index evaluates the performance of closed loop controller and specifies whether the controller requires retuning or not. A sequence of simulated examples is used to illustrate the benefit and effectiveness of this new performance assessment method.

Dynamic Modularity Approach to Adaptive Control of Robotic Systems With Closed Architecture

Modern applications of robotics typically involve a robot control system with an inner PI (proportional-integral) or PID (proportional-integral-derivative) control loop and an outer user-specified control loop. The existing outer loop controllers, however, do not take into consideration the dynamic effects of robots and their effectiveness relies on the ad hoc assumption that the inner PI or PID control loop is fast enough, and other torque-based control algorithms cannot be implemented in robotics with closed architecture. This paper investigates the adaptive control of robotic systems with an inner/outer loop structure, taking into full account the effects of the dynamics and the system uncertainties, and both the task-space control and joint-space control are considered. We propose a dynamic modularity approach to resolve this issue, and a class of adaptive outer loop control schemes is proposed and their role is to dynamically generate the joint velocity (or position) command for the low-level joint servoing loop. Without relying on the ad hoc assumption that the joint servoing is fast enough or the modification of the low-level joint controller structure, we rigorously show that the proposed outer loop controllers can ensure the stability and convergence of the closed-loop system. We also propose the outer loop versions of several standard joint-space direct/composite adaptive controllers for rigid or flexible-joint robots, and a promising conclusion may be that most torque-based adaptive controllers for robots can be designed to fit the inner/outer loop structure by using the new definition of the joint velocity (or position) command. Simulation results are provided to show the performance of various adaptive outer loop controllers, using a three-DOF (degree-of-freedom) manipulator, and experiment results using the UR10 robotic system are also presented.

Interactive Tool for Frequency Domain Tuning of PID Controllers

This paper presents an interactive tool focused on the study of proportional-integral-derivative (PID) controllers. Nowadays, PID control loops are extensively used in industrial applications. However, it is reported that many of them are badly tuned. From an educational point of view, it is essential for undergraduate students in control engineering to understand the importance of tuning a control loop correctly. For this reason, the tool provides different PID tuning methods in the frequency domain for stable open-loop time-delay-free processes. The different designs can be compared interactively by the user, allowing them to understand concepts about stability, robustness, and performance in PID control loops. A survey and a comparative study were performed to evaluate the effectiveness of the proposed tool.

Differential Drive Adaptive Proportional-Integral-Derivative (PID) Controlled Mobile Robot Speed Synchronization

In this paper we present the implementation of proportional integral derivative (PID) controlled mobile robot. we propose a mobile robot control method which based on optical encoder. First, the mobile robot counts the number of pulses from optical sensor. This system rejects the denouncing and optical sensor noises and makes a precise count of both the wheel rotation at the same time. Then through an adaptive PID control loop it controls the speed of both the motors to reach user defined set point. PID auto tuning methods are performed in different situations like on air, on ground and with load increase. This system detects the situation the robot at present and switches between its different modes to achieve the quickest maximum efficiency. Speed of each motor is controlled by Pulse Width Modulation (PWM). Finally, we experiment in a real environment, and verify the utility of the propose method.

Note: Split PID control--two sensors can be better than one.

The traditional proportional-integral-derivative (PID) algorithm for regulation suffers from a tradeoff: placing the sensor near the sample being regulated ensures that its steady-state temperature matches the desired setpoint. However, the propagation delay (lag) between heater and sample can limit the control bandwidth. Moving the sensor closer to the heater reduces the lag and increases the bandwidth but introduces offsets and drifts into the temperature of the sample. Here, we explore the consequences of using two probes-one near the heater, one near the sample-and assigning the integral term to the sample probe and the other terms to the heater probe. The split-PID algorithm can outperform PID control loops based on one sensor.

Performance Analysis and FPGA Implementation of Digital PID Controller for Speed Control of DC Motor

This paper deals with the performance analysis and implementation of PID(Proportional-Integral-Derivative) Controller on FPGA platform.The hardware implementation has been done on Xilinx Spartan 3E FPGA board.The software implementation has been done using Xilinx ISE 8.1i as a tool and simulation is performed using ModelSim 5.4a as a simulator.The PWM signal is generated by FPGA board,which further given to dc motor for its speed control. A new technique has been introduced for the generation of the control input as a PWM signal for controlling the motor driver circuit and decoding the optical encoder data for using it for the speed feedback in the PID control loop. The VHDL algorithm for the proposed implementation has been presented in this paper. Performance analysis of PID controller using MATLAB software shows the effectiveness of the proposed method.

Development of plasma control system for divertor configuration on QUEST

A plasma control system to sustain divertor configurations is developed on QUEST (Q-shu university experiment with steady-state spherical tokamak). Magnetic fluxes are numerically integrated at 100kHz using FPGA (Field-Programmable Gate Array) modules and transferred to a main calculation loop at 4kHz. With these signals, plasma shapes are identified in real time at 2kHz under the assumption that the plasma current can be represented as one filament current. This calculation is done in another calculation loop in parallel by taking advantage of a multi-core processor of the plasma control system. The inside and outside plasma edge positions are controlled to their target positions using PID (proportional-integral-derivative) control loops. Whereas the outside edge position can not be controlled by the outer PF coil current, the inside edge position can be controlled by the inner PF coil current.

Monitoring and retuning of low-level PID control loops

In this work, we focus on the problem of monitoring and retuning of low-level proportional-integral-derivative (PID) control loops used to regulate control actuators to the values computed by advanced model-based control systems like model predictive control (MPC). We consider the case where the real-time measurement of the actuation level is unavailable, and thus PID controller monitoring has to be achieved on the basis of process state measurements. A fault detection and isolation (FDI) method involving process models and real-time process measurements is used to monitor the PID control loops and compute appropriate residuals. Once poor tuning is detected and isolated, a PID tuning method based on the estimated transfer function of the control actuator is applied to the isolated, poorly functioning PID controller. An example of a non-linear reactor–separator process operating under MPC with low-level PID controllers regulating the control actuators is used to demonstrate the approach.

Comparative study of linear and non-linear integrated control schemes applied to a Buck converter for mobile applications

Energy-efficient conversion of DC voltages is gaining more and more importance in low-power applications, especially in mobile and wireless systems. Several control techniques can be applied to achieve output regulation of a Buck DC-DC converter. In this paper a linear PID (proportional-integral-derivative) control loop, both in analog and digital domain, is derived and its performance is compared to a non-linear regulation loop based on the sliding-mode theory. A goal of this paper is to point out potential advantages and drawbacks of the different solutions. This exploration forms the starting point for the implementation of the most promising concepts in a 65 nm CMOS technology.

Focus on vacuum and cryogenics

Focus on vacuum and cryogenics

Automated Feedback Control of an Inhalation Exposure System with Discrete Sampling Intervals: Testing, Performance, and Modeling

The application of a proportional-integral-derivative (PID) control algorithm to an inhalation exposure system using a building automation system is described. Previous studies had utilized a control system in which concentration was monitored continuously and adjustments to the generator were made on a continuous basis. In this system, benzene vapor was generated into a chamber, and a gas chromatograph was used to measure the concentration in a chamber at discrete 30-min intervals. Thus only limited opportunities were available to sample and adjust the vapor generator flow rate. A series of tests were conducted in which the generator was operated without control, with control, with an additional load, and with nonoptimal settings. The results showed that the PID control loop could function effectively to restore a system back to the target set point, even with an additional load on the system. With nonoptimal control settings, the system showed oscillatory behavior. A model to simulate operation of the chamber was developed on a spreadsheet program. The model was accurate at simulating the various testing scenarios and useful for selecting the proper control settings. A PID feedback control system operating with a concentration monitoring system that sampled on a 30-min cycle was shown to produce exposures that were accurate in matching the target set point and maintaining a constant concentration.

Automated Feedback Control of an Inhalation Exposure System with Discrete Sampling Intervals: Testing, Performance, and Modeling

The application of a proportional-integral-derivative (PID) control algorithm to an inhalation exposure system using a building automation system is described. Previous studies had utilized a control system in which concentration was monitored continuously and adjustments to the generator were made on a continuous basis. In this system, benzene vapor was generated into a chamber, and a gas chromatograph was used to measure the concentration in a chamber at discrete 30-min intervals. Thus only limited opportunities were available to sample and adjust the vapor generator flow rate. A series of tests were conducted in which the generator was operated without control, with control, with an additional load, and with nonoptimal settings. The results showed that the PID control loop could function effectively to restore a system back to the target set point, even with an additional load on the system. With nonoptimal control settings, the system showed oscillatory behavior. A model to simulate operation of the chamber was developed on a spreadsheet program. The model was accurate at simulating the various testing scenarios and useful for selecting the proper control settings. A PID feedback control system operating with a concentration monitoring system that sampled on a 30-min cycle was shown to produce exposures that were accurate in matching the target set point and maintaining a constant concentration.

Feedback control of substrate temperature during the growth of near-lattice-matched InGaAs on InP using diffuse reflection spectroscopy

Diffuse reflection spectroscopy (DRS) is used to control substrate temperature to within ±2°C of user specified setpoint during the growth of near-lattice-matched InGaAs on InP. The same growth under constant thermocouple control would result in a 50°C rise in real substrate temperature. Feedback control is achieved using a nested proportional-integral-derivative (PID) control loop; the inner loop consists of a conventional Eurotherm-thermocouple feedback loop that controls the substrate heater power; the outer loop updates the thermocouple setpoint based on the difference between the user setpoint and the substrate (DRS) temperature using a PID control loop implemented in the control software. Frequency loop shaping, based on a dynamical model of the system obtained from an identification experiment, is used to tune the outer PID loop. In addition, the thermal disturbances that occur during effusion cell shutter operations must be rejected. In the simplest case, a single correcting step in the Eurotherm (thermocouple) setpoint is input when a shutter is toggled. Through disturbance identification and model inversion a more sophisticated disturbance rejection action from the controller can be obtained.

Closed-loop control of composition and temperature during the growth of InGaAs lattice matched to InP

Spectroscopic ellipsometry (SE) and diffuse reflection spectroscopy (DRS) are used to control the Ga mole fraction and substrate temperature, respectively, during the growth of InGaAs lattice matched to InP. Ga mole fraction is controlled to within ±0.002 of its target value and substrate temperature is controlled to within ±2 °C of its target value. The same growth under constant thermocouple control would result in a 50 °C rise in real substrate temperature and a Ga composition 1% above its target value. In both cases, feedback control is achieved using a nested proportional-integral-derivative (PID) control loop, where, the inner loop consists of the conventional Eurotherm-thermocouple feedback loop and the outer loop updates the thermocouple setpoint using a PID control loop implemented in the control software. For composition control, the Ga cell thermocouple setpoint is increased (decreased) 0.2 °C for every 0.002 that the Ga mole fraction, given by the SE sensor, deviates below (above) the target value. During substrate temperature control, the thermocouple setpoint is updated based on the temperature difference between the DRS sensor and the user setpoint. Frequency loop shaping, based on a dynamical model of the system obtained from an identification experiment, is used to tune the outer PID loop.

Neural Control of the Movements of a Wheelchair

This paper studies the problem of controlling the movements of a handicapped person‘s motorized wheelchair from a practical point of view. The control system implemented has been divided into two levels: the “low level”, consisting of an electronic system which directly controls the drivers of the chair‘s motors, with a classic PID (proportional-integral-derivative) control loop. The aim of this level is to ensure that the speeds of each one of the wheels is similar to the input speed of these control boards. The second control level (“high level”), implemented by means of neural techniques, ensures that the linear and angular speeds of the wheelchair are those indicated by a trajectory generator. A new recurrent model is used as the neural network, for which the stability conditions of the complete control system are obtained and various practical tests are carried out, which show the correct performance of the actual system implemented.