Implementation Of Feedback Control Research Articles

High order differential feedback controller design and implementation for a Stewart platform

Stewart platform or other parallel manipulators with a Stewart structure are commonly used in flight simulators, surgical operations, medical rehabilitation processes, machine tools, industrial applications, etc. Therefore, researchers have paid attention to position control of these manipulators in addition to their design and development process. In this study, a developed Stewart platform and its inverse kinematic analysis are presented first. Then, a model-free control scheme called a high order differential feedback controller scheme is designed for the Stewart platform in order to improve its trajectory tracking performance and robustness against to different reference trajectories. Real-time trajectory tracking experiments with varied reference trajectories are carried out to show the robustness and effectiveness of the high order differential feedback controller scheme compared to the traditional proportional–integral–derivative controller of which the parameters are optimally tuned. The obtained visual trajectory tracking results and numerical performance results based on error-based performance measurement metrics such as integral of absolute error, integral of squared error, and integral of time-weighted absolute error are provided for both the proposed high order differential feedback controller scheme and the optimal tuned proportional–integral–derivative controller. Experimental results show that the proposed high order differential feedback controller scheme is more robust than the proportional–integral–derivative controller. Furthermore, the high order differential feedback controller scheme has superiority in both transient and steady-state responses and even the parameters of the proportional–integral–derivative controller are optimally tuned.

Implementation of Feedforward and Feedback Control for Active Handling and Dribbling System in MSL Robot Soccer

Ball handling and dribbling are basics soccer techniques. Therefore, handling and dribbling mechanism becomes important component for MSL (Middle Size League) robot soccer. The implementation of active handling and dribbling systems aims to enable the robot to perform dribbling mechanism when maneuvering, while in idle position use handling mechanism. Feedforward and feedback applied as control method in active ball handling and dribbling system. Feedforward control method will give a response to the dribbler wheel based on the motion of robot movement against x, y, and θ axes. Whereas, Feedback control method applied fuzzy inference system by reading the displacement of the arm angle from sensor databased on angle reference of dribbler arm to keep the ball in an ideal position. Implementation geometric calculation for feedforward control toward x, y, and θ axes movement of the robot that it has resulted RMSE value for left motor is 5.75 and for right motor is 7.01. Fuzzy inference system method is used as a feedback control to manipulate the speed and direction of wheel’s rotation as a result ball remains in the ideal position. The value of arm angle displacement and the combination of the two-dribbler arms are used as input for fuzzy inference system. The results of this research show that the application of the combined feedforward and feedback control methods in active handling and dribbling systems can provide robot-dribbling capabilities. Consequently, the robot has a good ability in handling and dribbling mechanism.

A portable EPR system for the absolute polarimetry of noble gases

A simple and portable electron paramagnetic resonance (EPR) system has been developed for the absolute polarimetry of noble gases polarized by spin-exchange optical pumping. By using modern digital technology together with software implementation of phase-sensitive detection and feedback control, the new system has become much more compact than the conventional EPR apparatus and can be easily transported anywhere. The main components of the new EPR system are a computer and a PC-based oscilloscope with a built-in function generator. The raw signal data is processed in real time by a computer, which offers great flexibility to the new system. By modifying the data-processing algorithm, it can be customized and applied to other scientific and engineering measurements that utilize phase-sensitive detection.

Active vibration control unit with a flywheel inertial actuator

This paper presents simulation and experimental results on the implementation of a velocity feedback control unit with a new flywheel inertial actuator, which can be used to reduce flexural vibration of distributed structures. The actuator incorporates a classical coil–magnet linear transducer and a flywheel element such that both linear and rotational inertia effects are generated by the moving components of the actuator. The additional rotational inertia effect shifts to lower values the fundamental resonance frequency of the actuator without increasing the static deflection of the suspended masses. Therefore, this actuator can be conveniently used to implement feedback control units, which are robust to shocks, have enhanced stability properties and, thus, improved vibration control effects. To illustrate the key features of the proposed actuator, the characteristic electro-mechanical response functions of a classical actuator and of the flywheel actuator are first presented. Then, the stability and flexural vibration control performance of velocity feedback loops with a classical and the flywheel inertial actuators are contrasted considering a thin rectangular plate hosting structure.

Feedback control and its impact on generalist predator–prey system with prey harvesting

This article examines the effectiveness of feedback control as a management policy on a generalist predator–prey system with prey harvesting. We discuss the result of implementing feedback control with respect to prey and predator separately. This paper also depicts the effect of exploitations up to maximum sustainable yield (MSY). We observe that with a constant fishing effort MSY policy is a sustainable management policy to protect both the species. However, further increase of fishing effort may cause the extinction of prey species. But considering feedback control of fishing effort may restrict the extinction of prey species. When fishing effort is controlled in terms of prey density, the extinction of prey population can be avoided. In this case, there may be coexistences of prey, predator and fishery or extinction of fishery. But when fishing effort is controlled by predator density, it is difficult to manage the coexistences of prey, predator and fishery.

Modular and tunable biological feedback control using a de novo protein switch.

De novo-designed proteins1-3 hold great promise as building blocks for synthetic circuits, and can complement the use of engineered variants of natural proteins4-7. One such designer protein-degronLOCKR, which is based on 'latching orthogonal cage-key proteins' (LOCKR) technology8-is a switch that degrades a protein of interest in vivo upon induction by a genetically encoded small peptide. Here we leverage the plug-and-play nature of degronLOCKR to implement feedback control of endogenous signalling pathways and synthetic gene circuits. We first generate synthetic negative and positive feedback in the yeast mating pathway by fusing degronLOCKR to endogenous signalling molecules, illustrating the ease with which this strategy can be used to rewire complex endogenous pathways. We next evaluate feedback control mediated by degronLOCKR on a synthetic gene circuit9, to quantify the feedback capabilities and operational range of the feedback control circuit. The designed nature of degronLOCKR proteins enables simple and rational modifications to tune feedback behaviour in both the synthetic circuit and the mating pathway. The ability to engineer feedback control into living cells represents an important milestone in achieving the full potential of synthetic biology10,11,12. More broadly, this work demonstrates the large and untapped potential of de novo design of proteins for generating tools that implement complex synthetic functionalities in cells for biotechnological and therapeutic applications.

Implementation of real-time and in-line feedback control for a fluid bed granulation process.

The application of process analytical technologies (PAT) to monitor critical quality attributes (CQAs) provides an important approach to enhance process understanding and improve the reliability of pharmaceutical production processes. The present study focuses on the first PAT based feedback control system for a fluid bed granulation batch process. Real-time particle size measurement by in-line spatial filtering technique (SFT) using a modified time-based buffer system was applied to define a target particle size after spraying a specific amount of binder solution. After identifying an appropriate control variable, a suitable strategy for feedback control was established, followed by tuning of the control loop to obtain best performance of the integrated system. By adapting the final target particle size within a specified range good functionality of the system could be demonstrated. Investigations of the robustness further showed that the implemented system enables the production of a predefined target particle size also by varying process and formulation parameters. The effect of increasing spray rates and binder concentrations on the particle size could be compensated in a given range by feedback control ensuring a predefined product quality. The study provides an advanced approach for quality assurance of fluid bed granulation.

Sensor Placement for Optimal Control of Infinite-Dimensional Systems

An important challenge in controlling distributed parameter systems is implementing feedback control laws over an infinite-dimensional space. One widely studied approach is to place sensors at a set of discrete locations and then approximate the state feedback using the sensor outputs. This approach naturally raises the question of where the sensors should be located. In this paper, we investigate the problem of placing a set of sensors on the unit interval in order to minimize the mean-square deviation between a desired infinite-dimensional control law, and an approximate finite-dimensional controller obtained by applying state feedback at the chosen sensor positions. We propose a greedy algorithm and derive optimality bounds on the selected set of sensors. We also present a simplified greedy algorithm in which the incremental improvements from adding each sensor are not updated at each step. We analyze the performance of the approaches under two scenarios. In the case where the sensor placements are constrained such that each of the detection radii of each pair of sensors do not overlap, we show that the two algorithms are equivalent and achieve a 1/2 + ε optimality guarantee, where ε can be made arbitrarily small at the cost of increased computational overhead. When overlaps exist between sensor detection areas, we derive an optimality bound for the simplified algorithm. The value of the optimality bound is determined by the sensor model, cardinality of sensor set, and the allowed minimum sensor distance. Our approach is illustrated through numerical study, in which we compare our proposed greedy algorithm, the current state-of-the-art approach, and the true optimum obtained from exhaustive search.

Monitoring juice hold-up in a cane diffuser bed using electrical conductivity – evaluation on a plant scale

The extraction of sucrose in a sugarcane diffuser depends on the percolation rate of juice through the cane bed. High percolation rates promote mass transfer and increase the wetness of the cane bed (i.e. liquid hold-up within the bed) thereby improving sucrose extraction. However, increasing the rate of juice applied to the surface of the cane bed above the maximum percolation rate results in flooding, causing uncontrolled mixing of juice, destruction of the dry substance content profile and reduced extraction. Flooding in the diffuser can be avoided by installing feedback control of adjustable sprays that alter the application area of juice onto the bed surface and automatically keeping the percolation rate optimised. Electrical conductivity of the cane bed, measured between the bed surface and the bottom screen of the diffuser, has been investigated as a possible online indicator of juice hold-up within the cane bed to provide the necessary measurement for implementing feedback control that can optimise percolation rates. Full scale tests were conducted on the Tongaat Hulett cane diffuser at the Maidstone factory. Reproducibility tests were done to confirm that there is a relationship between conductance and liquid hold-up.

A Pedagogical Study of Aerodynamic Feedback Control by Dielectric Barrier Discharge Plasma

Active flow control by means of plasma actuators has potential advantages over conventional strategies, e.g., mechanical or hydraulic components may be replaced by lightweight, compact, fast response plasma actuators. In this paper, several designs of dielectric barrier discharge (DBD) plasma actuators are presented for aerospace applications and the focus is on the associated feedback control implementation. The interdisciplinary nature of aerodynamic feedback control with plasma, however, makes direct experimental demonstrating an outstanding challenge. Here, we propose a realistic experimental control implementation afforded by commercial off-the-shelf electric products and the major achievement is the detailed instruction (in both electricity and aerodynamics) and the successful demonstration of the closed-loop design in controlling the dominant modes from a cylinder flow setup. The essence of our approach is to drive DBD plasma actuations by a downstream sensor and excite aerodynamic velocity perturbations, which are further amplified on the shear flow from the cylinder, leading to airflow structures, such as vortex roll-up and randomization, which are measured by the downstream sensor to complete the whole loop. We benchmark our control approach by comparing to the predicted dominant frequencies of the controlled flow system, which can be achieved by the Barkhausen stability criterion after establishing the corresponding transfer function of the whole flow control system. Overall, this paper shall assist a host of new applications in aerospace applications in the near future.

An earthworm-inspired friction-controlled soft robot capable of bidirectional locomotion**Preliminary results of this work were presented at the 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO 2017).

We present the design, fabrication, modeling and feedback control of an earthworm-inspired soft robot capable of bidirectional locomotion on both horizontal and inclined flat platforms. In this approach, the locomotion patterns are controlled by actively varying the coefficients of friction between the contacting surfaces of the robot and the supporting platform, thus emulating the limbless locomotion of earthworms at a conceptual level. Earthworms are characterized by segmented body structures, known as metameres, composed of longitudinal and circular muscles which during locomotion are contracted and relaxed periodically in order to generate a peristaltic wave that propagates backwards with respect to the worm’s traveling direction; simultaneously, microscopic bristle-like structures (setae) on each metamere coordinately protrude or retract to provide varying traction with the ground, thus enabling the worm to burrow or crawl. The proposed soft robot replicates the muscle functionalities and setae mechanisms of earthworms employing pneumatically-driven actuators and 3D-printed casings. Using the notion of controllable subspace, we show that friction plays an indispensable role in the generation and control of locomotion in robots of this type. Based on this analysis, we introduce a simulation-based method for synthesizing and implementing feedback control schemes that enable the robot to generate forward and backward locomotion. From the set of feasible control strategies studied in simulation, we adopt a friction-modulation-based feedback control algorithm which is implementable in real time and compatible with the hardware limitations of the robotic system. Through experiments, the robot is demonstrated to be capable of bidirectional crawling on surfaces with different textures and inclinations.

Implementation and Evaluation of Non-linear Optimal Feedback Control for Ship’s Automatic Berthing by Recurrent Neural Network

In this paper, we present an automatic ship’s berthing system by non-linear optimal feedback controller. In the proposed method, the recurrent neural network is used for non-linear optimal feedback controller for the realistic operational conditions such as different berthing distances and different disturbances. To obtain the feasible non-linear controller, the recurrent neural network is trained using pre-computed non-linear optimal solutions for various conditions. In order to evaluate the performance of the proposed system, extensive computer simulations and actual sea tests are carried out using small training ship Shioji-Maru under various conditions. As a result, we can see that the proposed non-linear optimal feedback controller by recurrent neural network is useful for automatic berthing system for the ship.

Learning Feedforward Control of a One-Stage Refrigeration System

Refrigeration control is usually realized by means of model-based feedback controllers, which requires high-computational load and time-consuming model identification efforts. The implementation of feedback control requires a compromise between performance and robust stability. Considering these difficulties, an online learning operation controller for one-stage refrigeration cycle is presented, which consists of two components: a model-based feedback component and a learning feedforward component. The feedback controller is utilized to guarantee robustness. Meanwhile, the optimized performance is reached by the learning feedforward controller including a one-hidden-layer structure with B-spline basis functions. The comparison results of benchmark problems validate the effectiveness of this strategy and show that a perfect tracking performance can still be achieved without extensive modeling.

Repeated multi-qubit readout and feedback with a mixed-species trapped-ion register.

Quantum error correction is essential for realizing the full potential of large-scale quantum information processing devices1,2. Fundamental to its experimental realization is the repetitive detection of errors via projective measurements of quantum correlations among qubits, as well as corrections using conditional feedback3. Repetitive application of such tasks requires that they neither induce unwanted crosstalk nor impede further control operations, which is challenging owing to the need to dissipatively couple qubits to the classical world for detection and reinitialization. For trapped ions, state readout involves scattering large numbers of resonant photons, which increases the probability of stray light causing errors on nearby qubits and leads to undesirable recoil heating of the ion motion. Here we demonstrate up to 50 sequential measurements of correlations between two beryllium ion microwave qubits using an ancillary optical qubit in a calcium ion, and implement feedback that allows us to stabilize two-qubit subspaces as well as Bell states, a class of maximally entangled states. Multi-qubit mixed-species gates are used to transfer information within the register from the qubit to the ancilla, enabling readout with negligible crosstalk to the data qubits. Heating of the ion motion during detection is mitigatedby recooling all three ions usinglight that interacts with onlythe calcium ion, known as sympathetic cooling. A key element of our experimental setup is a powerful classical control system that features flexible in-sequence processing for feedback control. The methods employed here provide essential tools for scaling trapped-ion quantum computing, quantum-state control and entanglement-enhanced quantum metrology4.

Implementation of feedback control in kitchen sink production

The quality of deep drawn parts is affected by many different influences. These can be separated into material related, temperature related and tool related influences. In the case of the stainless steel used in kitchen sink production, the temperature not only influences the friction but also the material properties. Therefore, a continuous monitoring and adjustment of the process is needed. The present paper shows a possibility of monitoring the current state of the part in combination with a control system for the adjustment of the press to compensate for non-measurable influences. The proposed monitoring system consists of an optical measuring device for the part state, as well as a non-destructive material testing system for the determination of material properties. The control system uses the blank holder forces as actuators. Also, the performance of the proposed system in the production line is shown.

Progressive change from nitrate to nitrite as the electron acceptor for the oxidation of H2S under feedback control in an anoxic biotrickling filter

Nitrate has been progressively replaced by nitrite as the electron acceptor in the oxidation of H2S from biogas mimic by an anoxic biotrickling filter. Perturbations in the inlet H2S concentration with and without the implementation of feedback controllers have been evaluated. Nitrite was successfully used without decreasing the H2S removal efficiency (94.74 ± 0.01%). Moreover, a PID controller allowed the sulfate selectivity to be maintained and reduced the maximum outlet H2S concentration when compared to the system without control (54.4–64.4%), although elemental sulfur was the main oxidation product. On using ORP control the main disadvantage was the production of peaks in the outlet H2S concentration. The stability and resilience of the biological system were assessed by analyzing the microbial community profiles by 16S rDNA-denaturing gradient gel electrophoresis (DDGE). The modification of the electron acceptor led to a reduction in the diversity and increased the dominance of the microbial populations.

An implementation of real-time feedback control of cured part height in Exposure Controlled Projection Lithography with in-situ interferometric measurement feedback

Exposure Controlled Projection Lithography (ECPL) is an in-house additive manufacturing process that can cure microscale photopolymer parts on a stationary transparent substrate with a time sequence of patterned ultraviolet beams delivered from underneath. An in-situ interferometric curing monitoring and measurement (ICM&M) system has been developed to measure the ECPL process output of cured height profile. This study develops a real-time feedback control system that utilizes an empirical process model and an online ICM&M feedback to automatically and accurately cure a part with targeted height. Due to the nature of photopolymerization, the total height of an ECPL cured part is divided into exposure cured height and dark cured height. The exposure cured height is controlled by a closed-loop feedback on-off controller. The dark cured height is compensated by an empirical process model obtained from the ICM&M measurements for a series of cured parts. A parallel computing software application is developed to implement the real-time measurement and control simultaneously. The experimental results directly validate the ICM&M system’s real-time capability in capturing the process dynamics and in sensing the process output. Meanwhile, it evidently demonstrates the feedback control system’s satisfactory performance in achieving the setpoint of total height, despite the presence of ECPL process uncertainties, ICM&M noises and computing interruptions. A comprehensive error analysis is reported, implying a promising submicron control with enhanced hardware. Generally, the study establishes a paradigm of improving additive manufacturing with a real-time closed-loop measurement and control system.

An autonomic‐computing approach on mapping threads to multi‐cores for software transactional memory

SummaryA parallel program needs to manage the trade‐off between the time spent in synchronisation and computation. This trade‐off is significantly affected by its parallelism degree. A high parallelism degree may decrease computing time while increasing synchronisation cost. Furthermore, thread placement on processor cores may impact program performance, as the data access time can vary from one core to another due to intricacies of the underlying memory architecture. Alas, there is no universal rule to decide thread parallelism and its mapping to cores from an offline view, especially for a program with online behaviour variation. Moreover, offline tuning is less precise. We present our work on dynamic control of thread parallelism and mapping. We address concurrency issues via Software Transactional Memory (STM). STM bypasses locks to tackle synchronisation through transactions. Autonomic computing offers designers a framework of methods and techniques to build autonomic systems with well‐mastered behaviours. Its key idea is to implement feedback control loops to design safe, efficient, and predictable controllers, which enable monitoring and adjusting controlled systems dynamically while keeping overhead low. We implement feedback control loops to automate management of threads and diminish program execution time.

Novel Active Queue Management Scheme for Routers in Wireless Networks

Congestion stability and prevention is the main aim of any decent network traffic management scheme. The protocol that drives congestion control in IP networks, called The Transmission Control Protocol (TCP), is plagued by bandwidth underutilization when implemented on wireless networks. The management of network trunk queue size is the goal of this paper, along with its antecedent delay issues with Active Queue Management (AQM) algorithms that overcomes the bandwidth underutilization issue faced by TCP flows in wireless networks. Two adaptive TCP models, specifically built for wireless networks, were created. This made it possible to implement feedback control techniques in the chosen AQM design for queue management. The two AQM policies were created with the help of Model Predictive Control (MPC) and Self-Tuning Control (STC). A very thorough comparison was made between the developed AQM schemes and two Early Detection Controllers, namely, Random Early Detection (RED) and Fixed-Parameter Proportional Integral (PI). Under varying wireless network conditions, the results obtained from simulating the proposed queue management scheme in MATLAB® confirmed that the fixed PI and RED controllers were, by comparison, inferior in performance. Copyright © 2018 Praise Worthy Prize S.r.l. - All rights reserved.

Data-Driven Modelling of Subjective Pain/Pleasure Assessments As Responses to Vaginal Dilation Stimuli

Women affected by pain during penetrative sexual intercourse are often treated using fixed-size vaginal dilators that are regularly perceived as uncomfortable and leading to premature treatment drop-outs. These dilators could be improved by making them adaptive, i.e., able to exert dynamically different pressures on the vaginal duct to simultaneously guarantee comfort levels and achieve the medical dilation objectives. Implementing feedback control would then benefit from models that connect the patients’ comfort levels with their experienced physiological stimuli. Here we address the problem of data-driven quantitative modeling of pain/pleasure self-assessments obtained through medical trials. More precisely, we consider time-series records of pelvic floor muscles pressure, vaginal dilation, and pain/pleasure evaluations, and model the relations among these quantities using statistical analysis tools. Besides this, we also address the important issue of the individualization of these models: different persons may respond differently, but these variations may sometimes be so small that it may be beneficial to learn from several individuals simultaneously. We here numerically validate the previous claim by verifying that clustering patients in groups may lead, from a data-driven point of view, to models with a significantly improved statistical performance.