Accurate Compensation Research Articles

Output redefinition-based active disturbance rejection control for nonminimum phase hypersonic vehicles

PurposeThis paper aims to propose and verify an improved cascade active disturbance rejection control (ADRC) scheme based on output redefinition for hypersonic vehicles (HSVs) with nonminimum phase characteristic and model uncertainties.Design/methodology/approachTo handle the nonminimum phase characteristic, a tuning factor stabilizing internal dynamics is introduced to redefine the system output states; its effective range is determined by analyzing Byrnes–Isidori normalized form of the redefined system. The extended state observers (ESOs) are used to estimate the uncertainties, which include matched and mismatched items in the system. The controller compensates observations in real time and appends integral terms to improve robustness against the estimation errors of ESOs.FindingsTheoretical and simulation results show that the stability of internal dynamics is guaranteed by the tuning factor and the tracking errors of external commands are globally asymptotically stable.Practical implicationsThe control scheme in this paper is expected to generate a reliable way for dealing with nonminimum phase characteristic and model uncertainties of HSVs.Originality/valueIn the framework of ADRC, a concise form of redefined outputs is proposed, in which the tuning factor performs a decisive role in stabilizing the internal dynamics of HSVs. By introducing an integral term into the cascade ADRC scheme, the compensation accuracy of matched and mismatched disturbances is improved.

MEMS Gyroscope Temperature Compensation Based on Improved Complete Ensemble Empirical Mode Decomposition and Optimized Extreme Learning Machine.

Herein, we investigate the temperature compensation for a dual-mass MEMS gyroscope. After introducing and simulating the dual-mass MEMS gyroscope's working modes, we propose a hybrid algorithm for temperature compensation relying on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sample entropy, time-frequency peak filtering, non-dominated sorting genetic algorithm-II (NSGA II) and extreme learning machine. Firstly, we use ICEEMDAN to decompose the gyroscope's output signal, and then we use sample entropy to classify the decomposed signals. For noise segments and mixed segments with different levels of noise, we use time-frequency peak filtering with different window lengths to achieve a trade-off between noise removal and signal retention. For the feature segment with temperature drift, we build a compensation model using extreme learning machine. To improve the compensation accuracy, NSGA II is used to optimize extreme learning machine, with the prediction error and the 2-norm of the output-layer connection weight as the optimization objectives. Enormous simulation experiments prove the excellent performance of our proposed scheme, which can achieve trade-offs in signal decomposition, classification, denoising and compensation. The improvement in the compensated gyroscope's output signal is analyzed based on Allen variance; its angle random walk is decreased from 0.531076°/h/√Hz to 6.65894 × 10-3°/h/√Hz and its bias stability is decreased from 32.7364°/h to 0.259247°/h.

A logistic-tent chaotic mapping Levenberg Marquardt algorithm for improving positioning accuracy of grinding robot

The precision of workpiece machining is critically influenced by the geometric errors in the kinematics of grind robots, which directly affect their absolute positioning accuracy. To tackle this challenge, this paper introduces a logistic-tent chaotic mapping Levenberg Marquardt algorithm designed to accurately identify and compensate for this geometric error. the approach begins with the construction of a forward kinematic model and an error model specific to the robot. Then the algorithm is adopted to identify and compensate for the geometric error. The method establishes a mapping interval around the initial candidate solutions derived from iterative applications of the Levenberg Marquardt algorithm. Within this interval, the logistic-tent chaotic mapping method generates a diverse set of candidate solutions. These candidates are evaluated based on their fitness values, with the optimal solution selected for subsequent iterations. Empirical compensation experiments have validated the proposed method's precision and effectiveness, demonstrating a 6% increase in compensation accuracy and a 47.68% improvement in efficiency compared to existing state-of-the-art approaches. This process not only minimizes the truncation error inherent in the Levenberg Marquardt algorithm but also significantly enhances solution efficiency. Moreover, simulation experiments on grind processes further validate the method's ability to significantly improve the quality of workpiece machining.

The Impact of GCP Chip Distribution on Kompsat-3A RPC Bias Compensation

The vast potential of high-resolution satellite images, including Kompsat-3A, has been demonstrated across diverse applications, such as mapping and disaster monitoring. However, these images can only be utilized as reliable GIS (geographic information system) data when they possess precise geographical information. To achieve this, sensor model information, represented by RPCs (rational polynomial coefficients), requires bias compensation through GCPs (ground control points). Though having a substantial number of well-distributed GCPs across satellite images is ideal, the acquisition process is often restricted due to cost and inaccessibility. The uniform distribution of GCP chips is not guaranteed, necessitating an investigation into the impact of GCP distribution on the bias compensation process, which is the focus of this study. Experiments were meticulously conducted using Kompsat-3A data using dense GCP information. The dense GCP information was automatically generated from aerial orthoimages through a three-step process. Firstly, the GCP chips were extracted from the aerial images, focusing on feature points. Secondly, these chips were projected onto the target Kompsat-3A data to align them accurately. Lastly, precise satellite image coordinates of the chips were obtained through image matching between the chips and the target Kompsat-3A image. The dense GCPs enabled detailed bias analysis that exhibited skewness in most Kompsat-3A data. This necessitates the implementation of an affine model for proper bias compensation over the entire image space. Next, the study delved into the influence of GCP distribution on RPC bias compensation. To this end, each target satellite image space was divided into nine zones, with the dense GCPs assigned accordingly. The accuracy of bias compensation was analyzed across nine experimental cases, ranging from GCPs occupying only one zone to GCPs covering all nine zones. It was observed that GCPs covering at least four or five zones should be utilized for reliable RPC bias compensation of Kompsat-3A, especially when aiming for a high level of accuracy with an RMSE of one pixel. Finally, it was concluded that GCPs covering three zones yielded satisfactory results as a minimum GCP requirement, but this was contingent upon their distribution not following a straight zone pattern.

Unscented Kalman Filter-Based Two-Stage Adaptive Compensation Method for Real-Time Hybrid Simulation

ABSTRACT In order to effectively solve the dynamic delay problem of the servo-hydraulic actuator, simplify the design of the compensator, and improve the robustness of the compensation, an unscented Kalman filter-based two-stage adaptive compensation (UKF-TAC) method is proposed for real-time hybrid simulation (RTHS) in this study. Theoretical analysis and numerical simulations are conducted to verify the performance of the proposed UKF-TAC method. The research results show that the proposed UKF-TAC method can significantly simplify the design of the compensator, effectively improve the compensation accuracy, and has the robustness to adapt to different partitioning cases and resist the interference of uncertain factors.

Accurate error compensation method for multi-axis parallel machine via singularized jacobi geometric parameter correction and coupling error evaluation

The Jacobian model is a prevalent tool for error compensation in multi-axis parallel mechanisms. However, discrepancies between the model's nominal and actual geometrical parameters, combined with equivalent replacements and high-order rounding in the modeling process, lead to equation solving challenges and modeling errors. These inaccuracies result in residual errors in the Jacobian model compensation. To address these problems, this paper proposes an optimal Jacobian correction approach. This is based on a geometrical parameter singularized Jacobian correction model, and a module for the evaluation of coupling errors for multi-axis parallel mechanisms was incorporated. Instead of relying on iterative processes, a singularized geometrical error solution method (SESM) was developed. Through this method, precise derivation of the Jacobian correction parameters is ensured, effectively addressing the indefinite equation challenge and partial posture non-solution problem. Moreover, modeling errors resulting from equivalent infinitesimal replacements and the overlooking of high-order minor values are compensated for by the SESM. It was observed that varying singularized geometrical parameters in the Jacobian model can produce different coupling effects and compensation outcomes. Therefore, a sensitivity-based error predictive evaluation method (EPEM) was introduced. By this method, the optimal correction parameter of the Jacobian model across the entire workspace is identified, ensuring precise pose error compensation. The proposed method was validated using a three-axis parallel mechanism. Through these tests, its superior efficacy was revealed. In comparison to the traditional uncorrected Jacobian compensation, reductions in position and orientation errors by 64.93% and 55.29%, respectively, were achieved. This method provides a new approach for error modeling, equation solving, and parameter correction for multi-axis mechanism error compensation and precision equipment development.

Investigation on centrifugal deformation effect of magnetic levitation superconducting rotor

The high-speed rotating superconducting rotor can be made into a high-precision inertial device. Centrifugal deformation is one of the key factors affecting the drift speed of the rotating superconducting rotor's polar axis. The larger the drift speed, the worse the accuracy of the inertial device. Applying magnetic torque to the superconducting rotor to compensate for the magnetic disturbance torque generated by centrifugal deformation is one of the effective methods to improve the measurement accuracy of the inertial device made of a superconducting rotor. To compensate for the magnetic disturbance torque caused by centrifugal deformation accurately, we studied the centrifugal deformation effect of the rotating superconducting rotor. In this paper, the centrifugal deformation of the superconducting rotor is analyzed first. And then the influence of centrifugal deformation of the superconducting rotor on magnetic force was studied by Finite Element Method (FEM). The results show that centrifugal deformation can reduce the magnetic levitation force of the superconducting rotor, leading to suspension position drift. Finally, the drift speed of the superconducting rotor's polar axis caused by centrifugal deformation is investigated, including the drift speed caused by centrifugal deformation of the rotating superconducting rotor, as well as the drift speed generated by the coupling of centrifugal deformation and suspension position drift of the superconducting rotor. The research results provide a reference for more accurate compensation of magnetic disturbance torque caused by centrifugal deformation and further improve the accuracy of superconducting rotor inertial devices.

Adaptive fuzzy control for tendon-sheath actuated bending-tip system with unknown friction for robotic flexible endoscope.

The tendon-sheath actuated bending-tip system (TAB) has been widely applied to long-distance transmission scenes due to its high maneuverability, safety, and compliance, such as in exoskeleton robots, rescue robots, and surgical robots design. Due to the suitability of operation in a narrow or tortuous environment, TAB has demonstrated great application potential in the area of minimally invasive surgery. However, TAB involves highly non-linear behavior due to hysteresis, creepage, and non-linear friction existing on the tendon routing, which is an enormous challenge for accurate control. Considering the difficulties in the precise modeling of non-linearity friction, this paper proposes a novel fuzzy control scheme for the Euler-Lagrange dynamics model of TAB for achieving tracking performance and providing accurate friction compensation. Finally, the asymptotic stability of the closed-loop system is proved theoretically and the effectiveness of the controller is verified by numerical simulation carried out in MATLAB/Simulink. The desired angle can be reached quickly within 3 s by adopting the proposed controller without overshoot or oscillation in Tracking Experiment, demonstrating the regulation performance of the proposed control scheme. The proposed method still achieves the desired trajectory rapidly and accurately without steady-state errors in Varying-friction Experiment. The angle errors generated by external disturbances are < 1 deg under the proposed controller, which returns to zero in 2 s in Anti-disturbance Experiment. In contrast, comparative controllers take more time to be steady and are accompanied by oscillating and residual errors in all experiments. The proposed method is model-free control and has no strict requirement for the dynamics model and friction model. It is proved that advanced tracking performance and real-time response can be guaranteed under the presence of unknown bounded non-linear friction and time-varying non-linear dynamics.

Robot joint space grid error compensation based on three-dimensional discrete point space circular fitting

The poor absolute positioning accuracy of industrial robots has limited their application in fields such as aerospace manufacturing. To address this issue, the spatial grid compensation method has been proposed as an effective solution. In this paper, we propose a sampling method based on three-dimensional discrete point space circular fitting for grid points to significantly reduce the sampling workload and improve compensation accuracy compared to traditional joint space grid compensation methods. Additionally, we use the Kriging interpolation algorithm instead of the inverse distance weighting (IDW) algorithm for spatial interpolation prediction of pose error. Based on this, the proposed sampling and interpolation prediction method in this paper was verified on a Comau NJ500–2.7 manipulator equipped with a fiber-laying end effector. The experimental results demonstrate that using our proposed sampling method yields pose data of grid points that have only a small deviation from directly sampled results and are only slightly higher than the robot's repeat positioning accuracy. Moreover, our proposed method can significantly reduce the sampling workload by 60% under the experimental conditions of this study (sampling 10 groups of data within 90 degrees range), with increasing sampling range leading to more obvious efficiency improvements. Finally, we show that compared to the IDW algorithm, the Kriging interpolation algorithm yields better results and improves the mean absolute positioning accuracy of robots after compensation by 30%.

Accuracy Compensation Based on Optimized Neural Network for a Robotic Patient Positioning System with 6 Degrees of Freedom Used in Proton Therapy System

Proton therapy for tumor treatment is a typical application of nuclear technology. For proton therapy systems, robotic patient positioning systems (PPSs) are increasingly used because of their high flexibility and efficiency. Most robotic PPSs are developed based on industrial robots, which have good repeatability but low absolute position accuracy (1 to 3 mm) and do not satisfy the requirement of highly precise treatment. In this study, an optimized algorithm, named the Back Propagation Neural Network (BPNN) algorithm based on particle swarm optimization, is proposed to improve the performance of absolute positioning accuracy. A comparison of the training for the traditional BPNN and the optimized algorithm is presented. A series of experiments with different payload weights and tools is implemented to validate the performance of the proposed method. The training results show that the proposed method can improve the average predicted positioning error from 0.55 to 0.38 mm. The results of the experiment with a calibration tool show that the average position error is reduced from 4.10 to 0.32 mm. The results of the experiment with a carbon fiber couch top show that the average and maximal positioning errors are 0.35 and 0.77 mm, respectively. All the results verify the feasibility of the proposed method in this study in improving the position accuracy of the robotic PPS.

Research on DC Voltage Stability Control of Railway Power Conditioner Based on Impedance Matching Principle

When the Railway Power Conditioner (RPC) is used to solve the power quality problem of the electrified railroad, the DC impedance will have a negative impedance characteristic during the bidirectional transmission of RPC power, and this negative impedance characteristic will affect the accuracy of RPC power compensation, cause the fluctuation of RPC DC bus voltage, and affect the effect of negative sequence current management on the grid side. In view of the above problems, this paper proposes an RPC control strategy based on the impedance matching principle, which optimizes the negative impedance characteristics into positive impedance characteristics by the cooperative control of DC voltage and power, increases the phase angle margin of the system, improves the stability and dynamic performance of DC voltage under the bidirectional flow of RPC power, and improves the effect of grid-side negative sequence current management. Firstly, this paper performs small-signal modeling of the DC-side port impedance and analyzes its impedance characteristics. Secondly, the working principle of the RPC control strategy based on the impedance matching principle is analyzed. Finally, the proposed control strategy is effectively verified by building a simulation model and an experimental platform.

Rapid and restricted swing control via adaptive output feedback for 5-DOF tower crane systems

Crane swing & relevant vibration are critical safety and efficiency issues to be addressed in construction automation, involving various disturbance and uncertainties. This paper presents for the first time a controller designed for 5-DOF tower crane systems with no velocity signals, and its effectiveness is experimentally verified. Compared to previous controllers, the new design utilizes an adaptive output feedback control method with accurate online gravity compensation, which solves the problems of unavailability velocity, noise amplification by numerical difference, and steady state error of cable in tower crane control. Additionally, the saturated control inputs are guaranteed by employing bounded functions. The results of this study unveil that the controller proposed in this paper can simultaneously achieve accurate trolley/jib/cable positioning, rapid payload swing suppression and elimination, as well as precise payload mass estimation, and guarantee control inputs constraints. This study provides a new approach for accurate control of tower crane systems.

Experimental demonstration on 400 nm-scale bandwidth optical parametric chirped-pulse amplification based on mixed cascaded crystals.

We present an optical parametric chirped-pulse amplification (OPCPA) based on mixed cascaded crystals, taking advantage of the unique parametric phase-matching of lithium triborate (LiB3O5, LBO) and yttrium calcium oxyborate ((YCa4O(BO3)3, YCOB) crystals. The OPCPA properties of LBO at 880 nm and YCOB at 750 nm are studied respectively. After amplification by two LBO and two YCOB crystals, a total signal gain of 108 and spectral bandwidth close to 400 nm is obtained. After accurate dispersion compensation with a grating-pair compressor and chirped mirror compensator, a pulse duration of 9.4 fs is obtained by a SHG-frequency-resolved optical grating (FROG). This approach will be of great significance in high energy amplifier for high peak power few-cycle laser sources.

Active Compensation Technology for the Target Measurement Error of Two-Axis Electro-Optical Measurement Equipment.

For two-axis electro-optical measurement equipment, there are many error sources in parts manufacturing, assembly, sensors, calibration, and so on, which cause some random errors in the final measurement results of the target. In order to eliminate the random measurement error as much as possible and improve the measurement accuracy, an active compensation technique for target measurement error is proposed in this paper. Firstly, the error formation mechanism and error transfer model establishment of the two-axis electro-optical measurement equipment were studied, and based on that, three error compensation and correction methods were proposed: the least square (LS)-based error compensation method, adaptive Kalman filter(AKF)-based error correction method, and radial basis function neural network (RBFNN)-based error compensation method. According to the theoretical analysis and numerical simulation comparison, the proposed RBFNN-based error compensation method was identified as the optimal error compensation method, which can approximate the random error space surface more precisely, so that a more accurate error compensation value can be obtained, and in order to improve the measurement accuracy with higher precision. Finally, the experimental results proved that the proposed active compensation technology was valid in engineering applicability and could efficiently enhance the measurement accuracy of the two-axis electro-optical measurement equipment.

A flexible compensation device for single-phase-to-ground fault in distribution networks based on double-loop passivity-based control

Aiming at the problem that the existing single-phase-to-ground fault flexible compensation device has low compensation accuracy, long response time, and needs DC side power supply, a flexible compensation device based on double-loop passivity-based control is proposed. Firstly, the topology and working principle of the device are analyzed. And a compensation current distribution method of the bridge arm is proposed. Secondly, a double-loop passivity-based controller is designed. Finally, the proposed method is verified by MATLAB/Simulink software and 10 kV physical simulation system of distribution network. The comparisons between double-loop passivity-based control, passivity-based control, and proportional integration control is discussed. The result shows that the proposed method can accurately and rapidly compensate the fault current.

AEKF-based trajectory-error compensation of knee exoskeleton for human–exoskeleton interaction control

PurposeThe purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.Design/methodology/approachA trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.FindingsSix volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.Originality/valueThe AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

Thermal error compensation in length inspection of large-scale aircraft spars in nonuniform temperature environments

As the primary load-bearing structures, large-scale aircraft spars are subject to the influence of nonuniform temperatures in field conditions, resulting in thermal errors during on-site length inspections. These errors require accurate compensation. Conventional linear scaling methods, based on the assumption of uniform temperatures and a retrieved coefficient of thermal expansion (CTE), suffer from low accuracy in nonuniform temperature environments. To address this issue, this paper proposed a thermal error compensation method that incorporates CTE recalibration. First, we established a predictive model for thermal errors in nonuniform temperature fields through differential thermoelastic analysis. Secondly, a recalibration technique for the sensitive parameter, CTE, was introduced to enhance the prediction accuracy. Finally, leveraging the equivalent form of the model, an uncertainty assessment approach tailored for nonuniform temperature conditions was formulated for the compensated lengths. Numerical and case studies of a nearly 1 m long simplified wing spar were implemented to validate the performance of the thermal error compensation method. The results indicate that the presented method improved accuracy by over 57.6% in terms of RMSE compared to the linear scaling method using average temperatures, which would provide a viable approach to achieve a more accurate on-site length inspection of aircraft components.

Optimal proportion compensation method of key geometric errors for five-axis machine tools considering multiple-direction coupling effects

Five-axis machine tools are subject to highly coupled geometric errors that significantly affect their machining accuracy. Existing geometric error compensation methods do not consider the coupling effects between errors, resulting in insufficient error compensation efficiency and accuracy. To solve this problem, an optimal proportion compensation method for key geometric errors of five-axis machine tools was proposed, considering multiple direction coupling effects. The key geometric errors were identified using the improved Sobol method based on the volumetric error model. The coupling effects of the geometric errors were analyzed based on the overlapping terms of the key errors in multiple directions, and the coupling situation was classified into four types. The compensation sequence and proportion value in each direction were developed according to the coupling type; i.e., the key errors were compensated to the proportion value instead of the traditional compensation to zero. Taking the S-shaped specimen as an example, the experimental verification indicated that the number of geometric error items that had to be compensated by our method was reduced by 44.4 % compared to the traditional key geometric error compensation method. Additionally, the compensation accuracy was increased by 58.9 %, thus proving the effectiveness of the proposed method.

Motion Hysteresis Compensation Based on Motor Current Segmentation for Elongated Cable-Driven Surgical Instruments

Cable-driven surgical instrument is a reusable and disposable component of Robot-assisted Minimally Invasive Surgery, and it is time-consuming to identify the motion hysteresis compensation model of each instrument in large-scale identification. Besides, the identification results failure caused by the loss of cable tension or lubrication conditions during repeated usage interferes with the accuracy of motion hysteresis compensation. To simplify the identification process and lengthen the instrument life, this paper leverages the relationship between actuate motor current and hysteresis phases, developing a novel motion hysteresis compensation method to compensate the motor reference trajectory. Firstly, prior knowledges including motor current and hysteresis curves of several instruments are collected to train the Hysteresis Identification model and Curve Generation model. Once the two models are well-trained in practical use, the only sensor data in need is the motor current for the Hysteresis Identification model, and the compensation curve will be generated pertinently for the instrument under current use. Finally, Feedforward Compensation scheme is conducted to compensate the reference trajectory of the actuate motor. Experiments study the range of hysteresis compensation errors when the method is applied to numerous surgical instruments with different motion hysteresis, and the feasibility and accuracy are verified. The method can be potentially applied to a wide range of cable-driven mechanisms facing the problem of large-scale identification or the identification results failure after repeated use. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper proposes a feasible motion hysteresis compensation method for cable-driven mechanism (CDM). For some CDMs like elongated cable-driven surgical instrument, their motion hysteresis characteristics will change during repeated use, and their distal angle and cable tension are not available in the environment of use. In these cases, the proposed method enables re-identification because the distal angle or cable tension are not needed during the practical use of our method. Besides, it is easy and low-cost for large-scale identification due to the simplicity of identification procedure. Once the Hysteresis Identification model and Curve Generation model are trained using the pre-collected prior knowledge including motor current and the angle of the end effector, the only sensor data in need to identify and compensate a certain CDM is the its motor current. Then, the pertinent compensation curve for the CDM device can be generated for the actuate motor to follow. The experimental results reveal that the competitive performance with other state-of-the-arts can be achieved. In the future research, we will integrate dynamic characteristics of CDM into the method to expand the scope of application.

Benefits of Planter Turn Compensation on Irregular Shaped Fields

Highlights For the production fields examined, turn compensation was actuated for between 4.7% and 12.1% of the area during planting operations. Seeding rate error without turn compensation ranged from 30.9% to 570.1% while with turn compensation seeding rate error was only 0.1% to 10.4%. A cost savings of $16 to $212 ha-1 can be realized when planting with a turn compensation feature. Abstract. Modern precision planters utilize advanced technologies such as electric seed metering units and hydraulic downforce systems, allowing for more precise control of seed placement during planting. This study focused on assessing the effectiveness of adopting turn compensation using electrically driven seed meters. Turn compensation refers to the ability of a planter to adjust seeding rates across the toolbar to account for the speed differential caused by planting around a turn or curvilinear pass. Significant research has been conducted on the accuracy of turn compensation implemented by electric driven seed meters, though no existing research could be found on the amount of ground covered in a production field when the technology is being utilized. Thus, the objectives of this study are: 1) to quantify the extent of area planted with turn compensation actuated on fields with varying size and shape and 2) to assess the potential cost savings when using a planter equipped with this technology. Results indicated that turn compensation could provide accurate adjustments of seed and fertilizer inputs while planting on curvilinear paths. In the production fields examined turn compensation would be actuated on between 4.7% and 12.1% of the area. Spacing data confirmed that the turn compensation accurately corrected the seed spacing when planting on curves. Seeding rate error without turn compensation ranged from 30.9% to 570.1% while with turn compensation seeding rate error was only 0.1% to 10.4%. Finally, results indicated a cost savings of $16 to $212 ha-1 when using a planter with a turn compensation feature.