Compensation Approach Research Articles

Resource Equivalency Analysis (REA): Implication environmental of groundwater in Kupang East Nusa Tenggara

This article discusses the environmental assessment caused by the commercial use of groundwater by the community as landowners. In the future, this practice must receive direction and responsibility from the government as policymakers to prevent and repair environmental damage, especially habitat damage and species in strengthening the principle of "paying for commercial groundwater" with the REA methodology to assess and compensate for environmental damage. This method, developed by the National Oceanographic and Atmospheric Administration (NOAA), uses the scale of remediation required to compensate for past, current and future damage. The compensation approaches are the services approach (or the resources approach) and the valuation approach (the value-to-value and value-to-cost approach). The results show that the change in residential land is 0.16%, or 25 ha. The total area of changed settlement/land built up has decreased the function of land which was originally secondary/logged-over dry land forest to become settlement/land built up. Furthermore, there was a decrease in secondary/logged-over dry land forest to open field of 0.03% or 3.1 ha, so that the total area of secondary/logged-over dry land forest decreased by 0.19% or 28.1 ha.

Advanced Pressure Compensation in High Accuracy NDIR Sensors for Environmental Studies

Measurements of atmospheric gas concentrations using of NDIR gas sensors requires compensation of ambient pressure variations to achieve reliable result. The extensively used general correction method is based on collecting data for varying pressures for a single reference concentration. This one-dimensional compensation approach is valid for measurements carried out in gas concentrations close to reference concentration but will introduce significant errors for concentrations further away from the calibration point. For applications, requiring high accuracy, collecting, and storing calibration data at several reference concentrations can reduce the error. However, this method will cause higher demands on memory capacity and computational power, which is problematic for cost sensitive applications. We present here an advanced, but practical, algorithm for compensation of environmental pressure variations for relatively low-cost/high resolution NDIR systems. The algorithm consists of a two-dimensional compensation procedure, which widens the valid pressure and concentrations range but with a minimal need to store calibration data, compared to the general one-dimensional compensation method based on a single reference concentration. The implementation of the presented two-dimensional algorithm was verified at two independent concentrations. The results show a reduction in the compensation error from 5.1% and 7.3%, for the one-dimensional method, to -0.02% and 0.83% for the two-dimensional algorithm. In addition, the presented two-dimensional algorithm only requires calibration in four reference gases and the storing of four sets of polynomial coefficients used for calculations.

Event-based fault estimation and compensation for discrete-time systems via zonotopes

A fault estimation and compensation approach is presented for discrete-time systems with event-triggered scheme based on zonotope techniques in this paper. Instead of energy-bounded uncertainties, the dynamic system is supposed to be subjected to unknown but amplitude-bounded disturbance and noise, which is more in line with engineering practice. By introducing dynamic interval variables, a component-wise dynamic event-triggered strategy is utilized to reduce the consumption of communication resources. With considering the amplitude-bounded uncertainties and event-triggered scheme, a joint state-fault estimator is constructed to estimate the system state as well as possible system faults simultaneously, which are utilized to construct the fault-tolerant controller by compensating the effects of system faults. A co-design approach of the estimator, compensator, and event-triggered strategy is proposed to guarantee the stability and l1 performance of the system, based on which a zonotope-based interval estimation algorithm of system state and possible faults is provided to obtain the tight estimation of system state and faults. Eventually, simulation results on aircraft engine systems indicate that the designed method achieves a satisfactory fault estimation and fault tolerance performance, and also reduce the consumption of communication resources significantly.

An explicit stable Q-compensated reverse time migration scheme for complex heterogeneous attenuation media

Prestack reverse-time migration (RTM) is a popular imaging technique for complex geological conditions, since the amplitude attenuation and velocity dispersion are common in seismic recordings. To image attenuated seismic recordings accurately, a robust migration algorithm with a stable attenuation compensation approach should be considered. In the context of the Q-compensated RTM approach based on the decoupled fractional Laplacians (DFLs) viscoacoustic wave equation, amplitude compensation can be implemented by flipping the sign of the dissipation term. However, the non-physical magnification of image amplitude could lead to a well-known numerical instability problem. The explicit stabilization operator can rectify the amplitude attenuation and suppress the numerical instability. However, limited by the inconvenient mixed-domain operator, the average Q value rather than the real Q value is often used in the compensation operator, lowering the compensated accuracy of the migration image. To overcome this problem, we propose a novel explicit Q-compensation scheme. The main advantage of the proposed compensation operator is that its order is space-invariant, making it more suitable for handling complex heterogeneous attenuation media. Several two-dimensional (2D) and three-dimensional (3D) synthetic models are used to verify the superiority of the proposed approach in terms of amplitude fidelity and image resolution. Field data further demonstrates that our approach has potential applications and can greatly enhance the resolution of seismic images.

Observer-Based Robust Fuzzy Controller Design for Uncertain Singular Fuzzy Systems Subject to Passivity Criterion

This paper discusses an observer-based control problem for uncertain Takagi–Sugeno Fuzzy Singular Systems (T-SFSS) subject to passivity performance constraints. Through the Parallel Distributed Compensation (PDC) approach and the Proportional Derivative (PD) control scheme, an observer-based fuzzy controller is constructed to achieve the stability of the considered system. An unlimited positive definite matrix is utilized to construct the Lyapunov function and derive sufficient stability conditions to develop a relaxed design method. Moreover, some technologies, such as the Schur complement, projection lemma, and Singular Value Decomposition (SVD), are applied to convert the conditions to Linear Matrix Inequality (LMI) form. Therefore, the convex optimization algorithm is used to solve the LMI conditions to find feasible solutions. The observer-based fuzzy controller is established with the obtained solutions to guarantee stability and passivity performance for the uncertain nonlinear singular systems. Finally, two examples are provided to verify the availability of the proposed fuzzy control approach.

An add-on damping enhancement with adjustable gain for lightly damped system

The inherently difficult problem with very lightly damped systems is the extreme sensitivity at the resonance peaks, which results in severe performance degradation even for small model uncertainty. And it is also difficult to cancel the undesirable lightly damped poles from different sensitivity functions. To this end, this paper presents an add-on damping compensation approach with adjustable gain, which can handle uncertain resonance frequency and effectively improve the vibration suppression performance in terms of different sensitivity functions. First, the lightly damped model is included in the observer form by augmenting the system with two extra state variables, which can simultaneously estimate the total disturbance and the resonance mode via prior resonance knowledge. Second, the add-on damping compensation term is applied to improve the vibration suppression performance. Third, the parameters tuning guideline is thereby provided via the frequency domain analysis. Several simulations and experiments are successfully implemented in the established two-mass–spring (TMS) system, and the results validate the effectiveness and superiority of the proposed method.

KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way

Robust and accurate pose estimation of a robotic platform, so-called sensor-based odometry, is an essential part of many robotic applications. While many sensor odometry systems made progress by adding more complexity to the ego-motion estimation process, we move in the opposite direction. By removing a majority of parts and focusing on the core elements, we obtain a surprisingly effective system that is simple to realize and can operate under various environmental conditions using different LiDAR sensors. Our odometry estimation approach relies on point-to-point ICP combined with adaptive thresholding for correspondence matching, a robust kernel, a simple but widely applicable motion compensation approach, and a point cloud subsampling strategy. This yields a system with only a few parameters that in most cases do not even have to be tuned to a specific LiDAR sensor. Our system performs on par with state-of-the-art methods under various operating conditions using different platforms using the same parameters: automotive platforms, UAV-based operation, vehicles like segways, or handheld LiDARs. We do not require integrating IMU data and solely rely on 3D point clouds obtained from a wide range of 3D LiDAR sensors, thus, enabling a broad spectrum of different applications and operating conditions. Our open-source system operates faster than the sensor frame rate in all presented datasets and is designed for real-world scenarios.

Improvement in hole-pose error for aerospace drilling applications based on Hermite surface reconstruction and manifold error similarity

Hole position accuracy and perpendicularity are significant factors in aerospace drilling. This study presents a novel compensation method with reference holes to reduce the hole position error and initial normal deviation for automated drilling systems. The hole-pose error and related generalized addition and subtraction methods are first defined using quaternions. Subsequently, approaches for accurately measuring the pose of the reference hole and calibrating the coordinate system are proposed. On this basis, the position error and initial normal error are estimated by bilinear interpolation based on the error similarity on the two-dimensional manifold, where the manifold coordinates are obtained by Hermite surface reconstruction. Subsequently, the hole-pose error is compensated for by generalized addition. For the initial normal modification, a compensation strategy utilizing the data of processed adjacent holes for interpolation was adopted. In addition, for situations in which it is inconvenient to arrange real reference holes on the product, a compensation approach employing virtual reference holes was designed. Finally, simulations and experiments are conducted, and the results demonstrate that the position error and initial normal deviation are effectively reduced by at least 42.25% and 74.68% with the proposed method, which further ensures that the indicators meet the requirements of aerospace drilling.

Event-based formation control for multiple unmanned aerial vehicles under directed topology

This paper focuses on the problem of formation control for multiple unmanned aerial vehicles (UAV) subject to cyber attacks by a novel event-triggered communication scheme. An average method is introduced to design the triggering condition of this communication scheme, by which the amount of wrong triggering events caused by the sudden change of system states is greatly decreased, thereby saving a great deal of network bandwidth and reducing network congestion. Considering cyber attacks, a new event-based formation control strategy is developed for multi-UAV systems under directed topology by utilizing a control compensation approach. Sufficient conditions for the multi-UAV system to achieve the desired formation are acquired. Finally, a simulation example is undertaken to demonstrate the effectiveness of the theoretical results.

Experimental and Modelling Analysis of a Downstream Compensation System: Energy Optimization of the Directional Control Valves

Through a study on the Fluid Power innovations in the last years emerged that still few solutions have been successfully implemented for the optimization of the hydraulic circuits. The recent machine electrification offers a potential for investment in energy-saving hydraulic systems to ensure greater performance and higher battery autonomy. From different studies emerged that in the specific field of ICE Off-road Vehicles, only about 10–15% of the available power at fuel level is actually transformed into useful energy for the actuators. Particularly the losses in the Directional Control Valves represent about 35–40% of the hydraulic energy available at the pump level. The traditional Directional Control Valves design solutions, in fact, neglects important opportunities for reducing losses and improving internal regeneration. Especially, energy recovery is rarely applied and in any case by means of important superstructures which considerably increase the costs of the system. This paper presents a new hydraulic architecture: an original Directional Control Valve layout based on a Downstream Compensation approach. In particular, a Flow Sharing system is implemented in this new architecture with the goal to minimize the wasted energy. In fact, this system realizes an important energy recovery from both the inertial loads and the simultaneous use of multiple actuators at different pressure level. The circuit enables recovered energy to be stored in a high-pressure accumulator. The paper presents the simulation results and the energy saving estimation realized through a lumped parameter environment “Amesim Simcenter”. Additionally, the results of experimental activities show the innovative system performance, benefits and physical applicability. This idea is based on concrete objectives and pays particular attention to cost sustainability, industrial manufacturability and system scalability.

Robust fuzzy stabilization control for the traction converters in high-speed train

High-speed railways have quickly gained popularity as an environmentally beneficial mode of transportation. In addition, converters and electric motors are becoming more widely used. However, power converters and motors can act as constant power loads when tightly controlled, making the source converters unstable. In this article, robust fuzzy control is proposed for stabilizing power electronic converters feeding a constant power load in a high-speed train. The negative incremental resistance characteristics of the trains are first investigated. Then, utilizing the Takagi–Sugeno fuzzy model and the parallel distributed compensation approach, a robust stabilizing controller is constructed to ensure asymptotic descent of the dynamic system state trajectories toward the equilibrium position. Moreover, using linear matrix inequalities, the intended control gain can be automatically computed. The critical adjustment time of the controller and total harmonic distortions of the line currents are selected to measure and compare the dynamic stability of the designed controller. The suggested technique not only maintains global stability in the face of considerable changes in the constant power loads, but it also offers a fast dynamic reaction time and precise tracking over a wide operating range. Finally, simulations and experiments are performed to validate the proposed approach.

High-density Surface EMG Decomposition by Combining Iterative Convolution Kernel Compensation with an Energy-specific peel-off Strategy.

Objective- This study aims to develop a novel framework for high-density surface electromyography (HD-sEMG) signal decomposition with superior decomposition yield and accuracy, especially for low-energy MUs. Methods- An iterative convolution kernel compensation-peel off (ICKC-P) framework is proposed, which consists of three steps: decomposition of the motor units (MUs) with relatively large energy by using the iterative convolution kernel compensation (ICKC) method and extraction of low-energy MUs with a Post-Processor and novel 'peel-off' strategy. Results- The performance of the proposed framework was evaluated by both simulated and experimental HD-sEMG signals. Our simulation results demonstrated that, with 120 simulated MUs, the proposed framework extracts more MUs compared to K-means convolutional kernel compensation (KmCKC) approach across six noise levels. And the proposed 'peel-off' strategy estimates more accurate MUAP waveforms at six noise levels than the 'peel-off' strategy proposed in the progressive FastICA peel-off (PFP) framework. For the experimental sEMG signals recorded from biceps brachii, an average of 16.1 ± 3.4 MUs were identified from each contraction, while only 10.0 ± 2.8 MUs were acquired by the KmCKC method. Conclusion- The high yield and accuracy of MUs decomposed from simulated and experimental HD-sEMG signals demonstrate the superiority of the proposed framework in decomposing low-energy MUs compared to existing methods for HD-sEMG signal decomposition. Significance- The proposed framework enables us to construct a more representative motor unit pool, consequently enhancing our understanding pertaining to various neuropathological conditions and providing invaluable information for the diagnosis and treatment of neuromuscular disorders and motor neuron diseases.

Compensation approach for discretization constraint in automobile powertrain control and its performance evaluation

Compensation approach for discretization constraint in automobile powertrain control and its performance evaluation

An Effective Translational Motion Compensation Approach for High-Resolution ISAR Imaging With Time-Varying Amplitude

An Effective Translational Motion Compensation Approach for High-Resolution ISAR Imaging With Time-Varying Amplitude

Citizens and Land: Socioeconomic Effects of Relocation and Resettlement by the Thilawa Special Economic Zone

Abstract: Special economic zones (SEZs) attract investment and political support based on promises of both macroeconomic growth and local economic benefit. Myanmar has numerous SEZs, including those in Thilawa, Dawei, and Kyaukphyu. Recent SEZ legislation requires investors and administrators to maintain the standard of living of communities displaced by the SEZ development. This paper studies the socioeconomic impact on households which have been relocated by the Thilawa SEZ, comparing them with those which remained in their original communities. Relocated households have experienced significantly higher rates of unemployment, debt, and lack of livelihood/income diversity. Due to a greater reliance on food purchases and income insufficiency, relocated households reported higher rates of food insecurity, and nearly one-third reported having taken out loans to meet food shortages in the past year. Overall, the pattern of coping amongst relocated households demonstrates significantly lower levels of resilience than non-relocated households, which results in a rapid erosion of economic capital, and subsequently a decline in future coping capacity. These findings challenge the assumptions around capital-based compensation approaches to relocation programs and argue instead that the process of relocation is best compared to a shock transition to an urban state, characterized by a rupturing of the relationship to land. The ensuing precarity demands a high level of adaptive capacity, which, in turn, requires not only new skills but access to resources, markets, and welfare mechanisms, many of which are not available. If SEZs are to fulfill both the wider economic promise and the legal requirements, a radically different approach to the processes of relocation is needed.

Adaptive Neural Design of Consensus Controllers for Nonlinear Multiagent Systems Under Switching Topologies

Existing adaptive neural control methods for nonlinear multiagent systems (MASs) are only applicable under a fixed topology or are applicable under switching topologies but require some linear growth conditions on the nonlinear functions. Motivated by these limitations, a state-dependent adaptive neural design method is proposed in this article. Technically, our method is developed from a state-dependent Lyapunov function candidate, a switched control law, and a projection-based adaptation mechanism. To overcome the stability analysis difficulty caused by the new design of the Lyapunov function, a nonswitched compensation approach and a modified multiple Lyapunov functions method are proposed to derive a dwell-time condition, under which stability can be preserved. It is proved that in addition to stability, synchronization errors converge to a tunable residual around zero. Besides, the proposed scheme achieves the improvement of transient performance in terms of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{2}$ </tex-math></inline-formula> norm and moreover, once there are no more topology switchings, asymptotic convergence of synchronization errors to a prescribed interval recovers automatically.

Time-Series Forecast-Based Endpoint Thickness Compensation for Thinning of Sapphire Wafer

The grinder consults measurement modules to control the endpoint thickness of the sapphire wafer thinning process, but these modules have shortcomings. We propose a forecast-based endpoint thickness and online error compensation approach for grinding hard, brittle material. We leverage forecasts to improve grinding efficiency, and address the shortcomings of conventional probe gauges, which can be used only when grinding is paused, as well as those of contact gauges, which require correction from time to time due to wear. We construct a multi-signal time-series forecast model and compare the prediction performance using features from various signals. We implement the forecast model in a vertical grinder for actual grinding to evaluate the effectiveness of the proposed approach. The results show that online error compensation reduces contact times for the contact gauge and maintains precise thickness, greatly facilitating the wafer thinning process. The proposed measurement approach applies not only to wafer thinning but can also be extended to other grinding processes.

Investigation on Multisampling Deadbeat Current Control With Time-Delay Compensation in Grid-Connected Inverter

The control of voltage source converters (VSCs) is now implemented on digital microprocessors. This digitalization has the drawback of time delay in the control loop. The goal of this research work was to investigate improvements that can be obtained from the combination of model-based and model-free time-delay compensation approaches. Deadbeat control (DBC) from model-based techniques and the method of moving the control variable’s sampling instants, or the pulse-width modulation (PWM) updating instants, from model-free time-delay compensation techniques, were put together as the proposed new method of time-delay compensation in this study. These controllers were thoroughly examined in terms of control algorithm design, system stability analysis, and sensitivity analysis of plant parameter perturbations. In addition, thorough Simulink-based computer simulations were conducted in this work to assess the performance of each controller. The proposed method compensated about <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$80~\mu \text{s}$ </tex-math></inline-formula> as compared with the time delay compensated by the conventional single-sampling method. This research work was limited to simulations only; hence, conducting experiments to further validate this research work could be a direction for further research.

Model predictive control for Takagi–Sugeno fuzzy model-based Spacecraft combined energy and attitude control system

A Combined Energy and Attitude Control System (CEACS) is a dual system in which flywheels are used as energy storage and attitude control devices. This work is a progress on CEACS for small satellites to improve the attitude accuracy. In this maiden work, the Fuzzy–MPC controller is introduced to regulate the CEACS attitude with both linear and nonlinear initial angles, and in the presence of actuator constraints. The nonlinear attitude model is transformed into a set of linear subsystems using the Takagi–Sugeno fuzzy modeling approach. The subsystem is designed with a MPC controller and a total control action is summed up using the parallel distributed compensation approach. The numerical results have been analyzed in terms of attitude pointing accuracies, actuator constraints, and energy consumed by the actuators. A performance comparison between the Fuzzy–MPC and Fuzzy–LQR controllers has also been done. The results validate that the Fuzzy-MPC controller achieves the desired CEACS attitude pointing accuracy of 0.0010° with a zero steady-state error and keeps the control torques within the actuator constraints. On the other hand, the Fuzzy–LQR controller gives some measurable steady-state error and achieves the CEACS attitude pointing accuracy of 0.0012°. Therefore, the Fuzzy–MPC based CEACS architecture not only achieves the desired pointing accuracies but also produces ten times smaller control torques than the Fuzzy–LQR controller, which result in a lower onboard power consumption.

Offsetting environmental impacts beyond climate change: the Circular Ecosystem Compensation approach

Since the Paris Agreement entered into force, climate neutrality and associated compensation schemes are even more on the agenda of politics and companies. Challenges of existing offsetting schemes include the rather theoretical saving scenario and the limited scope of considered impacts. To address some of these limitations, this paper proposes the Circular Ecosystem Compensation (CEC) approach based on monetization of LCA results and Ecosystem Valuation. CEC consists of six steps: i) carrying out a life cycle assessment, ii) reducing the environmental impacts, iii) determining environmental costs applying monetization methods, iv) deriving the environmental value based on restoration costs methods, v) implementing the ecological restoration of ecosystems and vi) monitoring of the renaturation measures. Thus, CEC allows to offset a broad set of environmental impacts beyond climate change (e.g., acidification, eutrophication, land use, water use) in a real ecosystem by renaturation of degraded ecosystems. Environmental burdens and environmental benefits are balanced on a monetary basis, as the renaturation measures are monetized and used to compensate the monetized LCA results, e.g., of a product, organization or individual. In a case study, the implementation of the approach is presented to show the practical implementation of the CEC. The challenges of CEC include the integration of further impact categories, the availability of up-to-date and reliable monetization methods, the asynchrony and time-lag of the compensation from an ecosystem and biodiversity perspective and the proof of cost-efficiency of the renaturation measures. It is further discussed, if CEC can be a step beyond “climate neutrality” towards “environmental neutrality”. The proposed approach should be further tested and is intended to foster progress in more comprehensive and robust offsetting of environmental impacts beyond climate change.