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The fundamental principle of the transient state control method for turbofan engines, which is based on the acceleration ratio of high-pressure rotational speed (N-dot), involves sacrificing a portion of the safety margin to obtain satisfactory acceleration performance. However, it could induce surge in the engine's compressor. To prevent the destructive damage caused by surge to both the engine and its components, a surge-elimination control strategy for the engine based on an N-dot controller is proposed. First, the engine mathematical model, which incorporates the effects of engine volumetric dynamics, stall zone characteristics, and combustion chamber flameout characteristics, is established to simulate surge mechanism. Subsequently, the acceleration schedule of the N-dot is calculated by employing sequential quadratic programming (SQP) algorithm to solve the multiconstraint optimization problem, while designing the transition state controller of N-dot based on a high-order filter. Finally, the surge detection logic and surge-elimination strategy based on the µ-correction method are proposed and designed to realize active control of surge elimination. The simulation results demonstrate that the N-dot control method offers significant advantages in mitigating the steady-state errors resulting from inevitable engine degradations. The surge state is effectively suppressed by the proposed surge-elimination control method, and the surge duration is significantly shorten during the acceleration phases. Furthermore, compared to the one without any surge-elimination control, the proposed method decreases the acceleration time by 5.53%. [ABSTRACT FROM AUTHOR]

Electro-hydraulic systems are extensively utilized to generate desired acceleration waveforms to provide a vibration environment for testing the performance and reliability of objects in various industrial applications. However, as electro-hydraulic systems are often affected by some inevitable drawbacks resulted from hydraulic nonlinearities, unwanted dynamic variations and disturbances, the generated acceleration waveform is generally far behind the expectation. In this paper, a convex combined adaptive controller with input shaping technique is proposed for enhancing the transient acceleration waveform replication accuracy of electro-hydraulic systems. The proposed controller is comprised of a three variable controller at the bottom level, an input shaping technique controller at the middle level, and a convex combined adaptive controller at the upper level. The three variable controller is firstly utilized for the establishment of a fundamental closed-loop acceleration control system, and then the input shaping technique controller is constructed by introducing an offline designed inverse prefilter utilizing the multi-innovation recursive least squares algorithm and the zero magnitude error tracking algorithm. The convex combined adaptive controller at the upper level is comprised of two individual adaptive filters with high and low step sizes, which provides the merits of fast convergence rate and high tracking accuracy, and it is further exploited to address for system's dynamic variations, model uncertainties and unexpected perturbations. Comparative experiments of the proposed controller with a manually generated random waveform and a recorded earthquake waveform as the testing inputs are conducted on a typical electro-hydraulic test bench, and the corresponding results demonstrate the feasibility and superiority of the proposed controller in improving the transient acceleration waveform replication performance of electro-hydraulic systems. • A new transient acceleration waveform replication strategy using convex combined adaptive controller with input shaping technique is proposed. • Input shaping technique controller acting as a prefilter is adopted to enhance tracking frequency bandwidth and reduce phase delay error. • Convex combined adaptive controller is exploited to address for system's dynamic variations, model uncertainties and unexpected disturbances. • Experimental results validate feasibility and superiority of the proposed controller than the other comparative methods. [ABSTRACT FROM AUTHOR]

In a bilateral control system, reducing the information-transmission channel between the master and slave systems has advantages, such as suppressing data traffic, reducing stored data, and simplifying the control-system design. The position/force hybrid-control-type bilateral control system can realize stable and highly transparent bilateral control; however, it requires four transmission channels between the master and slave systems to transmit the position and force information. Several types of conventional two-channel controllers are difficult to operate and contact with hard environments. A two-channel controller with a performance equivalent to that of a four-channel controller exists, but it still requires local position control loops. Therefore, this study proposes a force-symmetric type two-channel bilateral control system based on force control systems with robust acceleration controllers using second-order disturbance observers (DOBs) among higher-order DOBs. Bilateral control systems have two control goals: synchronization of the position of the master-slave system, which is a position-related control goal, and artificial realization of the law of action-reaction between the master-slave system, which is a force-related control goal. Methods using low-order DOBs, such as zero- and first-order DOBs, cannot achieve the position-related control goal. In contrast, the proposed method can achieve both the position and force control goals simultaneously, even though it only has force transmission channels and control loops. This study also showed that the performance of the proposed two-channel bilateral control system is equivalent to that of a four-channel bilateral control system that transmits both position and force information. The effectiveness of the proposed method was confirmed through experiments.

This study introduces a numerically disturbed experimentation to address the shake table control degradation commonly observed in shake table experiments. This degradation is caused by nonlinear characteristics, such as seismic damage, in the experiments; however, observing such nonlinear characteristics is a major purpose of these experiments. In the proposed numerically disturbed experimentation, a structure is numerically simulated, and its structural responses are fed back as the disturbance signal to the table in the physical domain via real-time interaction. This enables us to examine the control performance of a shake table with a structure, without having to place an actual structure on it. This experimentation is beneficial in cases wherein new control methods are applied for shake table control because the control performance can be examined safely and efficiently under various structural conditions by using numerical simulations. The proposed experimentation was applied to the shake table control examination of nonlinear signal-based control (NSBC), which has a nonlinear signal feedback action for nonlinear structural dynamics, as well as inversion-based control (IBC), which is a common feedforward method. In the numerically disturbed experiments, NSBC accurately realized a seismic acceleration record on the shake table with severe nonlinear characteristics, whereas IBC exhibited control degradation due to nonlinear characteristics. Similar results were obtained using actual shake table experiments with a steel structure. Therefore, the proposed numerically disturbed experimentation can be an alternative to shake table experiments using structures.

The surging popularity of adopting industrial robots in smart manufacturing has led to an increasing trend in the simultaneous improvement of the energy costs and operational efficiency of motion trajectory. Motivated by this, multi-objective trajectory planning subject to kinematic and dynamic constraints at multiple levels has been considered as a promising paradigm to achieve the improvement. However, most existing model-based multi-objective optimization algorithms tend to come out with infeasible solutions, which results in non-zero initial and final acceleration. Popular commercial software toolkits applied to solve multi-objective optimization problems in actual situations are mostly based on the fussy conversion of the original objective and constraints into strict convex functions or linear functions, which could induce a failure of duality and obtain results exceeding limits. To address the problem, this paper proposes a time-energy optimization model in a phase plane based on the Riemann approximation method and a solution scheme using an iterative learning algorithm with neural networks. We present forward-substitution interpolation functions as basic functions to calculate indirect kinematic and dynamic expressions introduced in a discrete optimization model with coupled constraints. Moreover, we develop a solution scheme of the complex trajectory optimization problem based on artificial neural networks to generate candidate solutions for each iteration without any conversion into a strict convex function, until minimum optimization objectives are achieved. Experiments were carried out to verify the effectiveness of the proposed optimization solution scheme by comparing it with state-of-the-art trajectory optimization methods using Yalmip software. The proposed method was observed to improve the acceleration control performance of the solved robot trajectory by reducing accelerations exceeding values of joints 2, 3 and 5 by 3.277 rad/s2, 26.674 rad/s2, and 7.620 rad/s2, respectively. [ABSTRACT FROM AUTHOR]

In this article, a new soft starting control scheme based on an artificial neural network (ANN) is presented for a three-phase induction motor (IM) drive system. The main task of the control scheme is to keep the accelerating torque constant at a level based on the value of reference acceleration. This is accomplished by the proper choice of the firing angles of thyristors in the soft starter. Using the ANN approach, the complexity of the online determination of the thyristors firing angles is resolved. The IM torque-speed characteristic curves are firstly used to train the ANN model. Secondly, the IM- soft starter system is modeled using MATLAB/SIMULINK. To prove the effectiveness of the proposed ANN-based acceleration control scheme, different reference accelerations and loading conditions are applied and investigated. Finally, a laboratory prototype of 3 kW soft starter is implemented. The proposed control scheme is executed in a real-time environment using a digital signal processor (Model: TMS320F28335). The simulation and real-time results significantly confirm that the proposed controller can efficiently reduce the IM starting current and torque pulsations. This in turn ensures a smooth acceleration of the IM during the starting process. Moreover, the proposed control scheme has the superiority over several soft starting control schemes since it has a simple control circuit configuration, less required sensors, and low computational burden of the control algorithm.

Abstract Measuring and controlling external force from the environment and human beings are essential to realize the future application of the robot systems for medical, nursing, and personal support systems. This paper proposes a friction and noise suppression for force control system based on the integration of the reaction torque observer and force (torque) sensor information. The proposed method performs external force estimation by integrating the low-frequency component information of the force sensor and the high-frequency component of the force information estimated by reaction torque observer (RTOB). By using the low-frequency component of the force sensor, the effect of static friction can be suppressed, and the high-frequency part of RTOB can be used to attenuate the noise component. As a result, the performance of the force control system can be enhanced. The proposed method is evaluated through the experiments of the force control and bilateral control as a position/force hybrid control.

This study proposes a method for simultaneous implementation of performance improvement, decoupling of null space and workspace, and suppressing operational force for a hybrid control system with a redundant degree of freedom (RDOF). Hybrid control systems with RDOF are necessary for motion control systems to achieve future applications for human support systems and robots in unknown and open environments. This article shows that the acceleration controller performs decoupling of task (modal) spaces in the redundant system. Additionally, this article proposes a novel method based on the extension of an acceleration-based disturbance observer in modal space for position/force hybrid controllers to the redundant systems. The proposed method contributes to the suppression of operating (inertia) force and interference from the null space with the simplification of inverse kinematics. Experiments of the scaled bilateral control, which is one of the hybrid control systems for the master and slave systems with RDOF, are conducted to validate the proposed method. [ABSTRACT FROM AUTHOR]

Although the virtual synchronous generator provides a grid-friendly operational mode for power converters, it may also introduce disadvantages similar to a traditional synchronous generator such as power oscillation in the parallel mode due to large virtual inertia. This article proposes an additional damping strategy to suppress the power oscillation. After analyzing the relationship between the output power and the angular acceleration, a damping strategy is designed by the acceleration control with a disturbance compensation. Small-signal analysis is also applied to study the stability of the proposed method. Finally, experiments are carried out to verify the proposed auxiliary damping method. [ABSTRACT FROM AUTHOR]

Generating robot motion for multiple tasks in dynamic environments is challenging, requiring an algorithm to respond reactively while accounting for complex nonlinear relationships between tasks. In this article, we develop a novel policy synthesis algorithm, Riemannian motion policy (RMP)flow, based on geometrically consistent transformations of RMPs. RMPs are a class of reactive motion policies that parameterize non-Euclidean behaviors as dynamical systems in intrinsically nonlinear task spaces. Given a set of RMPs designed for individual tasks, RMPflow can combine these policies to generate an expressive global policy, while simultaneously exploiting sparse structure for computational efficiency. We study the geometric properties of RMPflow and provide sufficient conditions for stability. Finally, we experimentally demonstrate that accounting for the natural Riemannian geometry of task policies can simplify classically difficult problems, such as planning through the clutter on high-degree-of-freedom manipulation systems. Note to Practitioners—Requirements on safety and responsiveness for collaborative robots have driven a need for new ideas in control design that bridge between standard objectives in low-level control (such as trajectory tracking) and high-level behavioral objectives (such as collision avoidance) often relegated to planning systems. Modern results from geometric control, which promise stable controllers that can smoothly and safely transition between many behavioral tasks, therefore, become highly relevant. However, for years, this field has remained inaccessible due to its mathematical complexity. This article aims to: 1) make those ideas accessible to robotics and control experts by recasting them in a concrete algorithmic framework amenable to controller design and 2) to additionally generalize them to better satisfy the specific needs of robotic behavior generation. Our experiments demonstrate that the resulting controllers can engender natural behavior that adapts instantaneously to changing surroundings with zero planning while performing manipulation tasks. The framework is gaining traction within the robotics community, finding increasing application in areas, such as autonomous navigation, tactile servoing, and multi-agent systems. Future research will address learning these controllers from data to simplify that process of design and tuning, which at present can require experience. [ABSTRACT FROM AUTHOR]

This paper investigates a multiple sensor fusion based drift compensation technique for a mecanum wheeled mobile robot platform. The mobile robot is equipped with high-precision encoders integrated to the wheels and four accelerometers placed on its chassis. The proposed algorithm combines the information from the encoders and the acceleration sensors to estimate the total drift in the acceleration dimension. The inner loop controller is designed utilizing a disturbance-observer-based acceleration control structure which is blind against the slipping motion of the wheels. The estimated drift acceleration from the sensor fusion is then mapped back to the joint space of the robot and used as additional compensation over the existing controllers. The proposed algorithm is tested on a series of experiments. The results of the experiments are also compared with those of a recent study in order to provide a benchmark evaluation. The enhanced tracking performance yielding towards smaller error magnitudes in the experiments illustrate the efficacy and success of the proposed control architecture in attenuating the positioning drift of mecanum wheeled robots. [ABSTRACT FROM AUTHOR]

The surging popularity of adopting industrial robots in smart manufacturing has led to an increasing trend in the simultaneous improvement of the energy costs and operational efficiency of motion trajectory. Motivated by this, multi-objective trajectory planning subject to kinematic and dynamic constraints at multiple levels has been considered as a promising paradigm to achieve the improvement. However, most existing model-based multi-objective optimization algorithms tend to come out with infeasible solutions, which results in non-zero initial and final acceleration. Popular commercial software toolkits applied to solve multi-objective optimization problems in actual situations are mostly based on the fussy conversion of the original objective and constraints into strict convex functions or linear functions, which could induce a failure of duality and obtain results exceeding limits. To address the problem, this paper proposes a time-energy optimization model in a phase plane based on the Riemann approximation method and a solution scheme using an iterative learning algorithm with neural networks. We present forward-substitution interpolation functions as basic functions to calculate indirect kinematic and dynamic expressions introduced in a discrete optimization model with coupled constraints. Moreover, we develop a solution scheme of the complex trajectory optimization problem based on artificial neural networks to generate candidate solutions for each iteration without any conversion into a strict convex function, until minimum optimization objectives are achieved. Experiments were carried out to verify the effectiveness of the proposed optimization solution scheme by comparing it with state-of-the-art trajectory optimization methods using Yalmip software. The proposed method was observed to improve the acceleration control performance of the solved robot trajectory by reducing accelerations exceeding values of joints 2, 3 and 5 by 3.277 rad/s2, 26.674 rad/s2, and 7.620 rad/s2, respectively.

We present a small-scale pneumo-hydraulic energy storage system (ss-CAES) which can provide frequency support to a power grid, as fast instantaneous reserve. This system is designed to be maintained at rest until called, thus avoiding idling costs. It utilizes a hydraulic drive train which transmits very high torque directly to the shaft of a synchronous generator, thus enabling rapid acceleration of the rotor. When an under-frequency event occurs, the generator must be accelerated from rest and synchronized to the grid. Here, we show that this is achieved by a ballistic synchronization approach which computes and follows an acceleration trajectory which simultaneously synchronizes both phase and frequency. A two-stage strategy is employed which switches from the ballistic acceleration trajectory to a grid-following mode once the synchronization conditions have been met. Computer simulations indicate that this approach enables very rapid synchronization of a model system to the grid in

Loaded walking with a rucksack results in both gravitational and inertial forces of the load that must be borne by human carriers. The inertial force may be the source of metabolic burden and musculoskeletal injuries. This paper presents a lightweight backpack with a disturbance observer-based acceleration control to minimize the inertial force. The backpack was evaluated by seven participants walking on a treadmill at 5 km h−1 with a 19.4 kg load. Three experimental conditions were involved, including walking with a locked load (LOCKED), with an acceleration-controlled load (ACTIVE) using the designed backpack and walking with the same load using a rucksack (RUCKSACK). Our results showed that the ACTIVE condition reduces the load acceleration by 98.5% on average, and reduce the gross metabolic power by 8.0% and 11.0% as compared to LOCKED and RUCKSACK conditions respectively. The results demonstrate that the proposed active backpack can improve the loaded walking economy compared with a conventional rucksack in level-ground walking. [ABSTRACT FROM AUTHOR]

Research on longitudinal motion control has so far mainly focused on high level planning and control techniques in high speed situations, for example highway driving, and the worst case scenarios there. Low level acceleration control is found only rarely in literature. With the development of automated vehicles, the controllers need to be able to handle the worst case scenarios at low velocities, such as traversing obstacles carefully. In this paper we present a novel approach for a low level acceleration controller that uses its knowledge of the road profile ahead to control engine and brakes proactively. The main contribution is the introduction of a suitable model predictive controller and its implementation in a real vehicle. In addition, the proposed control loop can be easily enhanced by employing existing control approaches. We present simulated data as well as experimental results for a state-of-the-art literature approach and our model predictive controller. Our data clearly shows that the control performance is significantly improved by our predictive solution. [ABSTRACT FROM AUTHOR]

A novel fault‐tolerant model predictive control (MPC)‐based trajectory tracking approach for an aerial vehicle is presented in this study. A generalised online sequential extreme learning machine is introduced first to identify the corresponding coefficients of actuator faults. Subsequently, a robust trajectory tracking control is developed based on MPC, where the system constraints can be effectively considered in the designed control scheme. Trajectory tracking control is achieved by controlling only the acceleration of the aerial robot in the MPC structure. This leads to less computational burden and faster closed‐loop dynamics. In addition, an effective disturbance observer is employed, which can satisfactorily capture the effects of unmodelled dynamics and external disturbances on the system dynamics. The stability of the proposed control algorithm is proved based on the Lyapunov theory under realistic assumptions. Finally, the proposed control strategy is applied to a quadrotor unmanned aerial vehicle. Both simulation and experimental results are presented to demonstrate the effectiveness of the introduced fault‐tolerant control scheme. The obtained results suggest that the designed control approach is capable of stabilising the attitude and providing acceptable performance in tracking a predefined trajectory in a three‐dimensional environment in the simultaneous presence of actuator faults and external disturbances. [ABSTRACT FROM AUTHOR]

Measuring and controlling external force from the environment and human beings are essential to realize the future application of the robot systems for medical, nursing, and personal support systems. This paper proposes a friction and noise suppression for force control system based on the integration of the reaction torque observer and force (torque) sensor information. The proposed method performs external force estimation by integrating the low-frequency component information of the force sensor and the high-frequency component of the force information estimated by reaction torque observer (RTOB). By using the low-frequency component of the force sensor, the effect of static friction can be suppressed, and the high-frequency part of RTOB can be used to attenuate the noise component. As a result, the performance of the force control system can be enhanced. The proposed method is evaluated through the experiments of the force control and bilateral control as a position/force hybrid control. [ABSTRACT FROM AUTHOR]

Torsion-torque-sensing-based load-side acceleration control is proposed for a two-inertia resonance system in this paper. This control uses a torsion torque sensor installed in a reduction gear, and consists of a torsion torque controller and load-side disturbance observer (DOb). In the load side of the gear, the proposed control structure is equivalent to a conventional DOb-based acceleration controller on the motor side. Therefore, because the proposed controller suppresses resonance vibration in an acceleration dimension, torsion-torque-sensing-based load-side acceleration control has the capability of controlling the load-side acceleration. The problem of the conventional acceleration controller and the effectiveness of the proposed acceleration controller are verified by theoretical analysis, numerical simulations, and experiments. Robust stability for parameter variation and stable regions of control bandwidth are also analyzed. [ABSTRACT FROM AUTHOR]

It is possible to obtain high efficiencies in the combined generation of electrical and thermal energy using micro-turbines. To study their operation within electrical networks, connected or isolated from the distribution network, it is necessary to use models that faithfully simulate their operation. This work studies the standalone operation of the micro-turbine and makes modifications to the model developed by "Lasseter". Thus, a new model is proposed that integrates the acceleration control, improving the accuracy in transient operation. Finally, validation of the proposed modifications is carried out by comparison with actual performance data of a Capstone C30 micro turbine. The simulations performed in this study show that including the acceleration control leads to major disturbances in the DC voltage, which has to be taken into account when designing the chopper of the converter. [ABSTRACT FROM AUTHOR]

Electro-hydraulic shake table (EHST) is vital seismic testing equipment in earthquake engineering for the assessment of structures subject to dynamic vibration excitations. The EHST system can be generally simplified as an electro-hydraulic servo system with prominent acceleration replication requirement. In order to improve the acceleration tracking performance of a typical EHST system, a novel realtime acceleration tracking strategy combining inverse compensation technique and neural-based adaptive controller is presented in this paper. The traditional three variable controller (TVC) is applied to the EHST system for obtaining a preliminary acceleration tracking accuracy in advance, and then the multi-innovation stochastic gradient algorithm is utilized to estimate the discrete parametric transfer function of the TVC controlled EHST system. Next, the zero magnitude error tracking technique, which is capable of handling non-minimum phase zeros, is exploited to design a stable and casual inverse model, and subsequently the parametric inverse compensation technique for the EHST system is constructed. Finally, a neural-based online adaptive controller is incorporated to the offline designed parametric inverse compensator as an outer loop, and the side effects of the system's inherent nonlinearities, varying dynamics, and external uncertainties are further addressed. The proposed controller is successfully implemented in the control system of a unidirectional EHST test rig using xPC target rapid prototyping technique, and experimental results reveal that a superior acceleration replication performance is achieved in contrast to the other comparative controllers.

Electro-hydraulic shaking tables are widely used for vibration testing where high force and displacement amplitudes are required. In particular, they are a vital tool in seismic testing, enabling the development of buildings and other structures which are earthquake resistant. Three-variable-control (TVC) is commonly used for the control of multi-degrees of freedom (DOFs) electro-hydraulic shaking tables. However, the coupling between the DOFs is often significant and is not compensated by TVC. In this paper, an acceleration decoupling control (ADC) method is presented for a 6 DOFs electro-hydraulic shaking table system to improve the acceleration tracking performance and decouple the motion in task space. The gravitational, Coriolis, and centripetal forces are compensated for in joint space based on a dynamic model of the shaking table. Modal control is used to transform the coupled dynamics into six independent systems. Inverse dynamics models are used to cancel the differences in actuator dynamics. The proportional gains in modal space are tuned heuristically to give sufficient stability margins to provide robustness in the presence of modeling errors. The input filter and feedforward controller in TVC are added to improve the acceleration tracking performance of each independent system. Experimental acceleration frequency responses are used to demonstrate the effectiveness of ADC, and in particular these show a consistent reduction in cross-axis coupling compared to TVC. Moreover, only four parameters need to be tuned, as opposed to 36 for TVC, and the method provides a viable route to improving the accuracy of seismic testing in the future. [ABSTRACT FROM AUTHOR]

Predictive cruise control concerns designing controllers for autonomous vehicles using the broadcasted information from the traffic lights such that the idle time around the intersection can be reduced. This study proposes a novel adaptive optimal control approach based on reinforcement learning to solve the predictive cruise control problem of a platoon of connected and autonomous vehicles. First, the reference velocity is determined for each autonomous vehicle in the platoon. Second, a data‐driven adaptive optimal control algorithm is developed to estimate the gains of the desired distributed optimal controllers without the exact knowledge of system dynamics. The obtained controller is able to regulate the headway, velocity, and acceleration of each vehicle in a suboptimal sense. The goal of trip time reduction is achieved without compromising vehicle safety and passenger comfort. Numerical simulations are presented to validate the efficacy of the proposed methodology. [ABSTRACT FROM AUTHOR]

The plasma compression fusion device (PCFD) generates the energy gain by plasma compression-induced nuclear fusion. This concept has the capability of maximizing the product of plasma pressure and energy confinement time to maximize the energy gain, and thus give rise to fusion ignition conditions. The preferred embodiment of this original concept uses a hollow cross-duct configuration of circular cross section in which the concentrated magnetic energy flux from two pairs of opposing curved-headed counter-spinning conical structures (possibly made from an alloy of tungsten with high capacitance) whose outer surfaces are electrically charged compresses a gaseous mixture of fusion fuel into a plasma, heated to extreme temperatures and pressures. The generated high-intensity electromagnetic (EM) radiation heats the plasma and the produced magnetic fields confine it in between the counter-spinning conical structures, named the dynamic fusors (four of them—smoothly curved apex sections opposing each other in pairs). The dynamic fusors can be assemblies of electrified grids and toroidal magnetic coils, arranged within a conical structure whose outer surface is electrically charged. The cross-duct inner surface surrounding the plasma core region is also electrically charged and vibrated in an accelerated mode to minimize the flux of plasma particles (including neutrals) from impacting the PCFD surfaces and initiating a plasma quench. The fusion fuel (preferably deuterium gas) is introduced into the plasma core through the counter-spinning conical structures, namely, injected through orifices in the dynamic fusor heads. There is envisioned another even more compact version of this concept, which uses accelerated vibration in a linear-duct configuration (using two counter-spinning dynamic fusors only) and would best be suited for fusion power generation on aircraft, or main battle tanks. The concept uses controlled motion of electrically charged matter through accelerated vibration and/or accelerated spin subjected to smooth, yet rapid acceleration transients, to generate extremely high-energy/high-intensity EM radiation (fields of high-energy photons) which not only confines the plasma but also greatly compresses it so as to produce a high power density plasma burn, leading to ignition. The PCFD concept can produce power in the gigawatt to terawatt range (and higher) with input power in the kilowatt to megawatt range and can possibly lead to ignition (self-sustained) plasma burn. Several important practical engineering and operational issues with operating a device such as the PCFD are discussed. [ABSTRACT FROM AUTHOR]

Abstract This paper focuses on the design of a novel path following control concept for fixed-wing aircraft, which systematically incorporates the nonlinearities of the flight dynamics. By introducing an acceleration based inner loop control, feedforward acceleration demands of nonlinear 3D paths can be directly taken into account. Furthermore, the nonlinear effects of airspeed, orientation, and gravity are considered separately by implementing a cascaded design and feedback linearization. As a result, robust performance of the path following control is achieved even for wind speeds in the order of the aircraft's airspeed and path accelerations significantly higher than the gravitational acceleration. By further including direct lift control, a high-bandwidth vertical acceleration control is developed. Results of flight experiments show that the designed control concept is particularly beneficial in terms of the tracking performance for 3D paths, the incorporation of input constraints, the robustness against wind and turbulence effects, and the ease of implementation as well as the low computational complexity. [ABSTRACT FROM AUTHOR]

Energy autonomous sensors for I4.0 applications powered by kinetic energy harvesters (KEHs) are widely discussed – especially in terms of vibration harvesting. Typically, industrial linear stages offer weak vibrations, so other inertia‐based harvesting methods are investigated. This study investigates the usability of human motion energy harvesters in industrial linear motion technology for the first time. Two KEHs – harvesting swing or shocks, respectively – are tested while controlling the parameters velocity, acceleration, and jerk‐limitation according to the real applications' parameter ranges. The swing‐KEH and the shock‐KEH harvested up to 106 and 124 mW, respectively. Furthermore, a parameter study is performed assuming constant driving lengths with optimised stroke rates to obtain a generalised power and energy profile for each harvester. The analytically obtained overall average power is 22 mW for the swing‐KEH and 14 mW for the shock‐KEH. The analytical investigation revealed that a reciprocal dependency of performance and velocity exists for both KEHs, respectively. Both experimental and analytical parts show that the wireless sensor node for I4.0 on industrial linear stages can be powered by harvesters made for human motions. [ABSTRACT FROM AUTHOR]

Abstract Electro-hydraulic shake table (EHST), also known as earthquake simulator, is of considerable significance in civil engineering for evaluating structures or infrastructures subjected to earthquake ground motions. However, reproduction of prescribed accelerations at table for EHST systems remains to be imperfect as the whole systems are confronted with hydraulic nonlinearity, varying dynamics, unexpected disturbance, etc. For enhancing the acceleration tracking performance of EHST systems, an acceleration waveform reproduction strategy using offline designed parametric feedforward compensator (PFC) and online functional link adaptive controller (FLAC) is proposed in this paper. The PFC controller is established on the basis of classical three variable controller (TVC) as an inner compensation loop, in which multi-innovation forgetting gradient (MIFG) algorithm together with zero magnitude error tracking (ZMET) technique are utilized during the design process. The FLAC controller is combined to the PFC controller as an outer loop for further acceleration enhancement purpose, and the controller's nonlinear mapping ability is achieved with trigonometric expansion implementation. Following theoretical analysis of the proposed controller, comparative experiments are performed on an established unidirectional EHST test bench with both random and real-time recorded earthquake input waveforms. The experimental results validate the feasibility and superiority of the proposed acceleration reproduction strategy. Highlights • A new compound acceleration control strategy using parametric feedforward compensator and functional link adaptive controller is proposed. • An inner-loop parametric feedforward compensator is designed with MIFG algorithm and ZMET technique. • An outer-loop functional link adaptive controller with nonlinear mapping ability is developed to address the system's nonlinearity and varying dynamics. • Experimental results validate the superiority of the proposed controller than the other comparative methods. [ABSTRACT FROM AUTHOR]

Objective: For occupant protection, it is important to understand how a car's deceleration time history in crashes can be designed using efficient of energy absorption by a car body's structure. In a previous paper, the authors proposed an energy derivative method to determine each structural component's contribution to the longitudinal deceleration of a car passenger compartment in crashes. In this study, this method was extended to 2 dimensions in order to analyze various crash test conditions. The contribution of each structure estimated from the energy derivative method was compared to that from a conventional finite element (FE) analysis method using cross-sectional forces.Method: A 2-dimensional energy derivative method was established. A simple FE model with a structural column connected to a rigid body was used to confirm the validity of this method and to compare with the result of cross-sectional forces determined using conventional analysis. Applying this method to a full-width frontal impact simulation of a car FE model, the contribution and the cross-sectional forces of the front rails were compared. In addition, this method was applied to a pedestrian headform FE simulation in order to determine the influence of the structural and inertia forces of the hood structures on the deceleration of the headform undergoing planar motion.Result: In an oblique impact of the simple column and rigid body model, the sum of the contributions of each part agrees with the rigid body deceleration, which indicates the validity of the 2-dimensional energy derivative method. Using the energy derivative method, it was observed that each part of the column contributes to the deceleration of the rigid body by collapsing in the sequence from front to rear, whereas the cross-sectional force at the rear of the column cannot detect the continuous collapse. In the full-width impact of a car, the contributions of the front rails estimated in the energy derivative method was smaller than that using the cross-sectional forces at the rear end of the front rails due to the deformation of the passenger compartment. For a pedestrian headform impact, the inertial and structural forces of the hood contributed to peaks of the headform deceleration in the initial and latter phases, respectively.Conclusions: Using the 2-dimensional energy derivative method, it is possible to analyze an oblique impact or a pedestrian headform impact with large rotations. This method has advantages compared to the conventional approach using cross-sectional forces because the contribution of each component to system deceleration can be determined. [ABSTRACT FROM AUTHOR]

Pan-tilt robotic platforms are widely used to point sensor arrays (e.g. cameras, radars and antennas) in certain directions toward the target. Such platforms may suffer from external disturbances due to terrain changes, high-frequency vibrations and sudden shocks, wind and other environmental factors. These disturbances and hence small angular displacements may cause large position errors if the target is too far away. Therefore, high precision stabilization is required for these platforms to converge to the desired orientation and maintain it by rejecting unknown disturbances. In motion control, robust stabilization problem is usually tackled by employing angular acceleration feedback. However, obtaining reliable acceleration information is a challenging task. In this paper, we propose a novel master-slave type Kalman filter algorithm which consists of an extended Kalman filter (EKF) and an inverse Φ-algorithm in a master-slave configuration to estimate reliable angular acceleration signals by fusing 3-axis gyroscope, 3-axis accelerometer and 3-axis magnetometer data. Performance of the proposed sensor fusion algorithm is evaluated on a high fidelity simulation model by using the estimated accelerations as feedback signals in the stabilization control of a 2-DOF pan-tilt system subject to external disturbances. As the acceleration feedback is incorporated into the control loop, higher stabilization is achieved. The performance of the proposed fusion algorithm is compared to Newton predictor enhanced Kalman filter (NPEKF) and the error state Kalman filter (ErKF). The proposed master-slave Kalman filter outperforms the Newton predictor enhanced Kalman filter whereas the results obtained by the proposed algorithm and the error state Kalman filter are comparable. [ABSTRACT FROM AUTHOR]

Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing modelbased acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study. [ABSTRACT FROM AUTHOR]

Electro-hydraulic hybrid testing, which imposes the desired acceleration and force on the specimen in parallel, is a novel structural testing method for structures or facilities and is extensively applied in civil and seismic engineering. To efficiently suppress the surplus force resulted from the acceleration motion of the specimen during the force control process, a compound force tracking control strategy comprised of a force and voltage feedforward controller (FVFC) and feedforward inverse with disturbance observer (FIDOB) controller is presented in this research. The FVFC controller as an inner loop feedforward component is first constituted by the generated force feedback signal and the real-time control voltage signal of the acceleration actuator so as to compensate for the acceleration motion of the specimen for a better disturbance rejection performance, and the FVFC controller requires little information of the system dynamic structure or parameters. The FIDOB controller composed by a feedforward inverse controller and an inverse model-based disturbance observer is then combined with the FVFC controller as an outer loop to further deal with the remaining disturbances for the FVFC-controlled electro-hydraulic hybrid testing system. The inverse model applied in the FIDOB controller is obtained with the frequency domain complex curve fitting and zero magnitude error tracking technology with respect to the proportional–integral controlled static loading system. Hence, the proposed controller integrates the advantages of the FVFC controller and FIDOB controller in terms of easy implementation and high tracking performance. Finally, comparative experiments are carried out on an uniaxial electro-hydraulic hybrid testing test rig with the xPC rapid prototyping technology and experimental results demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a new algorithm of generating pulse sequence for numerical controllers. Different from the existing algorithms using which the generated pulse frequency is fixed at one displacement increment, the proposed algorithm can generate pulse sequence with real-time changing frequency following the reference displacement command, so that fast-changing velocity requirements in machining can be satisfied. Moreover, by adopting the proposed algorithm, the generated velocity and acceleration can be also controlled within the range of the motor system to achieve better performance. Structure and parameters of the numerical controller which adopts the proposed algorithm are thoroughly discussed in this paper, and methods of adjusting the controller parameters to adapt to the servo system's torque-frequency characteristic are also introduced. At last, effectiveness of the proposed algorithm and effectiveness of the proposed methods for velocity and acceleration control are demonstrated by simulations.

A novel controller for three-dimensional contouring control of three-degrees-of-freedom (3-DOF) robotic manipulators is presented in this paper. The proposed controller comprises of an independent joint controller, designed in the configuration space, and a sliding mode controller that enforces desired dynamics for the tracking error projections to the Frenet-Serret frame. Therefore, the presented controller has a hybrid structure and it is named as hybrid contouring controller. In this paper, contour tracking with constant magnitude tangential velocity is discussed. Reference trajectory is generated using the time based spline approximation in order to provide a smooth reference path. The proposed hybrid contouring controller was experimentally compared with the independent joint controller that is designed in the acceleration control framework with disturbance observer. Experimental results, undertaken on a delta robot, showed that hybrid contouring controller outperforms independent joint control architecture. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of path following for unmaned cars using only GNSS positionning. Several papers have already addressed the lane keeping, usually restricting the focus to the computation of the optimal steering wheel angle, therefore usually offering a good solution in either straight lines or curves, but rarely both. Moreover the GNSS receiver have a sampling time higher than the required one for the proposed strategies in the literature. In this paper, a control algorithm is proposed for the steering wheel angle, with adaptation of the speed of the car, in order to provide a solution working both for straight lines and curves by using only GNSS. The presented solution has been used in real conditions to realize the demonstration “speed synchronization at intersections using intervehicular communication, x.icars” shown at the Intelligent Transportation System World Congress in Bordeaux, 2015 1 1 https://www.youtube.com/watch?v=KBx6qks8kCI . [ABSTRACT FROM AUTHOR]