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The authors want to design an adaptive grasping control strategy without setting the expected contact force in advance to maintain grasping stable, so that the proposed control system can deal with unknown object grasping manipulation tasks.

The adaptive grasping control strategy is proposed based on bang-bang-like control principle and slippage detection module. The bang-bang-like control method is designed to find and set the expected contact force for the whole control system, and the slippage detection function is achieved by dynamic time warping algorithm.

The expected contact force can adaptively adjust in grasping tasks to avoid bad effects on the control system by the differences of prior test results or designers. Slippage detection can be recognized in time with variation of expected contact force manipulation environment in the control system. Based on if the slippage caused by an unexpected disturbance happens, the control system can automatically adjust the expected contact force back to the level of the previous stable state after a given time, and has the ability to identify an unnecessary increasing in the expected contact force.

Only contact force is used as feedback variable in control system, and the proposed strategy can save hardware components and electronic circuit components for sensing, reducing the cost and design difficulty of conducting real control system and making it easy to realize in engineering application field. The expected contact force can adaptively adjust due to unknown disturbance and slippage for various grasping manipulation tasks.

Helicopter fuselage vibration prediction is important to keep a safety and comfortable flight process. The helicopter vibration mechanism model is difficult to meet of demand for accurate vibration prediction. Thus, the purpose of this paper is to develop an intelligent algorithm for accurate helicopter fuselage vibration analysis.

In this research, a novel weighted variational mode decomposition (VMD)- extreme gradient boosting (xgboost) helicopter fuselage vibration prediction model is proposed. The vibration data is decomposed and reconstructed by the signal clustering results. The vibration response is predicted by xgboost algorithm based on the reconstructed data. The information transfer order between the controllable flight data and flight attitude are analyzed.

The mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) of the proposed weighted VMD-xgboost model are decreased by 6.8%, 31.5% and 32.8% compared with xgboost model. The established weighted VMD-xgboost model has the highest prediction accuracy with the lowest mean MAPE, RMSE and MAE of 4.54%, 0.0162, and 0.0131, respectively. The attitude of horizontal tail and cycle pitch are the key factors to vibration.

A novel weighted VMD-xgboost intelligent prediction methods is proposed. The prediction effect of xgboost model is highly improved by using the signal-weighted reconstruction technique. In addition, the data set used is collected from actual helicopter flight process.

Adaptive bump inlet can adaptively change the shape of inlet bump surface according to the flight speed of aircraft, ensuring that the inlet has good inlet-engine match performance in a wide speed range. This paper aims to use a composite flexible skin reinforced by shape memory alloy (SMA) fiber as the deformable structure at bump surface to realize the adjustable bump surface of adaptive bump inlet.

According to the deformation and load-bearing requirements of adaptive bump, SMA is applied to the design of adaptive bump inlet due to its characteristic of super-elasticity. A kind of SMA fiber is studied. A composite flexible skin reinforced by SMA is proposed, and its mechanical properties are analyzed. On this basis, an adaptive bump inlet is designed in which the composite flexible skin reinforced by SMA is used as bump surface, and the shape of the bump surface is adjusted by way of pressuring. The design scheme and specific parameters of the adaptive bump are given.

An adaptive bump surface that meets the design requirements of the inlet is designed, which can effectively adjust the inlet throat area with a throat area change rate of 20%.

An adaptive bump inlet with composite flexible skin as a deformable structure at bump surface is designed, and SMA is applied as the reinforcing fiber.

The purpose of this paper is to present the methods of concurrent optimization of the analogue and digital parts (software‐hardware) of estimating, identifying and filtering systems with adaptively adjusted analogue parts – adaptive estimation systems (AES).

Concurrent (complete) optimization of AES permits the determination of the most efficient algorithms for computing the estimates and the controls adjusting analogue units of AES in the way maximally improving the quality of observations delivered by them to the digital part. Performance of AES is assessed by the mean square error (MSE) of estimates which is constructed employing the models of input excitation, analogue and digital parts. Global extremum of MSE is searched by Bayesian methods taking into account the always bounded input range of AES and its possible overloading.

There are determined upper boundaries of potentially achievable accuracy of estimates, as well as optimal estimating and controlling observation units' algorithms, ensuring their achievement. New effects appearing in completely optimal AES are analysed.

The paper presents the backgrounds of new and analytically complex approach. To clarify basic ideas and methods, the simplest but useful for applications single input‐single output and single input‐multiple output models of ASE were considered. The obtained results create wide field for further investigations.

The results of the paper can be applied in the development of new classes of high‐efficient adaptive data acquisition, measurement, controlling, communication and other systems.

Concurrent optimisation of AES is important task having no general solution until now. Known approaches allow only the separate optimisation of the analogue and digital parts. Presented original approach enables the correct formalisation and solution of this task that permits the design and realization of systems with characteristics close to theoretically achievable ones and exceeding the characteristics of the known systems of similar predestination.

The purpose of this paper is to establish an adaptive assembly, to realize the adaptive changing of the models and to improve the flexibility and reliability of assembly change. For a three-dimensional (3D) computer-aided design (CAD) assembly in a changing process, there are two practical problems. One is delivering parameters’ information not smoothly. The other one is to easily destroy an assembly structure.

The paper establishes associated parameters design structure matrix of related parts, and predicts possible propagation paths of the parameters. Based on the predicted path, structured storage is made for the affected parameters, tolerance range and the calculation relations. The study combines structured path information and all constrained assemblies to build the adaptive assembly, proposes an adaptive change algorithm for assembly changing and discusses the extendibility of the adaptive assembly.

The approach would improve the flexibility and reliability of assembly change and be applied to different CAD platform.

The examples illustrate the construction and adaptive behavior of the assembly and verify the feasibility and reasonability of the adaptive assembly in practical application.

The adaptive assembly model proposed in the paper is an original method to assembly change. And compared with other methods, good results have been obtained.

The wind turbine (WT) is a complex system subjected to wind disturbances. Because the aerodynamics is nonlinear, the control is thus challenging. For the variation of wind speed when rated power is delivered at rated wind speed, the power is limited to the rate by the pitching of the blades of the turbine. This paper aims to address pitch control with the WT benchmark model. The possible use of appropriate adaptive controller design that modifies the control action automatically identifying any change in system parameters is explored.

To deal with pitch control problem when wind speed exceeds the rated wind speed of the WT, six digital self-tuning controller (STC) with different structures such as proportional integral (PI), proportional derivative (PD), Dahlin’s, pole placement, deadbeat and Takahashi has been taken herein. The system model is identified as a second-order autoregressive exogenous (ARX) model by three techniques for comparison: recursive least square method (RLS), RLS with exponential forgetting and RLS with adaptive directional forgetting identification methods. A comparative study of three identification methods, six adaptive controllers with the conventional PI controller and sliding mode controller (SMC), are shown.

As per the results, the best improvement in control of the output power by pitching in full load region of benchmark model is achieved by self-tuning PD controller based on RLS with adaptive directional forgetting method. The adaptive control design has a future in WT control applications.

A comparative study of identification methods, six adaptive controllers with the conventional PI controller and SMC, are shown here. As per the results, the best improvement in control of the output power by pitching in the full load region of the benchmark model has been achieved by self-tuning PD controller. The best identification method or the system is RLS with an adaptive directional forgetting method. Instead of a step input response design for the controllers, the controller design has been carried out for the stochastic wind and the performance is adjudged by the normalized sum of square tracking error (NSSE) index. The validation of the proposed self-tuning PD controller has been shown in comparison to the conventional controller with Monte-Carlo analysis to handle model parameter alteration and erroneous measurement issues.

Adaptive slicing is a key step in 3D printing as it is closely related to the building time and the surface quality. This study aims to develop an adaptive layering algorithm that can coordinate the optimization of printing quality and efficiency to meet different printing needs.

A multiobjective optimization model is established for printing quality, printing time and layer height based on the variation of surface features, profile slope and curvature of the model. The optimal solution is found by an improved method combining Newton's method and gradient method and adapts to different printing requirements by adjusting the parameter thresholds.

Several benchmarks are applied to verify this new method. The proposed method has also been compared with the uniform layering method, it reduces the volume error by 46.4% and shortens the printing time by 28.1% and is compared with five existing adaptive layering methods to demonstrate its superior performance.

Compared with other methods with only one layered result, this method is a demand-oriented algorithm that can obtain different results according to different needs and it can reach a trade-off between the building time and the surface quality.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

This paper aims to present a smooth transition adaptive hybrid impedance control for compliant connector assembly.

The dynamics of the manipulator is firstly presented with linear property. The controller used in connector assembly is inspired by human operation habits in similar tasks. The hybrid impedance control is adopted to apply force in the assembly direction and provide compliance in rest directions. The reference trajectory is implemented with an adaptive controller. Event-based switching strategy is conducted for a smooth transition from unconstrained to constrained space.

The method can ensure both ideal compliance behaviour with dynamic uncertainty and a smooth transition from unconstrained to constrained space. Also, the method can ensure compliant connector assembly with a good tolerance to the target estimation error.

The method can be applied in the connector assembly by “pushing” operation. The controller devotes efforts on force tracking and smooth transition, having potential applications in contact tasks in delicate environment.

As far as the authors know, the paper is original in providing a uniform controller for improving force and position control performance in both unconstrained and constrained space with dynamic uncertainty. The proposed controller can ensure a smooth transition by only adjusting parameters.

The purpose of this paper is to present a comprehensive self‐adaptive genetic algorithm (GA) based on fuzzy mechanism, aiming to improve both the optimizing capability and the convergence speed.

Many key factors that affect the performance of GAs are identified and analyzed, and their influences on the optimizing capability and the convergence speed are further elaborated, which prove to be very difficult to be described with explicit mathematical formulas. Therefore, a set of fuzzy rules are used to model these complicated relationships, in order to effectively guide the online self‐adaptive adjustments, such as changing the crossover and mutation probabilities, and thus to improve the optimizing capability and convergence speed.

Simulation results illustrates that, compared with a normal GA and another self‐adaptive GA based on explicit mathematical modeling of the key factors, the new GA is more advanced in terms of the optimizing capability and the convergence speed.

This paper develops a fuzzy‐rule‐based approach to describe the relationships between multiple GA parameters and online states, and the approach is useful in the design of a comprehensive self‐adaptive GA.