ISA transactions最新文献

In this paper, we propose an adaptive nonlinear strategy for the motion and force control of manipulators with flexible joints. Our approach provides force control when in contact and robust motion control in its absence, all without the need for a control switch. This self-tuning behaviour for mixed contact/non-contact scenarios results from a unified formulation of force and motion control, with an integral transpose-based inverse kinematics core and adaptive update laws to cope with the manipulator flexibility and the contact stiffnesses. The global boundedness of all signals and the asymptotic stability of this controller are guaranteed via Lyapunov analysis. Finally, we validate its applicability experimentally by using low-cost hardware in a realistic mixed-contact scenario, demonstrating low computational demand.

This paper presents a novel data-driven controller design methodology for discrete-time switching systems, emphasizing reduced conservativeness. This approach leverages both lifting and virtual clock approaches to achieve this goal. The paper thoroughly examines different application scenarios, including noise-free state measurable, noise-free state unmeasurable, and the consideration of noise. A compromise between conservativeness and applicability is also explored to relax usage restrictions. Importantly, the proposed controller design method is non-conservative in the noise-free case under specific conditions. Simulation results demonstrate that, in the presence of noise, the H_∞ performance of the controllers significantly surpasses that of gain controllers based on traditional methods. Corresponding numerical and practical examples are added to all the methods presented to illustrate their validity.

For compound fault detection of in-wheel motor bearings, this paper proposes a novel approach to adaptively separate multi-source signals and extract compound fault features. Building upon blind source separation (BSS), this approach integrates blind deconvolution to address the challenge of extracting weak features. To resolve the undetermined condition of BSS and enhance feature expression, an adaptive signal reconstruction strategy based on local mean decomposition is proposed. Non-negative matrix factorization, a commonly used BSS method, is refined to suit practical applications by adopting the Itakura-Saito distance and the sparse constraint. Then, fault source signals are adaptively identified based on the proposed envelope spectrum peak factor. By introducing a new waveform extension strategy to effectively reduce the endpoint effect, multipoint optimal minimum entropy deconvolution adjusted is improved and used to enhance and extract weak features. Simulation and experimental results validate the effectiveness and robustness of the proposed approach across various stable working conditions and different types of compound faults.

The reference database or maps is the most important foundation of the gravity matching aided navigation system, which can directly affect the navigation performance of the system and determine the level of matching positioning accuracy. The matching algorithm is usually designed according to the form of database, and its principle is closely related to the structure of database. In this paper, a reference composite features database construction method based on track segmentation (TS-RFD) is proposed. The TS-RFD method mainly can extract texture features from gravity reference data, and determines 8 kinds of features such as index feature and matching feature to establish a reference composite features database. Combined with the search structure of key-value pairs, index feature is used as keys and matching features as values to propose the track segmentation search strategy for matching, and the final positioning result is obtained. Compared to the traditional numerical gravity reference databases or maps which briefly constructed from just gravity anomaly values, with the proposed TS-RFD method various matching features derived from gravity distribution and change are composited to construct a reference composite features database. When the new TS-RFD based database is loaded for gravity matching aided navigation system instead of traditional numerical database, it can significantly enhance efficiency and accuracy, and maintains robust stability. Six subregions in the South China Sea with different gravity distribution and changes were chosen for simulation experiments to verify the performance of proposed database construction. In these six subregions, matching positioning tests along 4200 simulated tracks were carried out. Simulation results show that, with gravity features database constructed from TS-RFD method, both matching accuracy and stability of gravity matching navigation are distinctly improved that obviously superior to the gravity matching with traditional pure numerical database. Moreover, the gravity matching navigation tests were conducted utilizing real measured gravity data in the South China Sea. Measured data test results indicate that after 150 times matching positioning along the track, the average positioning accuracies of matching navigation experiment with traditional numerical database are more than 1.45 nautical miles. In contrast, the average positioning accuracy with TS-RFD database can achieve 1.19 nautical miles, the stability and success rate are still significant advantages.

Tunnels have a crucial role in preventing traffic jams in cities' transportation systems. Therefore, their timely design and construction are fundamental. The past decade has seen the rapid development of Earth Pressure Balance (EPB) machines as the most efficient and safest boring machines in urban areas with the lowest surface subsidence. Nevertheless, despite their numerous benefits, using these machines has disadvantages, such as long-term downtimes and heavy maintenance costs that the projects suffer from. Recently, there has been a surge of interest among researchers in troubleshooting and reducing the downtime of this complex machine. This paper mainly aims to trace and estimate executive elements' impact on machine reliability. To this end, all stops related to 16 subsystems over 12 months were collected and divided into two scenarios, direct (technical) and indirect (technical and executive) factors. According to the results obtained from the preliminary analysis of the raw data: (1) no substantial executive elements were recorded for the navigation subsystem; (2) the trend and serial correlation tests indicated that all Time Between Failures (TBFs) and Time To Repairs (TTRs) from subsystems followed the renewal processes, except for the navigation subsystem's TTR data that followed the non-homogenous poison process (NHPP); (3) the conveyor and segment subsystems were jointly introduced as the most critical subsystem with indirect factors; (4) in contrast, the conveyor subsystem with direct factors was found as the most critical one from the reliability point of view; and (5) the most striking result obtained from the data was that the executive elements could reduce the overall reliability of the EPB machine by about 40 % compared to the contrary scenario.

For the electrohydraulic composite braking system, the general total braking force calculation strategy frequently ignores the resist forces, thereby cannot track the braking intention of driver perfectly. Moreover, the torque allocation process reduces the control reliability and energy recovery effect. In this research, a novel hierarchical braking accurate control (HBAC) algorithm is designed to achieve both the control accuracy and the ideal energy recovery efficiency. It includes target calculation, parameter adjustment, and organization coordination levels. In the target calculation level, the resist forces such as air, tire roll resistances are considered to calculate the demanded-braking force accurately. In the parameter adjustment level, the ideal demand-braking force is constrained by the estimated road adhesion coefficient and the vertical load transfer. At the organization coordination level, the torque allocation process is omitted by applying a compensation control of the hydraulic braking torque. The simulation results indicated outstanding braking distances by the proposed HBAC are 111.5 m, 40.8 m, and 63.2 m under the varying adhesion, dry asphalt, and wet asphalt roads, respectively. Moreover, compared with the comparative control strategy, the energy recovery efficiency of HBAC is increased by 11.74 %, 6.67 %, and 8.4 % under these road conditions. Experimental implementation corroborates the effectiveness of proposed strategy.

The paper addresses the issue of decentralized control with positivity constraint for impulsive interconnected switched positive systems (IISPSs) with mixed time-varying delays coexisting in the state term and the interconnection term under mode-dependent minimum dwell time (MDMDT) switching. Firstly, a positivity criterion of IISPSs is given from the aspect of sufficiency and necessity. Next, through adopting a new discretized linear copositive Lyapunov-Krasovskii functional approach, a sufficient stability criterion of IISPSs under MDMDT constraint is presented. Then, utilizing the method of matrix decomposition, for the mode-dependent controller gains, a valid decentralized controller design scheme in the mode-dependent piece-wise form with formulated linear programming (LP) condition is given for IISPSs under MDMDT constraint. Furthermore, the proposed decentralized control design can degenerate into the one for the case that mixed delay does not lie in IISPSs. At last, three examples are presented to verify the validity of decentralized control design.

This work describes the dissipative constraint-based load frequency control problem for multi-area power system under load disturbances. Particularly, a new model incorporating time-varying delays and cyber-attacks are widespread in communication networks, significantly impacting control and stability. Consequently, the state-space equations of the addressed model are formulated and analyzed under the impact of false data injection attacks, and time-varying delays. The analysis is simplified by representing cyber-attacks using nonlinear functions adhering to Lipschitz continuity, while possible cyber-attacks are characterized by stochastic parameters conforming to Bernoulli distributions. Followed by the above information, stochastic analysis and Lyapunov-Krasovskii stability theory, the convex optimization problem is formulated. As a consequence, the load frequency control gains were effectively constructed, confirming that the established power model is stochastically stable and strictly (Q,S,R)-γ-dissipative. Finally, the case studies are employed to examine the usefulness of the suggested scheme.

Multi-axis contouring control is crucial for ultraprecision manufacturing industries, contributing to meeting the ever-increasingly stringent performance requirements. In this article, a novel contouring adaptive real-time iterative compensation (CARIC) method is proposed to achieve extreme multi-axis contouring accuracy, remarkable trajectory generalization, disturbance rejection, and parametric adaptation simultaneously. Specifically, control actions generated by CARIC consist of robust feedback, adaptive feedforward, and online trajectory compensation components. Robust feedback and adaptive feedforward terms initially stabilize single-axis closed-loop control systems and adapt to parameter variations. An online contouring error prediction model subsequently captures upcoming contouring errors in advance, enabling the iterative calculation of optimal online trajectory compensation signals at each sampling instant during real-time motion. This mechanism proactively suppresses potential contouring errors before their occurrence. Comparative simulations and experiments demonstrate that the proposed CARIC method reaches the accuracy limit previously attainable only by iterative learning control (ILC) while enhancing trajectory generalization, disturbance rejection, and parametric adaptation. Notably, practical experiments on a nano-accuracy air-bearing motion stage showcase consistent 7-nm-level accuracy across various 100-mm stroke contouring tasks even under varying contours, payloads, and disturbances. Owing to these advantages, CARIC offers promising potential to enhance ultraprecision manufacturing performance through advanced motion control techniques.

This paper introduces a fully distributed model-free adaptive control (MFAC) approach for consensus tracking in multi-agent systems (MASs) with compact form data linearization (CFDL). Unlike prior methods that require agents to know the full communication graph, our approach allows each agent to configure its controller using only local information from its neighbors, achieving a fully distributed control. Therefore, our method easily supports scenarios where agents dynamically join or leave MAS. Additionally, our approach does not require a strongly connected communication graph and consensus can be achieved as long as the graph includes a spanning tree with the leader as the root. Simulations demonstrate that this method converges faster to the desired trajectory compared to previous MFAC-based methods.