Explore the vast range of titles available.

PurposeThis paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory tracking and stable operation with heavy load are the main challenges of parallel mechanism for wheel-legged robots, especially in complex road conditions. To guarantee the tracking performance in an uncertain environment, the disturbances, including the internal friction, external environment interaction, should be considered in the practical robot system.Design/methodology/approachIn this paper, a fuzzy approximation-based model predictive tracking scheme (FMPC) for reliable tracking control is developed to the six wheel-legged robot, in which the fuzzy logic approximation is applied to estimate the uncertain physical interaction and external dynamics of the robot system. Meanwhile, the advanced parallel mechanism of the electric six wheel-legged robot (BIT-NAZA) is presented.FindingsCo-simulation and comparative experimental results using the BIT-NAZA robot derived from the developed hybrid control scheme indicate that the methodology can achieve satisfactory tracking performance in terms of accuracy and stability.Originality/valueThis research can provide theoretical and engineering guidance for lateral stability of intelligent robots under unknown disturbances and uncertain nonlinearities and facilitate the control performance of the mobile robots in a practical system.

In order to realize the active and compliant motion of the robot, it is necessary to eliminate the impact caused by processing contact. A hybrid control strategy for grinding and polishing robot is proposed based on adaptive impedance control. Firstly, an electrically driven linear end effector is designed for the robot system. The macro and micro motions control model of the robot is established, by using impedance control method, which based on the contact model of the robot system and the environment. Secondly, the active compliance method is adopted to establish adaptive force control and position tracking control strategies under impact conditions. Finally, the algorithm is verified by Simulink simulation and experiment. The simulation results are as follows: The position tracking error does not exceed 0.009 m, and the steady-state error of the force is less than 1 N. The experimental results show that the motion curve coincides with the surface morphology of the workpiece, and the contact force is stable at 10 ± 3 N. The algorithm can realize more accurate position tracking and force tracking, and provide a reference for the grinding and polishing robot to realize surface processing.

PurposeThis paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.Design/methodology/approachFirst, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.FindingsThe experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.Practical implicationsThe proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.Originality/valueThe adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.

In this work, an effective and practical robot collision detection algorithm is proposed, with the aim of addressing the safety problem of industrial robot force/position hybrid control application conditions. First, a robot force/position hybrid control collision detection scheme was designed, and a collision detection model based on dynamics was established. Then, given the problem of large joint friction force identification error caused by the discontinuous joint speed of the robot force control, the continuous friction model was used to identify and address the joint friction problem through the least square method. Finally, experiments were carried out on a light industrial manipulator. According to the different collision directions of the robots during the experiment, a collision detection method was proposed to monitor the torque changes of the position control joints and the force control joints. Experimental results prove that the continuous friction model is more accurate and effective for joint friction compensation than other methods. The proposed method can achieve effective collision detection with force and position control direction thresholds of 8 and 4 N·m, respectively. The practicability and simplicity of the algorithm that can streamline the process of robot collision detection, the simplified model of the collision detection process only detects the torque change in the position control direction, which has a certain engineering reference value.

Structural engineers face the challenge of mitigating seismic damage in various structural systems. Conventional methods such as massive moment-resisting frames and multiple braced frames, which rely on heavy structural elements, are limited in addressing this challenge. Therefore, novel techniques based on control systems have been proposed to reduce vibrations during earthquakes, and structural engineers are expected to implement such control devices into structures that would intelligently mitigate seismic vibrations through the life of the structure. This study investigated the performance of a hybrid control scheme that combines two passive control systems: base isolation (BI) and mass damper (MD). This scheme was applied to a 50-story tubular building, and its parameters are optimized using metaheuristic algorithms. A new algorithm, called Enhanced Special Relativity Search (ESRS), was developed by incorporating chaos theory into the Special Relativity Search (SRS) algorithm. The ESRS algorithm was adopted to improve the convergence behavior of the SRS algorithm in both exploration and exploitation phases. The results showed that the ESRS algorithm can effectively tune the parameters of the BI and MD systems and enhance the seismic response of the building. The ESRS algorithm outperformed the SRS algorithm in terms of the objective function value and the maximum displacement reduction for all seven earthquake records. The hybrid control scheme with optimal parameters obtained by the ESRS algorithm achieved a 57% displacement reduction for the Duzce earthquake, demonstrating its superior performance compared with existing control schemes. This study proposed a novel hybrid control scheme that combines two passive control systems for better protecting tall buildings against seismic vibrations.

Rotary Inverted Pendulum (RIP) mimics the behavior of many practical control systems like crane mechanism, segway, unicycle robot, traction control in vehicles, rocket stabilization, and launching. RIP is a fourth-order nonlinear open-loop unstable dynamical system and is widely used for testing the effectiveness of the newly developed control algorithms. In this paper, a Hybrid Control Scheme (HCS) based on energy balance and fuzzy logic controllers is proposed to implement the swing up and stabilization control of RIP. In the proposed control scheme, the fuzzy logic-based state feedback gains are dynamically tuned in real-time by minimizing the absolute error between the desired and actual states to get robust control performance. The proposed HCS is also compared with the conventional Linear Quadratic Controller (LQR) for this application. The comparative results show that the proposed fuzzy logic-based hybrid control scheme gives the optimal control performance in terms of achieving satisfactory transient, steady-state, and robust responses from a given RIP system, as compared to the conventional LQR based control scheme. The proposed control scheme is also relatively less complex with a low computational cost and provides desired response characteristics as compared to the existing ones in the literature.

In this paper, a hybrid control system (HCS) endowing a base isolation system (BIS) with a Tuned Mass Damper Inerter (TMDI) is proposed for the protection of steel storage tanks from severe structural damages induced by seismic events. Among all the components of industrial plants, cylindrical steel storage tanks are widely spread and play a primary role when subjected to seismic hazard, since they suffer of many critical issues related to their dynamic response such as high convective wave height and base shear force. The adopted base isolation system is realized with spring and damper elements, whereas the TMDI is realized with a tuned mass damper connected to the ground by the inerter. The developed mechanical model consists of a MDOF system, which considers the impulsive and convective modes as well as the TMDI dynamics. An optimal design problem is tackled, making use of a multi-objective approach, with the scope to mitigate simultaneously the convective and impulsive response of the storage tank. A zero mean white noise excitation is assumed as input in the optimal design procedure. Once the HCS is optimally designed, a systematic investigation of its seismic effectiveness is reached through parametric analysis. Modal parameters and frequency response functions are discussed. A literature case study comparing the effectiveness of the proposed optimally designed HCS with traditional base isolation is illustrated and performances are assessed through stochastic excitation and natural earthquakes.

This paper proposes an original method to suppress the zero-sequence circulating currents (ZSCCs) in two parallel-connected inverters feeding the induction motor (IM), using combining both controllers nonlinear and linear. The synergetic (SYC) controller and the standard PI controller have been combined to form the new hybrid controller. Therefore, the developed controller integrates a SYC controller and a PI controller to operate concurrently, leveraging the frequency separation principle to eliminate the ZSCC components at low, medium and high frequencies, respectively. So, the linear PI controller effectively reduced the low-frequency ZSCC component, while the nonlinear SYC achieved a notable decrease in medium- and high-frequency ZSCC components. The IM drive system, based on indirect field-oriented control with space vector modulation technique, is tested under different operation cases, namely healthy and normal operation as well as imbalance cases, caused by different dead times and switching frequencies. Simulation and experimental studies under different situations were used to validate the effectiveness and practicability of the hybrid controller (PI-synergetic). The proposed PI-synergetic hybrid controller has demonstrated better performances of the zero-sequence circulating currents suppression at the entire frequency range, which validate the feasibility of the proposed PI-synergetic hybrid controller technique for eliminating circulation currents.

This study was conducted based on hybrid damping control theory, and an equivalent damping ratio calculation method was proposed. Additionally, a response calculation method for the elastoplastic stage of the hybrid control system was developed. Furthermore, a cooperative working mechanism between viscous dampers and metal composite dampers was introduced. A time–history analysis was employed to verify the system’s effectiveness in optimizing the multi-dimensional seismic performance of frame structures. Using actual engineering as the research background, an elastoplastic analysis of the hybrid control system was conducted. The analysis results show that the first three natural periods of vibration were shortened by 6.1% (in the X direction), 5.9% (in the Y direction), and 21.0% (torsion), effectively enhancing the overall stiffness of the structure. Under seismic action, the inter-story displacement decreased by 37.1% to 0.166 m in the X direction and by 48.3% to 0.080 m in the Y direction; the base shear forces were reduced by 58.8% (in the X direction) and 41.7% (in the Y direction). Regarding damage control, the number of plastic hinges was significantly reduced, and they appeared only on the most unfavorable floors; the axial compressive stress peaks in the frame columns were strictly controlled below 0.65 fc, and the inter-story displacement angles (<1/50) met the standards of GB50011-2010 for key protection structures. The hybrid system demonstrated multi-dimensional synergistic effects, whereby the viscous dampers primarily controlled the acceleration responses in the X direction, while the metal composite dampers dominated energy dissipation in Y displacement. The difference in seismic reduction efficiency between the two main axes was less than 11%, and a 21% improvement in the torsional period was achieved simultaneously.

This study proposes a force–position hybrid control method for quadruped robots based on the Model Predictive Control (MPC) algorithm, aiming to address the challenges of stability and adaptability in complex terrain environments. Traditional control methods for quadruped robots are often based on simplified models, neglecting the impact of complex terrains and unstructured environments on control performance. To enhance the real-world performance of quadruped robots, this paper employs the MPC algorithm to integrate force and position control to achieve precise force–position hybrid regulation. By transforming foot-end forces into joint torques and optimizing them using kinematic inverse solutions, the robot’s stability and motion accuracy in challenging terrains is further enhanced. In this study, a Kalman filter-based state estimation method is adopted to estimate the robot’s state in real time, enabling closed-loop control through the MPC framework, combined with kinematic inverse solutions for hybrid control. The experimental results demonstrate that the proposed MPC algorithm significantly improves the robot’s adaptability and control accuracy across various terrains. In particular, it exhibits superior performance and robustness in multi-contact and uneven terrain scenarios. This research provides a novel approach for deploying quadruped robots in dynamic and complex environments and offers strong support for further optimization of motion control strategies.