Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment.

This study develops an adaptive sliding mode control approach for a drilling tool attitude adjustment system, aiming at solving the problems of model uncertainties and insufficient ability of disturbance suppression during the regulation behavior. To further improve the performance of the position-tracking loop in terms of response time, tracking accuracy, and robustness, a state observer based on an improved radial basis function is designed to approximate the model uncertainties, a valve dead-zone compensate controller is used to reduce control deviation, an adaptive sliding mode controller is designed to improve the position-tracking precision and attenuate sliding mode chattering. Finally, simulation and experimental results are carried out to verify the observability of the model uncertainties and position-tracking errors of the drilling tool attitude adjustment system, which can effectively improve the position-tracking performance and robustness of the drilling tool attitude adjustment system.

Adaptive Second-Order Fixed-Time Sliding Mode Controller with a Disturbance Observer for Electronic Throttle Valves.

In order to enhance the precision and speed of control for electronic throttle valves (ETVs) in the face of disturbance and parameter uncertainties, an adaptive second-order fixed-time sliding mode (ASOFxTSM) controller is developed, along with disturbance observer compensation techniques. Initially, a control-oriented model specifically considering lumped disturbances within the ETV is established. Secondly, to address the contradiction between fast response and heavy chattering of conventional fixed-time sliding mode, a hierarchical sliding surface approach is introduced. This approach proficiently alleviates chattering effects while preserving the fixed convergence properties of the controller. Furthermore, to enhance the anti-disturbance performance of the ETV control system, an innovative fixed-time sliding mode observer is incorporated to estimate lumped disturbances and apply them as a feed-forward compensation term to the ASOFxTSM controller output. Building upon this, a parameter adaptive mechanism is introduced to optimize control gains. Subsequently, a rigorous stability proof is conducted, accompanied by the derivation of the expression for system convergence time. Finally, a comparison is drawn between the proposed controller and fixed-time sliding mode and super-twisting controllers through simulations and experiments. The results demonstrate the superiority of the proposed method in terms of chattering suppression, rapid dynamic response, and disturbance rejection capability.

Production Change Optimization Model of Nonlinear Supply Chain System under Emergencies.

Aiming at the problem that the upstream manufacturer cannot accurately formulate the production plan after the link of the nonlinear supply chain system changes under emergencies, an optimization model of production change in a nonlinear supply chain system under emergencies is designed. Firstly, based on the structural characteristics of the supply chain system and the logical relationship between production, sales, and storage parameters, a three-level single-chain nonlinear supply chain dynamic system model containing producers, sellers, and retailers was established based on the introduction of nonlinear parameters. Secondly, the radial basis function (RBF) neural network and improved fast variable power convergence law were introduced to improve the traditional sliding mode control, and the improved adaptive sliding mode control is proposed so that it can have a good control effect on the unknown nonlinear supply chain system. Finally, based on the numerical assumptions, the constructed optimization model was parameterized and simulated for comparison experiments. The simulation results show that the optimized model can reduce the adjustment time by 37.50% and inventory fluctuation by 42.97%, respectively, compared with the traditional sliding mode control, while helping the supply chain system to return the smooth operation after the change within 5 days.

Integrated Controller Design and Application for CNC Machine Tool Servo Systems Based on Model Reference Adaptive Control and Adaptive Sliding Mode Control.

In order to reduce the effect of nonlinear friction and time-varying factors on the servo system of a computer numerical control (CNC) machine tool and improve its motion control accuracy, this paper uses an adaptive sliding mode control (ASMC) method based on model reference adaptive control (MRAC). The method adopts ASMC in the control outer loop and obtains the optimal control parameters by making the sliding mode control (SMC) law continuous and adaptively estimating the control parameters. At the same time, MRAC is used in the control inner loop to enhance the "invariance" of the controlled object so that the switching gain of SMC can satisfy the disturbance matching condition even under lesser conditions. Simulation and experimental results show that compared with the traditional SMC, the ASMC based on MRAC proposed in this paper effectively reduces the influence of nonlinear friction on the system performance, and the reduction in following error reaches 71.2%, which significantly improves the motion control accuracy of the control system. The spectral analysis of the following errors shows that the maximum magnitude reduction rate of the high-frequency chattering is 89.02%, which significantly reduces the effect of the high-frequency chattering and effectively improves the stability performance of the control system.

An Adaptive Sliding-Mode Iterative Constant-force Control Method for Robotic Belt Grinding Based on a One-Dimensional Force Sensor.

To improve the processing quality and efficiency of robotic belt grinding, an adaptive sliding-mode iterative constant-force control method for a 6-DOF robotic belt grinding platform is proposed based on a one-dimension force sensor. In the investigation, first, the relationship between the normal and the tangential forces of the grinding contact force is revealed, and a simplified grinding force mapping relationship is presented for the application to one-dimension force sensors. Next, the relationship between the deformation and the grinding depth during the grinding is discussed, and a deformation-based dynamic model describing robotic belt grinding is established. Then, aiming at an application scene of robot belt grinding, an adaptive iterative learning method is put forward, which is combined with sliding mode control to overcome the uncertainty of the grinding force and improve the stability of the control system. Finally, some experiments were carried out and the results show that, after ten times iterations, the grinding force fluctuation becomes less than 2N, the mean value, standard deviation and variance of the grinding force error's absolute value all significantly decrease, and that the surface quality of the machined parts significantly improves. All these demonstrate that the proposed force control method is effective and that the proposed algorithm is fast in convergence and strong in adaptability.

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions.

Model-free adaptive task-space sliding mode control of a Delta robot using a novel reaching law.

This paper presents a model-free adaptive sliding mode control for the Delta robot with a novel reaching law for achieving a less conservative sign-function gain and protecting the Delta robot against overloads. A desired closed-loop system with asymptotic stability based on the Lyapunov theorem is proposed to derive the control law. The proposed control system can overcome uncertainties without prior knowledge of the bounding functions. The reaching time is adjusted adaptively to achieve a smooth convergence to the sliding surface, resulting in chattering attenuation. The gradient descent algorithm is utilized for the first time with a novel adaptation rule to estimate the Delta robot inverse Jacobian matrix. Instead of employing a numerical dynamic model, an analytical model is used for the proposed control law, stability analysis, and simulations. A simple, straightforward inverse-kinematics solution based on a geometrical approach is presented. Simulation results demonstrate a superior performance of the proposed reaching law through comparisons.

Modeling and motion control of helical microrobots using the dual quaternion framework and adaptive sliding mode strategy.

This study investigates the tracking control problem of helical microrobots (HMRs) in complicated blood environments. The integrated relative motion model of HMRs is established by resorting to the dual quaternion method, which can describe the coupling effect between the rotational and translational motions. Subsequently, an original apparent weight compensator (AWC) is designed to alleviate the adverse effects of the HMR sinking and drifting owing to its own weight and buoyancy. An adaptive sliding mode control based on the developed AWC (AWC-ASMC) is constructed to guarantee the fast convergence of the relative motion tracking errors in the presence of model uncertainties and unknown perturbations. The chattering phenomenon of the classical SMC is significantly reduced using the developed control strategy. Furthermore, the stability of the closed-loop system under the constructed control framework is demonstrated by the Lyapunov theory. Finally, numerical simulations are performed to demonstrate the validity and superiority of the developed control scheme.

Autonomous motion and control of lower limb exoskeleton rehabilitation robot.

Introduction: The lower limb exoskeleton rehabilitation robot should perform gait planning based on the patient's motor intention and training status and provide multimodal and robust control schemes in the control strategy to enhance patient participation. Methods: This paper proposes an adaptive particle swarm optimization admittance control algorithm (APSOAC), which adaptively optimizes the weights and learning factors of the PSO algorithm to avoid the problem of particle swarm falling into local optimal points. The proposed improved adaptive particle swarm algorithm adjusts the stiffness and damping parameters of the admittance control online to reduce the interaction force between the patient and the robot and adaptively plans the patient's desired gait profile. In addition, this study proposes a dual RBF neural network adaptive sliding mode controller (DRNNASMC) to track the gait profile, compensate for frictional forces and external perturbations generated in the human-robot interaction using the RBF network, calculate the required moments for each joint motor based on the lower limb exoskeleton dynamics model, and perform stability analysis based on the Lyapunov theory. Results and discussion: Finally, the efficiency of the APSOAC and DRNNASMC algorithms is demonstrated by active and passive walking experiments with three healthy subjects, respectively.

Finite-time adaptive sliding mode control for high-precision tracking of piezo-actuated stages.

Piezo-actuated stages are widely used in nanopositioning applications. However, they not only have inherent static hysteresis characteristics but also have dynamic rate-dependent hysteresis nonlinearity. Therefore, to address dynamic hysteresis nonlinearity and uncertainty in the model parameters, an adaptive switching-gain sliding mode controller with a proportional-integral-derivative surface is designed. In particular, the combination of Bouc-Wen model and second-order linear system is used to describe the dynamic hysteresis process. To improve the robustness and reduce chattering in the sliding mode control method, an adaptive switching-gain is added to the controller without knowing in advance the upper bound of uncertainties. Finite-time convergence conditions of the closed-loop system are also analyzed. Finally, the proposed control method is implemented in real time on an ARM experimental platform. Comparative experimental results demonstrate excellent tracking performance and robustness. The dynamic hysteresis characteristics are suppressed effectively, and this result provides a powerful reference for engineering applications.

Adaptive synchronization of chaotic systems with hysteresis quantizer input.

This paper proposes two new designing methods of adaptive controllers in order to synchronize uncertain nonlinear chaotic systems with input quantization. The hysteresis quantizer, which is a class of sector-bounded quantizers, has been used to quantize the control signal. This can avoid the possible chattering caused by some conventional controllers. Two adaptive robust schemes are proposed to accomplish chaos synchronization of master and slave systems in presence of unknown parameters and uncertainties. The proposed controllers in this paper do not require the restrictive conditions for quantized parameters in contrast to some available control techniques for systems with input quantization. In addition, asymptotic stability of the proposed adaptive controllers is also verified analytically. Finally, the proposed controller is applied to a chaotic gyroscope and also to a Micro-Electro-Mechanical-System to validate its efficiency and robustness.

Adaptive sliding mode current control with sliding mode disturbance observer for PMSM drives.

This paper focuses on the current control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. To improve the performance of the PMSM current loop in terms of the speed of response, tracking accuracy, and robustness, a hybrid control strategy is proposed by combining the adaptive sliding mode control and sliding mode disturbance observer (SMDO). An adaptive law is introduced in the sliding mode current controller to improve the dynamic response speed of the current loop and robustness of the PMSM drive system to the existing parameter variations. The SMDO is used as a compensator to restrain the external disturbances and reduce the sliding mode control gains. Experiments results demonstrate that the proposed control strategy can guarantee strong anti-disturbance capability of the PMSM drive system with improved current and speed-tracking performance.

A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results.

Mean deviation coupling synchronous control for multiple motors via second-order adaptive sliding mode control.

A new mean deviation coupling synchronization control strategy is developed for multiple motor control systems, which can guarantee the synchronization performance of multiple motor control systems and reduce complexity of the control structure with the increasing number of motors. The mean deviation coupling synchronization control architecture combining second-order adaptive sliding mode control (SOASMC) approach is proposed, which can improve synchronization control precision of multiple motor control systems and make speed tracking errors, mean speed errors of each motor and speed synchronization errors converge to zero rapidly. The proposed control scheme is robustness to parameter variations and random external disturbances and can alleviate the chattering phenomena. Moreover, an adaptive law is employed to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. Performance comparisons with master-slave control, relative coupling control, ring coupling control, conventional PI control and SMC are investigated on a four-motor synchronization control system. Extensive comparative results are given to shown the good performance of the proposed control scheme.

Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.

Speed tracking and synchronization of multiple motors using ring coupling control and adaptive sliding mode control.

A new control approach for speed tracking and synchronization of multiple motors is developed, by incorporating an adaptive sliding mode control (ASMC) technique into a ring coupling synchronization control structure. This control approach can stabilize speed tracking of each motor and synchronize its motion with other motors' motion so that speed tracking errors and synchronization errors converge to zero. Moreover, an adaptive law is exploited to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort and attenuate chattering. Performance comparisons with parallel control, relative coupling control and conventional PI control are investigated on a four-motor synchronization control system. Extensive simulation results show the effectiveness of the proposed control scheme.

Controller design and experiment for autothermal reforming of methanol in miniature reactor.

In this paper, a miniature methanol fuel processor and its controller design is introduced for onboard hydrogen production. The hydrogen is generated via autothermal reforming of methanol. The control scheme consists of a hydrogen flow rate controller and a reforming temperature controller. To deal with uncertain system dynamics and external disturbance, an adaptive sliding mode control algorithm is adopted as the hydrogen flow rate controller for regulating hydrogen flow rate by manipulating methanol flow rate. Additionally, a high-gain observer is implemented to estimate the unmeasurable system state. The stability of closed-loop system is guaranteed by standard Lyapunov analysis. Furthermore, a variable ratio control law is employed as the reforming temperature controller to achieve steady reforming temperature by adjusting the reforming air flow rate. Finally, the effectiveness of the entire system is testified by experimental means.