Adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators

Sliding mode observer-based model predictive tracking control for Mecanum-wheeled mobile robot

This paper proposes a novel adaptive variable power sliding mode observer-based model predictive control (AVPSMO-MPC) method for the trajectory tracking of a Mecanum-wheeled mobile robot (MWMR) with external disturbances and model uncertainties. First, in the absence of disturbances and uncertainties, a model predictive controller that considers various physical constraints is designed based on the nominal dynamics model of the MWMR, which can transform the tracking problem into a constrained quadratic programming (QP) problem to solve the optimal control inputs online. Subsequently, to improve the anti-jamming ability of the MWMR, an AVPSMO is designed as a feedforward compensation controller to suppress the effects of external disturbances and model uncertainties during the actual motion of the MWMR, and the stability of the AVPSMO is proved via Lyapunov theory. The proposed AVPSMO-MPC method can achieve precise tracking control while ensuring that the constraints of MWMR are not violated in the presence of disturbances and uncertainties. Finally, comparative simulation cases are presented to demonstrate the effectiveness and robustness of the proposed method.

Multi-stage trajectory tracking of robot manipulators under stochastic environments

For robot manipulators composed of Lagrange subsystems driven by direct current (DC) motors under stochastic environments, multi-stage trajectory tracking is investigated in this paper. The main challenge is how to achieve the end-effector drive of manipulators from a given initial state to a final state. First, the inverse kinematics method and the partition of the task space are adopted to tackle multi-stage trajectory planning. Second, the adaptive backstepping technique is used to design tracking controller for stochastic Lagrangian subsystems. Then, based on the state-dependent switching signal, a multi-stage switched controller is designed for trajectory tracking of robot manipulators. All signals in the close-loop error switched system are bounded in probability, and the tracking error in mean square can be made arbitrarily small enough by parameters-tuning The effectiveness of the proposed control method is illustrated by simulation results.

Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter

In this paper, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time-varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti-disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme.

Fixed-time terminal sliding mode control for uncertain robot manipulators

This paper proposes a fixed-time tracking control for robot manipulators in the presence of parametric uncertainties and disturbances. An auxiliary function is first proposed for constructing a fixed-time sliding manifold. Benefited from this fixed-time sliding manifold, a singularity-free robust control is proposed to evade the effects of algebraic loop problem of the commonly-used sliding mode controls (SMC). The key advantages of the proposed approach are: (i) exact fixed-time stability featuring the convergence time does not relate to the initial conditions and is acquired in advance; (ii) the singularity and algebraic loop problems are eliminated completely; (iii) a simple and intuitive control structure is used for easy implementation of trajectory tracking control for uncertain robot manipulators with faster transient and higher steady-state precision. Simulations and experimental comparisons validate the improved tracking performance of the proposed approach.

A model-free terminal sliding mode control for robots: Achieving fixed-time prescribed performance and convergence

This paper introduces a new control strategy for robot manipulators, specifically designed to tackle the challenges associated with traditional model-based sliding mode (SM) controller design. These challenges include the need for accurately computed system models, knowledge of disturbance upper bounds, fixed-time convergence, prescribed performance, and the generation of chattering. To overcome these obstacles, we propose the incorporation of a neural network (NN) that effectively addresses these issues by removing the constraint of a precise system model. Additionally, we introduce a novel fixed-time prescribed performance control (PPC) to enhance response performance and position-tracking accuracy, while effectively limiting overshoot and maintaining steady-state error within the predefined range. To expedite the convergence of the SM surface to its equilibrium point, we introduce a faster terminal sliding mode (TSM) surface and a novel fixed-time reaching control algorithm (RCA) with adaptable factors. By integrating these approaches, we develop a novel control strategy that successfully achieves the desired goals for robot manipulators. The effectiveness and stability of the proposed approach are validated through extensive simulations on a 3-DOF SAMSUNG FARA-AT2 robot manipulator, utilizing both Lyapunov criteria and performance evaluations. The results demonstrate improved convergence rate and tracking accuracy, reduced chattering, and enhanced controller robustness.

Adaptive super-twisting control for leader-following consensus of second-order multi-agent systems based on time-varying gains

In this paper, robust distributed consensus control is designed based on adaptive time-varying gains for a class of nonlinear multi-agent systems (MAS) in the presence of uncertain parameters and external disturbances with unknown upper bounds. Due to various conditions and constraints, different dynamical models for the agents can be considered in practice. On the basis of a continuous homogeneous consensus method which has been proposed for the nominal nonlinear MAS, the discontinuous and continuous adaptive integral sliding mode control strategies are particularly designed and extended to accomplish exact and precise consensus for non-identical MASs influenced by imposed perturbations. However, it is noted that in practical problems, the exact upper bound of perturbations is unknown. Then, the proposed controllers have been improved in an adaptive scheme to overcome this drawback. In addition to the adaptive estimation strategy and time-varying gains, which address considered uncertain parameters in the dynamics of the following agents, the designed distributed super-twisting sliding mode strategy for nonlinear agents adjusts the gain of the control inputs and guarantees that the proposed protocol performs properly without any setbacks of the chattering phenomenon. The illustrative simulations depict the robustness, accuracy, and effectiveness of the designed methods.

Disturbance observer-based prescribed performance super-twisting sliding mode control for autonomous surface vessels

This paper proposes a disturbance observer-based prescribed performance super-twisting sliding mode control (DOB PPSTSMC) for trajectory tracking of the autonomous surface vessels (ASVs) subject to unknown external disturbances and modeling errors. Both unknown external disturbances and system modeling errors are approximated by the disturbance observer, thus eliminating most of the effect caused by lumped disturbances in the control performance. Based on this, a prescribed performance super-twisting sliding mode controller is explored to further suppress the residual error of disturbance compensation. Prescribed performance constraints are considered in the coming up with the super-twisting sliding mode controller, so that ASVs not only achieve effective tracking of time-varying desired trajectories, but also improve the transient performance of the control system. In addition, the controller is continuous and chatter-free, which has greater practical value. The excellence of the control project design is highlighted through the simulation and comparison results.

Research on the Line of Sight Stabilization Control Technology of Optronic Mast under High Oceanic Condition and Big Swaying Movement of Platform

To realize high-performance line of sight (LOS) stabilization control of the optronic mast under high oceanic conditions and big swaying movements of platforms, a composite control method based on an adaptive radial basis function neural network (RBFNN) and sliding mode control (SMC) is proposed. The adaptive RBFNN is used to approximate the nonlinear and parameter-varying ideal model of the optronic mast, so as to compensate for the uncertainties of the system and reduce the big-amplitude chattering phenomenon caused by excessive switching gain in SMC. The adaptive RBFNN is constructed and optimized online based on the state error information in the working process; therefore, no prior training data are required. At the same time, a saturation function is used to replace the sign function for the time-varying hydrodynamic disturbance torque and the friction disturbance torque, which further reduce the chattering phenomenon of the system. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed control method is validated by a series of simulations and experiments.

Revised adaptive active disturbance rejection sliding mode control strategy for vertical stability of active hydro-pneumatic suspension

The unmanned ground vehicle (UGV) travels in complex and uncertain terrain. Its vertical stability is a key factor affecting the working state and service life of high-sensitivity on-board sensors and mechanical structures. With the development of unmanned platform, a six-wheel independent drive UGV (6WID UGV) came into being. Its complex operating conditions and the unique configuration of active hydro-pneumatic suspension (AHPS) put forward higher requirements for vertical stability control. Based on the AHPS of 6WID UGV, a revised active disturbance rejection sliding mode controller (R-ADRSMC) is designed to improve the vertical stability of UGV. Firstly, the dynamic model of AHPS was established, and a test platform was built to verify the accuracy of the nonlinear characteristics of stiffness and damping. Secondly, an extended state observer (ESO) is used to estimate the disturbance caused by the model's high nonlinearity and uncertainty. The known disturbance is fed back to ESO to form feedforward compensation, which improves the accuracy of disturbance estimation and compensation. Thirdly, the output of ESO is incorporated into the control law of the sliding mode controller (SMC), giving the control law real-time adaptive capability to the state of suspension system. Finally, the effectiveness of R-ADRSMC and its strong robustness to the uncertainty of road and load parameters are verified by simulation. The results show that compared with passive suspension (PS), active disturbance rejection control (ADRC), and SMC, the proposed R-ADRSMC can effectively improve the vertical stability of UGV under complex road conditions and has better control characteristics.

Predefined performance-based model-free adaptive fractional-order fast terminal sliding-mode control of MIMO nonlinear systems

The purpose of this article is to tackle with the problem of data-driven robust control of multi-input multi-output discrete-time nonlinear plants under tracking error constraints and output perturbations. Thereby, based upon the concept of dynamic linearization, a novel predefined performance based model-free adaptive fractional-order fast terminal sliding-mode controller is proposed so that the tracking errors can converge and remain within a preassigned neighborhood. The presented approach does solely rely on the real-time input/output data of the process, and the transient response together with the steady-state manner of the errors can be arbitrarily predefined. In the meantime, the closed-loop behavior is investigated by mathematical analysis, and the efficiency of the method is validated through various simulation examples.

Dynamic prescribed performance sliding mode control for DC-DC buck converter system with mismatched time-varying disturbances

A generalized proportional integral observer (GPIO) based dynamic prescribed performance sliding mode control (DPPSMC) method for DC-DC buck converter with mismatched time-varying disturbance is proposed to achieve high output voltage tracking performance. Firstly, because extended state observer (ESO) could only estimate the constant interference, considering the mismatched time-varying interference, GPIO is designed to estimate the lumped disturbance so as to enhance the anti-disturbance performance. Then, for the sake of further improve the transient performance, the prescribed performance algorithm is introduced. However, the traditional prescribed performance adopts static performance function. The dynamic system tracking error is likely to exceed the boundaries set by performance functions due to external disturbance and uncertainty, leading to the failure of the algorithm. On account of this, a dynamic prescribed performance function (PPF) is put forward in this paper to keep the tracking error of the converter system always within the predefined error boundary and the algorithm failure problem is avoided. Finally, combined with disturbance estimation technology and dynamic PPF, DPPSMC method is designed to dispose mismatched time-varying interference and improve the transient performance. The Lyapunov stability theorem is applied to certify that the proposed control algorithm could stabilize the closed-loop system. Simulation and experimental result verify the meliority of the designed controller.

Desired compensation adaptive robust repetitive control of a multi-DoFs industrial robot

In the presence of system coupling and dynamic uncertainties, extensive research has been conducted on the precise motion control of industrial manipulators with general reference trajectories. Since repetitive operations are common tasks in industrial applications, it is an essential and practical problem to further improve the control accuracy by taking advantage of the periodicity of the reference trajectory. In this paper, a desired compensation adaptive robust repetitive control is proposed for multi-DoFs industrial manipulators to perform repetitive tasks. Specifically, the link dynamics identified offline is compensated directly to decouple the system and capture the main characteristics of the link effect. Then, the uncertain friction is dealt with through an online adaptation scheme, in which the desired compensation is utilized to avoid measurement noise and chattering at low speed. And periodic disturbances are approximated by Fourier series expansion with unknown Fourier coefficients, which will be learned online. Finally, the robust feedback is designed to guarantee transient control accuracy and robustness against dynamic uncertainties. Comparative experiments on an industrial manipulator show that the proposed controller possesses better transient and steady-state control accuracy and error convergence rate.

Adaptive dynamic feedback control of parallel robots with unknown kinematic and dynamic properties

Uncertainties in dynamic and kinematic parameters are unavoidable components in the control of robotic manipulators. Although calibration is a well-known method to reject this issue, it is time-consuming, some parameters may be altered slowly, and therefore, it is not applicable to some special cases such as deployable cable-driven robots. This paper addresses an adaptive dynamic feedback controller in which the adaptation laws together with new states could remedy these shortcomings and may be appropriately used in deployable cable-driven robots. For this purpose, the Jacobian matrix and its determinant are expressed in regressor form. Additionally, a non-singular sliding surface is considered for the trajectory tracking error. The fast finite-time feasible trajectory tracking is ensured by Lyapunov direct method using an appropriate design of adaptation laws of unknown parameters together with dynamical matrices in the presence of external disturbance. A 4RPR (revolute-prismatic-revolute) redundant rigid body and a fully actuated 3-DOF cable-driven robot are considered to verify the proposed method and also compare the results with state-of-art by simulation and experiment.

Adaptive nonsingular fixed-time sliding mode control for uncertain robotic manipulators under actuator saturation

This paper describes an adaptive nonsingular fixed-time sliding mode control (ANFSMC) scheme under actuator saturation that can track the trajectory of a robotic manipulator under external disturbances and inertia uncertainties. First, a novel NFSMC that offers rapid convergence and avoids singularities is proposed for ensuring robotic manipulators global approximate fixed-time convergence. An ANFSMC is then developed for which the bound of the coupling uncertainty is not necessary to know in advance. The controller exhibits small absolute tracking errors and consumes little energy. An actuator saturation compensator is designed and shown to minimize the chattering of the system while accelerating the trajectory tracking. The proposed schemes are analyzed using Lyapunov stability theory, and their effectiveness and superiority are demonstrated through numerical simulations.

Optimization of Sliding Mode Control to Save Energy in a SCARA Robot

Sliding mode control is a robust technique that is used to overcome difficulties such as parameter variations, unmodeled dynamics, external disturbances, and payload changes in the position-tracking problem regarding robots. However, the selection of the gains in the controller could produce bigger forces than are required to move the robots, which requires spending a large amount of energy. In the literature, several approaches were used to manage these features, but some proposals are complex and require tuning the gains. In this work, a sliding mode controller was designed and optimized in order to save energy in the position-tracking problem of a two-degree-of-freedom SCARA robot. The sliding mode controller gains were optimized usinga Bat algorithm to save energy by minimizing the forces. Finally, two controllers were designed and implemented in the simulation, and as a result, adequate controller gains were found that saved energy by minimizing the forces.

Prescribed Performance Active Braking Control with Reference Adaptation for High-Speed Trains

Active braking control systems are vital for the safety of high-speed trains by leading the train operation at its maximum adhesion state. The train adhesion is a nonlinear function of the slip ratio and varies with the uncertain wheel-rail contact conditions. A nonlinear active braking control with rapid and accurate tracking performance is highly required for train braking systems. This paper proposes a novel prescribed performance active braking control with reference adaptation to obtain the maximum adhesion force. The developed feedback linearization controller employs a prescribed performance function that specifies the convergence rate, steady-state error, and maximum overshoot to ensure the transient and steady-state control performance. Furthermore, in the designed control approach, a continuous-time unscented Kalman filter is introduced to estimate the uncertainty of wheel-rail adhesion. The estimation is utilized to represent uncertainty and compensate for the prescribed performance control law. Finally, based on the estimated wheel-rail adhesion, an on-line optimal slip ratio generation algorithm is proposed for the adaptation of the reference wheel slip. The stability of the system is provided, and experiment results validate the effectiveness of the proposed method.

Prescribed Performance Control with Sliding-Mode Dynamic Surface for a Glue Pump Motor Based on Extended State Observers

The actuator of a particleboard glue-dosing system, the glue pump motor, is affected by external disturbances and unknown uncertainty. In order to achieve accurate glue-flow tracking, in this paper, a glue pump motor compound control method was designed. First, the prescribed performance control method is used to improve the transient behaviors, and the error of the glue flow tracking is guaranteed to converge to a preset range, as a result of the design of an appropriate performance function. Second, two extended state observers were designed to estimate the state vector and the disturbance, in order to improve the robustness of the controlled system. To further strengthen the steady-state performance of the system, the sliding-mode dynamic surface control method was introduced to compensate for uncertainties and disturbances. Finally, a Lyapunov stability analysis was conducted, in order to prove that all of the signals are bounded in a closed-loop system, and the effectiveness and feasibility of the proposed method were verified through numerical simulation.

Research on Kinematics Analysis and Trajectory Planning of Novel EOD Manipulator

To address the problems of mismatch, poor flexibility and low accuracy of ordinary manipulators in the complex special deflagration work process, this paper proposes a new five-degree-of-freedom (5-DOF) folding deflagration manipulator. Firstly, the overall structure of the explosion-expulsion manipulator is introduced. The redundant degrees of freedom are formed by the parallel joint axes of the shoulder joint, elbow joint and wrist pitching joint, which increase the flexibility of the mechanism. Aiming at a complex system with multiple degrees of freedom and strong coupling of the manipulator, the virtual joint is introduced, the corresponding forward kinematics model is established by D–H method, and the inverse kinematics solution of the manipulator is derived by analytical method. In the MATLAB platform, the workspace of the manipulator is analyzed by Monte Carlo pseudo-random number method. The quintic polynomial interpolation method is used to simulate the deflagration task in joint space. Finally, the actual prototype experiment is carried out using the data obtained by simulation. The trajectory planning using the quintic polynomial interpolation method can ensure the smooth movement of the manipulator and high accuracy of operation. Furthermore, the trajectory is basically consistent with the simulation trajectory, which can realize the work requirements of putting the object into the explosion-proof tank. The new 5-DOF folding deflagration manipulator designed in this paper has stable motion and strong robustness, which can be used for deflagration during the COVID-19 epidemic.

Maximum Power Extraction from Wind Turbines Using a Fault-Tolerant Fractional-Order Nonsingular Terminal Sliding Mode Controller

This work presents a nonlinear control approach to maximise the power extraction of wind energy conversion systems (WECSs) operating below their rated wind speeds. Due to nonlinearities associated with the dynamics of WECSs, the stochastic nature of wind, and the inevitable presence of faults in practice, developing reliable fault-tolerant control strategies to guarantee maximum power production of WECSs has always been considered important. A fault-tolerant fractional-order nonsingular terminal sliding mode control (FNTSMC) strategy to maximize the captured power of wind turbines (WT) subjected to actuator faults is developed. A nonsingular terminal sliding surface is proposed to ensure fast finite-time convergence, whereas the incorporation of fractional calculus in the controller enhances the convergence speed of system states and simultaneously suppresses chattering, resulting in extracted power maximisation by precisely tracking the optimum rotor speed. Closed-loop stability is analysed and validated through the Lyapunov stability criterion. Comparative numerical simulation analysis is carried out on a two-mass WT, and superior power production performance of the proposed method over other methods is demonstrated, both in fault-free and faulty situations.

Analysis of exit probability for a trajectory tracking robot in case of a rare event

In this paper, a novel statistical application of large deviation principle (LDP) to the robot trajectory tracking problem is presented. The exit probability of the trajectory from stability zone is evaluated, in the presence of small-amplitude Gaussian and Poisson noise. Afterward, the limit of the partition function for the average tracking error energy is derived by solving a fourth-order system of Euler–Lagrange equations. Stability and computational complexity of the proposed approach is investigated to show the superiority over the Lyapunov method. Finally, the proposed algorithm is validated by Monte Carlo simulations and on the commercially available Omni bundleTM robot.

Output tracking and feedback stabilization for 6-DoF UAV using an enhanced active disturbance rejection control

Purpose

The hybrid control system of the nonlinear PID (NLPID) controller and improved active disturbance rejection control (IADRC) are proposed for stabilization purposes for a 6-degree freedom (DoF) quadrotor system with the existence of exogenous disturbances and system uncertainties.

Design/methodology/approach

IADRC units are designed for the altitude and attitude systems, while NLPID controllers are designed for the x−y position system on the quadrotor nonlinear model. The proposed controlling scheme is implemented using MATLAB/Simulink environment and is compared with the traditional PID controller and NLPID controller.

Findings

Different tests have been done, such as step reference tracking, hovering mode, trajectory tracking, exogenous disturbances and system uncertainties. The simulation results showed the demonstrated performance and stability gained by using the proposed scheme as compared with the other two controllers, even when the system was exposed to different disturbances and uncertainties.

Originality/value

The study proposes an NLPID-IADRC scheme to stabilize the motion of the quadrotor system while tracking a specified trajectory in the presence of exogenous disturbances and parameter uncertainties. The proposed multi-objective Output Performance Index (OPI) was used to obtain the optimum integrated time of the absolute error for each subsystem, UAV quadrotor system energy consumption and for minimizing the chattering phenomenon by adding the integrated time absolute of the control signals.

High Performance Both in Low-Speed Tracking and Large-Angle Swing Scanning Based on Adaptive Nonsingular Fast Terminal Sliding Mode Control for a Three-Axis Universal Inertially Stabilized Platform

In order to improve the performance in the practical engineering applications including so called low-speed video tracking and large-angle swing scanning imaging at the same time for a three-axis universal inertially stabilized platform (UISP), we propose an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) strategy subjected to the uncertain disturbances and input saturation constraints. First of all, a second-order dynamic model is established with uncertain disturbances and input saturation constraints. Secondly, a nonsingular fast terminal sliding mode controller (NTSMC) is constructed to ensure the system error converges to zero fast in a finite time; meanwhile, a novel reaching law based on a modified normal distribution function is designed to adjust the control gain. Thirdly, an adaptive control law is designed to online estimate the parameters of the lumped uncertain disturbances. Additionally, the stability of the control system is proved by Lyapunov theory. Finally, extensive comparative simulations and experiments are carried out, the results comprehensively show the effectiveness and superiority of the proposed control method, which can accelerate convergence, weaken the chattering, and has the better control accuracy and robust performance both in the low-speed tracking and large-angle swing scanning applications. Moreover, the exact dynamic model and the prior knowledge of the upper bounds of the disturbances are not required during the procedure of the controller design, which make it have more extensive application value in practical engineering.

An interval-estimation-based anti-disturbance sliding mode control strategy for rigid satellite with prescribed performance

This paper investigates an anti-disturbance sliding mode control strategy for a rigid satellite system with external disturbance under the prescribed performance constraints. An interval observer is firstly introduced to generate the interval estimation of the attitude angular velocity. Then a finite time identical disturbance reconstruction strategy is developed by using the interval estimation. Based on the novel performance function and error transformation constraints, the attitude tracking error is converted into a new error system that guarantees the desired transient and steady-state responses for the tracking error. Then, by introducing the reconstructed disturbance, a finite time anti-disturbance controller is constructed with the backstepping method. The stability of the strategy is guaranteed by the Lyapunov stability method. Finally, simulation results demonstrate the effectiveness of the proposed approach.

Model-free continuous nonsingular fast terminal sliding mode control for cable-driven manipulators

This work proposes a model-free robust control for cable-driven manipulators with disturbance. To achieve accurate, singularity-free and fast dynamical control performance, we design a new NFTSM surface utilizing a new continuous TSM-type switch element. By replacing the integral power with fractional one for the error dynamics, the designed TSM-type switch element can effectively enhance the dynamical performance of the NFTSM surface. Time-delay estimation (TDE) technique is applied to cancel out complicated nonlinear dynamics guaranteeing an excellent model-free scheme. Thanks to the designed NFTSM surface, adopted reaching law and TDE, our control can provide good comprehensive control performance effectively. Stability and comparisons of control precision and convergence speed have been theoretically analyzed. Finally, comparative experiments were conducted to prove the superiorities of our control.

Robust Finite-Time Tracking Control for Robotic Manipulators with Time Delay Estimation

In this study, a robust H∞ finite-time tracking controller is proposed for robotic manipulators based on time delay estimation. In this controller, there is no need to know the dynamics of robots, so it is quite simple. The high-gain observer is employed to estimate the joint velocities, which makes it much lower in cost. The theorem proof shows that the closed-loop system is finite-time stable and has a L2 gain that is less than or equal to γ, which shows high accuracy and strong robustness to estimation errors and external disturbances. Simulations on a two-link robot illustrate the effectiveness and advantages of the proposed controllers.