Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties

In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity.     

Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input

This article focuses on robust adaptive sliding mode control law for uncertain discrete systems with unknown time-varying delay input, where the uncertainty is assumed unknown. The main results of this paper are divided into three phases. In the first phase, we propose a new sliding surface is derived within the Linear Matrix Inequalities (LMIs). In the second phase, using the new sliding surface, the novel Robust Sliding Mode Control (RSMC) is proposed where the upper bound of uncertainty is supposed known. Finally, the novel approach of Robust Adaptive Sliding ModeControl (RASMC) has been defined for this type of systems, where the upper limit of uncertainty which is assumed unknown. In this new approach, we have estimate the upper limit of uncertainties and we have determined the control law based on a sliding surface that will converge to zero. This novel control laws are been validated in simulation on an uncertain numerical system with good results and comparative study. This efficiency is emphasized through the application of the new controls on the two physical systems which are the process trainer PT326 and hydraulic system two tanks.     

Observer-based sliding mode control with adaptive perturbation estimation for micropositioning actuators

Control of piezoelectric actuators is under the effects of hysteresis that could affect actuators micropositioning accuracy. In this paper a modified Prandtl-Ishlinskii (PI) operator and its inverse is utilized for both identification and real time compensation of the hysteresis effect. As a result, the actuator dynamic model would be transformed to the second order linear dynamic model. Considering the parametric uncertainties, PI estimation error and probably unmodeled dynamics, a variable structure controller coupled with adaptive perturbation estimation is proposed for trajectory tracking of the piezoelectric position. Considering the very noisy output of the actuator, a high-gain observer would estimate full states from the only measurable position trajectory. The stability of the controller in the presence of the estimated state is demonstrated with the Lyapunov criterion. Comparing to the widely used proportional-integral controller, the experimental results depicts that the proposed approach is greatly achieved in precisely tracking of multiple frequency trajectories.     

Robust internal model control of servo motor based on sliding mode control approach

This paper proposes a robust internal model control (IMC) based on sliding mode control (SMC) approach for high-performance motion control of a servo motor subject to uncertainties and/or disturbances. The proposed control strategy considers not only the simplicity and intuition of the IMC-based controller for a prescribed tracking performance but also the effectiveness of the SMC scheme to guarantee the robustness of the servo system. Since the performance of the IMC-based controller can be analyzed via a SMC structure, a robust control law based on the SMC technique is introduced into the IMC scheme to decrease the sensitivity to uncertainties and enhance the resistance to disturbances. Moreover, the 2-degree-of-freedom IMC integrating the robust SMC scheme is developed to further improve the control performance. The stability is analyzed based on Lyapunov theory, and the theoretical results show that a prescribed transient tracking performance and a final tracking accuracy of the servo system can be guaranteed. Comparative simulations and experiments are investigated to verify the high performance nature of the proposed control strategy.     

Stabilization and synchronization for a mechanical system via adaptive sliding mode control

In this paper, we investigate the synchronization problem of chaotic centrifugal flywheel governor with parameters uncertainty and lumped disturbances. A slave centrifugal flywheel governor system is considered as an underactuated following-system which a control input is designed to follow a master centrifugal flywheel governor system. To tackle lumped disturbances and uncertainty parameters, a novel synchronization control law is developed by employing sliding mode control strategy and Nussbaum gain technique. Adaptation updating algorithms are derived in the sense of Lyapunov stability analysis such that the lumped disturbances can be suppressed and the adverse effect caused by uncertainty parameters can be compensated. In addition, the synchronization tracking-errors are proven to converge to a small neighborhood of the origin. Finally, simulation results demonstrate the effectiveness of the proposed control scheme.     

采用滑模观测器的机械臂故障检测与控制优化

针对复合干扰影响下机械臂的故障检测和控制精度问题,提出了一种基于滑模观测器的故障检测和控制优化方法。首先建立了带有电机故障、模型误差和机械摩擦等复合干扰的机械臂系统故障模型,然后设计了滑模观测器来实现在复合干扰下对电机故障的准确检测,最后引入滑模观测器对电机故障程度进行估计,并设计了反步容错控制方法,从而实现了对机械臂系统的精确控制。仿真结果表明,基于滑模观测器的故障检测和控制优化方法能够快速、准确检测和估计电机故障,确保机械臂系统准确跟踪指令信号,角度跟踪误差范围仅为-0.2°～0.2°,能够准确估计出复合干扰的大小,估计误差范围仅为-0.1～0.1 (°)/s²,大大改善了对机械臂的控制效果。     

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.     

Model-based adaptive sliding mode control of the subcritical boiler-turbine system with uncertainties

As higher requirements are proposed for the load regulation and efficiency enhancement, the control performance of boiler-turbine systems has become much more important. In this paper, a novel robust control approach is proposed to improve the coordinated control performance for subcritical boiler-turbine units. To capture the key features of the boiler-turbine system, a nonlinear control-oriented model is established and validated with the history operation data of a 300 MW unit. To achieve system linearization and decoupling, an adaptive feedback linearization strategy is proposed, which could asymptotically eliminate the linearization error caused by the model uncertainties. Based on the linearized boiler-turbine system, a second-order sliding mode controller is designed with the super-twisting algorithm. Moreover, the closed-loop system is proved robustly stable with respect to uncertainties and disturbances. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves excellent tracking performance, strong robustness and chattering reduction.     

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods.     

Neural network adaptive sliding mode control for omnidirectional vehicle with uncertainties

This paper presents a novel neural network adaptive sliding mode control (NNASMC) method to design the dynamic control system for an omnidirectional vehicle. The omnidirectional vehicle is equipped with four Mecanum wheels that are actuated by separate motors, and thus has the omnidirectional mobility and excellent athletic ability in a narrow space. Considering various uncertainties and unknown external disturbances, kinematic and dynamic models of the omnidirectional vehicle are established. The inner-loop controller is designed based the sliding mode control (SMC) method, while the out-loop controller uses the proportion integral derivative (PID) method. In order to achieve the stable and robust performance, the artificial neural network (ANN) based adaptive law is introduced to model and estimated the various uncertainties disturbances. Stability and robustness of the proposed control method are analyzed using the Lyapunov theory. The performance of the proposed NNASMC method is verified and compared with the classical PID controller and SMC controller through both the computer simulation and the platform experiment. Results validate the effectiveness and robustness of the NNASMC method in presence of uncertainties and unknown external disturbances.     

Direct power control of DFIG wind turbine systems based on an intelligent proportional-integral sliding mode control

This paper presents an intelligent proportional-integral sliding mode control (iPISMC) for direct power control of variable speed-constant frequency wind turbine system. This approach deals with optimal power production (in the maximum power point tracking sense) under several disturbance factors such as turbulent wind. This controller is made of two sub-components: (i) an intelligent proportional-integral module for online disturbance compensation and (ii) a sliding mode module for circumventing disturbance estimation errors. This iPISMC method has been tested on FAST/Simulink platform of a 5 MW wind turbine system. The obtained results demonstrate that the proposed iPISMC method outperforms the classical PI and intelligent proportional-integral control (iPI) in terms of both active power and response time.     

An adaptive sliding mode control technology for weld seam tracking

A novel adaptive sliding mode control algorithm is derived to deal with seam tracking control problem of welding robotic manipulator, during the process of large-scale structure component welding. The proposed algorithm does not require the precise dynamic model, and is more practical. Its robustness is verified by the Lyapunov stability theory. The analytical results show that the proposed algorithm enables better high-precision tracking performance with chattering-free than traditional sliding mode control algorithm under various disturbances.     

Robust current control-based generalized predictive control with sliding mode disturbance compensation for PMSM drives

This paper addresses the current control of permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and disturbances. A generalized predictive current control method combined with sliding mode disturbance compensation is proposed to satisfy the requirement of fast response and strong robustness. Firstly, according to the generalized predictive control (GPC) theory based on the continuous time model, a predictive current control method is presented without considering the disturbance, which is convenient to be realized in the digital controller. In fact, it's difficult to derive the exact motor model and parameters in the practical system. Thus, a sliding mode disturbance compensation controller is studied to improve the adaptiveness and robustness of the control system. The designed controller attempts to combine the merits of both predictive control and sliding mode control, meanwhile, the controller parameters are easy to be adjusted. Lastly, the proposed controller is tested on an interior PMSM by simulation and experiment, and the results indicate that it has good performance in both current tracking and disturbance rejection.     

Sliding mode control with fuzzy adaptive perturbation compensator for 6-DOF parallel manipulator

This paper proposes a sliding mode controller with fuzzy adaptive perturbation compensator (FAPC) to get a good control performance and reduce the chatter. The proposed algorithm can reduce the chattering because the proposed fuzzy adaptive perturbation compensator compensates the perturbation terms. The compensator computes the control input for compensating unmodeled dynamic terms and disturbance by using the observer-based fuzzy adaptive network (FAN). The weighting parameters of the compensator are updated by on-line adaptive scheme in order to minimize the estimation error and the estimation velocity error of each actuator. Therefore, the combination of sliding mode control and fuzzy adaptive network gives the robust and intelligent routine to get a good control performance. To evaluate the control performance of the proposed approach, tracking control is experimentally carried out for the hydraulic motion platform which consists of a 6-DOF parallel manipulator.     

Reference slip ratio generation and adaptive sliding mode control for railway rolling stocks

We propose a reference slip ratio generation algorithm that accounts for a large adhesion force to improve the braking performance of railway rolling stocks even if the rail conditions change. Our algorithm is based on fuzzy logic, the efficiency of which was evaluated by comparing the braking distances of rolling stocks using the proposed algorithm and using constant reference slip ratios under various rail conditions. Our proposed slip ratio generation algorithm was used as the basis of an adaptive sliding mode controller for a rolling stocks quarter model. In this design, an adaptive rule was developed using the Lyapunov stability theorem, and the performance of the proposed control system was evaluated by computer simulation.     

Robust passive control for a class of uncertain neutral systems based on sliding mode observer

The passivity-based sliding mode control (SMC) problem for a class of uncertain neutral systems with unmeasured states is investigated. Firstly, a particular non-fragile state observer is designed to generate the estimations of the system states, based upon which a novel integral-type sliding surface function is established for the control process. Secondly, a new sufficient condition for robust asymptotic stability and passivity of the resultant sliding mode dynamics (SMDs) is obtained in terms of linear matrix inequalities (LMIs). Thirdly, the finite-time reachability of the predesigned sliding surface is ensured by resorting to a novel adaptive SMC law. Finally, the validity and superiority of the scheme are justified via several examples.     

A novel adaptive sliding mode control with application to MEMS gyroscope

This paper presents a new adaptive sliding mode controller for MEMS gyroscope; an adaptive tracking controller with a proportional and integral sliding surface is proposed. The adaptive sliding mode control algorithm can estimate the angular velocity and the damping and stiffness coefficients in real time. A proportional and integral sliding surface, instead of a conventional sliding surface is adopted. An adaptive sliding mode controller that incorporates both matched and unmatched uncertainties and disturbances is derived and the stability of the closed-loop system is established. The numerical simulation is presented to verify the effectiveness of the proposed control scheme. It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as the consistent estimation of gyroscope parameters including angular velocity and large robustness to parameter variations and external disturbances.     

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach.     

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods.