Cascaded-Extended-State-Observer-Based Sliding-Mode Control for Underactuated Flexible Joint Robot

Continuous sliding mode disturbance rejection control for flexible joint robots with input saturation.

This paper presents estimation of disturbance to create a compound disturbance observer based on sliding modes. Disturbance observer(DOB) and sliding mode control are both effective methods in motion control. However, DOB is confined to nonlinear disturbance while sliding mode control(SMC) is limited by chattering phenomenon. The proposed method uses sliding mode to compensate the dynamic nonlinear equivalent disturbance and the switching gain of sliding mode, which is designed by disturbance estimation error using fuzzy mapping. The method also helps to decrease chattering with the help of DOB. The validity of the proposals is confirmed by experiments.KeywordsFlight simulatorMotion ControlDisturbance observerSliding modeDisturbance estimate

Due to the advantages of high stiffness, high precision, high load capacity and large workspace, hybrid robots are applicable to drilling and milling of complicated components with large sizes, for instance car panels. However, the difficulty in establishing an exact dynamic model and external disturbances affect the high accuracy control directly, which will decrease the machining accuracy and thereby affect the machining quality and efficiency of the system. Sliding mode control is an effective approach for high-order nonlinear dynamic systems since that it is very insensitive to disturbances and parameter variations. However, chattering may exist in traditional sliding mode control with fixed parameters, which results from a constant approaching speed. Besides, the approaching speed will affect the chattering strength directly. To solve these problems, a modified sliding mode controller with self-adaptive parameters is proposed to enhance the trajectory-tracking performance of a 5-degree-of-freedom hybrid robot. Firstly, the kinematic model of the robot is established. Then adopting the principle of virtual work, a rigid dynamic model of the robot is built. Based on the built dynamic model, a modified sliding mode control method is developed, of which the approaching speed is dependent on the system state. Finally, the sliding mode controller with self-adaptive parameters is created for a hybrid robot. The proposed sliding mode controller can achieve a rapid approaching speed and suppress chattering simultaneously. Simulation results demonstrate that the proposed modified sliding mode controller can achieve a comparatively accurate and smooth trajectory, which owns good robustness to external disturbances.

This paper presents an interconnection and damping assignment passivity based control (IDA-PBC) for the position and impedance control of flexible joint robot. In considering of the joint damping and with some simplification of friction, a flexible joint robot system is descripted as an port-controlled Hamiltonian system with dissipation(PCHD). Then, giving a desired Hamiltonian function which both shapes potential and kinetic energies, the control laws of position control and impedance control is derived by the algebraic IDA-PBC method, which preserves the PCHD structure of the close-loop system. Comparing with the traditional passivity based control (PBC), the proposed method gives a new explanation of the control of flexible joint robot by introducing the self-damping and cross-damping terms, which make the gain selecting procedure more intuitive and comfortable. Simulation and experiments are done to verify the proposed controller, and the results shows a promising performance both in position and impedance control.

EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots

In this paper, a stability control approach of flexible joint robot (FJR) based T-S fuzzy model using fuzzy Lyapunov function is proposed. First, the Takagi and Sugeno (T-S) fuzzy model is employed to approximate the flexible joint robot, then a fuzzy controller is developed based on parallel distributed compensation principle (PDC). The non-quadratic stability conditions for the flexible joint robot control system are proposed by using fuzzy Lyapunov function combined with linear matrix inequality (LMI). Finally, the simulation example is given to illustrate the effectiveness of the proposed method.

A switching control scheme is described for flexible joint robots which does not use link jerk or acceleration feedback. The control scheme does not require the numerical differentiation of the velocity signal or the inversion of the inertial matrices. Simulations are presented to verify the validity of the control scheme and its superiority over existing rigid robot controllers when applied to flexible joint robots. >

An effective method, adaptive fuzzy sliding-mode (SM) PI Control to design full-bridge inverter is proposed in this paper. For practical applications, sliding mode control (SMC) with chattering phenomenon is a large hindrance. The modified model of the PI controller is built by the plant extension scheme, in order to relieve the chattering. Also, the fuzzy logic is applied to find the appropriate parameter values of the PI controller, and can adapt to plant parameter variations and external load disturbances. The proposed method has been realized for the actual full-bridge inverters controlled by DSP and CPLD. Simulation and experimental results of the closed-loop system show that the proposed method yields system performance improvement, such as low total harmonic distortion (THD), fast dynamic response, reduced steady-state error, and reduced chattering.

One of the most important issues with respect to nuclear reactors is power control. In this study, we designed a fractional-order sliding mode controller based on a nonlinear fractional-order model of the reactor system in order to track the reference power trajectory and overcome uncertainties and external disturbances. Since not all of the variables in an operating reactor are measurable or specified in the control law, we propose a reduced-order fractional neutron point kinetic (ROFNPK) model based on measurable variables. In the design, we assume the differences between the approximated model and the real system is limited. We use the obtained model in the controller design process and use the Lyapunov method to perform a stability analysis of the closed-loop system. We simulate the proposed reduced-order fractional-order sliding mode controller (ROFOSMC) using Matlab/Simulink, and its performance is compared with that of a reduced order integer-order sliding mode controller (ROIOSMC). Our simulation results indicate an acceptable performance of the proposed approach in tracking the reference power trajectory with respect to ROIOSMC because of faster response of control effort signal and the smaller tracking error. Moreover, the results illustrate the capability of the controller in rejection of the disturbance and the noise signals and the robustness of controller against uncertainty.

A robust adaptive neural network controller is presented for flexible joint robots using feedback linearization techniques. The controller is based on an approach of using an additional neural network to provide adaptive enhancements to a bask fixed nonlinear controller which can be either neural-network-based or model-used. The weights of the additional neural network are updated on-line based on direct adaptive techniques. It is shown that if Gaussian radial basis function networks are used for the additional neural network, uniformly stable adaptation is assured and asymptotic tracking of the position reference signal is achieved. Intensive computer simulations on a two-link flexible joint robot have shown that the controller can belter handle dynamical model changes and parameter uncertainties than the conventional feedback linearization controller

In this paper, an adaptive chattering free neural network‐based sliding mode control (ACFN‐SMC) method is proposed for tracking trajectories of redundant parallel manipulators. ACFN‐SMC combines adaptive chattering free radial basis function neural networks (RBFN), sliding mode control with online updating the robust term parameters, and a nonlinear compensation item for reducing tracking errors. The stability of the closed‐loop system with modeling uncertainties, frictional uncertainties, and external disturbances is ensured by using the Lyapunov method. The proposed controller has a simple structure and little computation time while securing dynamic performance with expected quality in tracking trajectories of redundant parallel manipulators. In addition, the ACFN‐SMC strategy does not need to know the upper bound of any uncertainties. From the simulation results, it is evident that the proposed control strategy not only has significantly higher robustness capability for uncertainties but also can achieve better chattering elimination when compared with those using existing intelligent control schemes.

Dynamic Movement Primitives (DMPs) are a well-known tool for encoding robotic motions. Their popularity stems from invariance properties in time and space, the ability to describe complex coordinated motions in multiple degrees of freedom with a relatively small number of parameters, and the linearity in the parameters that describe the motion. The latter allows easily fitting a DMP to motions e.g. demonstrated by a human. DMPs are at their core second order autonomous differential equations. However, feedforward controls of robots with flexible joints are known to require reference trajectories up to the fourth derivative of position. Consequently, classical DMPs are mechanically not compatible with flexible joint robots. In this paper, we propose an extension of DMPs by introducing FlexDMPs. This concept retains the structural properties and benefits of classical DMPs but generates trajectories up to the fourth derivative that can theoretically be tracked ideally (i.e. with zero tracking error) by flexible joint robots. The concept is demonstrated on a high fidelity simulation model of an industrial robot and in experimental results on a collaborative manipulator.

Echo-state network based adaptive fuzzy sliding-mode consensus control scheme for nonlinear multi-agent systems with external disturbances.

The work presented here is concerned with the robust control problem for the inverted pendulum with mismatched disturbances via a non-linear disturbance observer (NDO)-based sliding mode control (SMC) method. The NDO-based SMC method provides a solution to the main limitation of conventional first-order sliding mode controllers that is the presence of high frequency oscillations in the control input known as chattering while retaining the nominal performance. To show the effectiveness of NDO-based SMC, both the conventional SMC and the integral SMC (I-SMC) methods are employed in the simulation studies for the purpose of comparison studies and results demonstrate the merits of NDO-based SMC.

Improved Takagi–Sugeno fuzzy model-based control of flexible joint robot via Hybrid-Taguchi genetic algorithm