Unknown Friction Parameters Research Articles

Adaptive Optimal Control of UAV Brake Based on Parameter Estimation

A new parameter estimation method for a UAV braking system with unknown friction parameters is suggested. The unknown part containing friction is separated from the coupling system. The law of parameter updating is driven by the estimation error extracted by the auxiliary filter. A controller is developed to guarantee the convergence of the parameter estimation and tracking errors simultaneously. Furthermore, a designed performance index function enables the system to track the desired slip rate optimally. The optimal value of the performance function is updated by a single critic neural network (NN) to obtain comprehensive optimization of the control energy consumption, dynamic tracking error, and filtering error during braking. In addition, the unknown bounded interference and neural network approximation errors are compensated by robust integral terms. Simulation results are presented to confirm the effectiveness of the proposed control scheme.

A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds.

High precision demands in a large number of emerging robotic applications strengthened the role of the modern control laws in the position control of the Permanent Magnet Synchronous Motor (PMSM) servo system. This paper proposes a learning-based adaptive control approach to improve the PMSM position tracking in the presence of the friction uncertainty. In contrast to most of the reported works considering the servos operating at high speeds, this paper focuses on low speeds in which the friction stemmed deteriorations become more obvious. In this paper firstly, a servo model involving the Stribeck friction dynamics is formulated, and the unknown friction parameters are identified by a genetic algorithm from the offline data. Then, a feedforward controller is designed to inject the friction information into the loop and eliminate it before causing performance degradations. Since the friction is a kind of disturbance and leads to uncertainties having time-varying characters, an Adaptive Proportional Derivative (APD) type Iterative Learning Controller (ILC) named as the APD-ILC is designed to mitigate the friction effects. Finally, the proposed control approach is simulated in MATLAB/Simulink environment and it is compared with the conventional Proportional Integral Derivative (PID) controller, Proportional ILC (P-ILC), and Proportional Derivative ILC (PD-ILC) algorithms. The results confirm that the proposed APD-ILC significantly lessens the effects of the friction and thus noticeably improves the control performance in the low speeds of the PMSM.

An adaptive speed observer for a class of nonlinear mechanical systems: Theory and experiments

We propose a solution to the problem of adaptive speed observer for a class of mechanical systems containing cross terms in the velocity (momenta). We focused our attention on mechanical systems with unknown constant input disturbances and Coulomb friction matrix, which generate products of unmeasurable velocities and unknown friction parameters. The adaptive speed observer proposed is based on the well-known Immersion and Invariance technique. We ensure global convergence of the speed observer, while the friction parameters estimation remain bounded. Our approach is validated through simulations and experimental results.

An Experimental Method for Estimating Combined Friction Torque in Vane Type Pneumatic Semi Rotary Actuators

In this paper, an experimental method is proposed for estimation of friction torque in vane type pneumatic semi rotary actuators. The friction is modelled in the form of fully combined Stribeck model since this combined friction model provides good solutions for precise control applications. The study aims estimating static friction torque, Coulomb friction torque, Stribeck speed and viscous friction&damping coefficient which is included in fully combined Stribeck model for both counterclockwise and clockwise directions of the rotary actuator since these unknown parameters show differences when direction of motion is altered. For that purpose, an experimental setup is designed which includes pressure sensors for measuring the chamber pressures of actuator, analogue potentiometer for reading angular position as well as speed of vane and Arduino microcontroller card for data acquisition. A proper MATLAB Simulink block diagram is prepared for the simultaneous estimation of processed data from experimental data. Nonlinear curve fitting operation is applied and the unknown friction parameters are estimated on the fitted curve easily.

Development of a Test Apparatus for Estimation of Friction Parameters at Linear Pneumatic Cylinders

Pneumatic cylinders possess non-linear characteristics due to the air-compressibility and stick-slip in cylinder barrel. Friction characteristics in pneumatic cylinders is one of the main non-linearity that negatively affects the precise control. To be able to use these actuator systems in high level control applications, their friction force models should be developed. Hence, unknown friction parameters should be estimated correctly since the friction parameters of pneumatic cylinders are not listed in the manufacturers’ catalogue and these parameters cannot be calculated by only analytical methods. For that reason, in this study, a test apparatus is designed and experimental procedures are developed for the estimation of the friction parameters of linear pneumatic cylinders as in the form of static friction force, Coulomb friction force, Stribeck velocity and viscous damping coefficient. 

An adaptive speed observers’ design for a class of nonlinear mechanical systems

An adaptive speed observer for mechanical systems, which are linear in the velocity (momenta) after a change of coordinates (Venkatraman et al. [2010]), was recently reported in the literature (Romero and Ortega [2015]). The velocity observer considers input disturbances and some unknown friction parameters in the design. In this note, we relax some assumptions imposed in that work so that, the class of systems is enlarged and quadratic terms in the velocity(momenta) and all the friction parameters are included in the design of the velocity observer. Simulation results using the robotic–leg system illustrate the performance of the proposed adaptive observer.

Sliding Mode Robot Control with Friction and Payload Estimation

The paper deals with robust motion control of robotic systems with unknown friction parameters and payload mass. The parameters of the robot arm were considered known with a given precision. To solve the control of the robot with unknown payload mass and friction parameters, sliding mode control algorithm was proposed combined with robust parameter adaptation techniques. Using Lyapunov method it was shown that the resulting controller achieves a guaranteed final tracking accuracy. Simulation results are presented to illustrate the effectiveness and achievable control performance of the proposed scheme.

A design method of adaptive H∞ control for servo system with friction compensation: using dead-zone modification strategy

This paper considers a tracking control of a servo mechanism with friction. It is assumed that the static and dynamic characteristics of friction are captured by the dynamic LuGre model. Based on notion of H∞ optimality, an adaptive friction compensation strategy is proposed. Neural-Network (NN) is used to parameterize the nonlinear characteristic function of the friction model. In this proposed method, unknown friction parameters and NN weight vector are updated by estimating strategy. Moreover, an approximation error in NN is regarded as an exogenous disturbance to the system, the L2 gains from the disturbance to generalized outputs are made less than prescribed positive constants. To cope with the practical applications, dead-zone modification method is also applied to the unknown parameter estimating strategies. Experimental results are shown to illustrate the effectiveness of our proposed method.

Determination of workpiece flow stress and friction at the chip–tool contact for high-speed cutting

This paper presents a methodology to determine simultaneously (a) the flow stress at high deformation rates and temperatures that are encountered in the cutting zone, and (b) the friction at the chip–tool interface. This information is necessary to simulate high-speed machining using FEM based programs. A flow stress model based on process dependent parameters such as strain, strain-rate and temperature was used together with a friction model based on shear flow stress of the workpiece at the chip–tool interface. High-speed cutting experiments and process simulations were utilized to determine the unknown parameters in flow stress and friction models. This technique was applied to obtain flow stress for P20 mold steel at hardness of 30 HRC and friction data when using uncoated carbide tooling at high-speed cutting conditions. The average strain, strain-rates and temperatures were computed both in primary (shear plane) and secondary (chip–tool contact) deformation zones. The friction conditions in sticking and sliding regions at the chip–tool interface are estimated using Zorev's stress distribution model. The shear flow stress ( k chip) was also determined using computed average strain, strain-rate, and temperatures in secondary deformation zone, while the friction coefficient ( μ) was estimated by minimizing the difference between predicted and measured thrust forces. By matching the measured values of the cutting forces with the predicted results from FEM simulations, an expression for workpiece flow stress and the unknown friction parameters at the chip–tool contact were determined.