Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller
High-accuracy motion trajectory tracking control of a pneumatic cylinder driven by a proportional directional control valve was considered. A mathematical model of the system was developed firstly. Due to the time-varying friction force in the cylinder, unmodeled dynamics, and unknown disturbances, there exist large extent of parametric uncertainties and rather severe uncertain nonlinearities in the pneumatic system. To deal with these uncertainties effectively, an adaptive robust controller was constructed in this work. The proposed controller employs on-line recursive least squares estimation(RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodeled dynamics and disturbances. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology was applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping was used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Extensive experimental results were presented to illustrate the excellent achievable performance of the proposed controller and performance robustness to the load variation and sudden disturbance.
The system considered in this work consists of a cylinder which is controlled by a pair of three-way servo valves rather than a four-way one.Therefore,the cylinder output stiffness is independently controllable of the output force.A discontinuous projection based adaptive robust controller (ARC) was constructed to achieve high-accuracy output force trajectory tracking for the system.In ARC,on-line parameter adaptation method was adopted to reduce the extent of parametric uncertainties due to the variation of friction parameters,and sliding mode control method was utilized to attenuate the effects of parameter estimation errors,unmodelled dynamics and disturbance.Furthermore,output stiffness maximization/minimization was introduced to fulfill the requirement of many robotic applications.Extensive experimental results were presented to illustrate the effectiveness and the achievable performance of the proposed scheme.For tracking a 0.5 Hz sinusoidal trajectory,maximum tracking error is 4.1 N and average tracking error is 2.2 N.Meanwhile,the output stiffness can be made and maintained near its maximum/minimum.
