Pressure-based Impedance Control of A Pneumatic Actuator

In this thesis, three control methods are developed for the impedance control of a linear pneumatic actuator for contact tasks using discrete valves. Linear pneumatic actuators, particularly with discrete valves, utilize compressed air to produce linear motion. It is a low cost and clean system with straightforward implementation compared to other actuators. Impedance control is applied to the pneumatic actuator to regulate not only force and position, but also the relationship between them. Specifically, the impedance control yields a desired air pressure based on the actual and desired positions, velocity, and force of a pneumatic cylinder to drive the dynamics of the actuator system. Three controllers including Active Disturbance Rejection Control (ADRC), Sliding Mode Control (SMC), and Extended State Observer (ESO) based SMC are implemented to control the pressure output of the actuator system. The control goal is to drive the actual pressure output to the desired pressure from the impedance control module despite the presence of parameter variations and external disturbances. The performances of these controllers are compared based on their abilities of regulating position, force, and pressure in contact and non-contact situations, as well as the amount of control efforts that excite the valve to achieve these goals. Simulation results demonstrate that ADRC provides the best solution to accomplish the control goals in terms of accurate tracking of position, effectively regulating impedance in the presence of an object, and requiring the least amount of control effort necessary to excite valves

Model Identification And Controller Design For An Electro-Pneumatic Actuator System With Dead Zone Compensation

Pneumatic actuator system is inexpensive, high power to weight ratio, cleanliness and ease of maintenance make it’s a choice compared to hydraulic actuator and electromagnetic actuator. Nonetheless, the steady state error of the system is high due to the dead zone of the valve. In this paper, an Auto-Regressive with External Input (ARX) model structure is chosen to represent the pneumatic actuator system. The recursive least square method is used to estimate the model parameters. The pole-assignment controller is then developed for position tracking. To cater the problem of high in steady state error, the dead zone compensation is added to the system. The dead zone controller was designed based on the inverse dead zone model and the dead zone compensation designed based on the desired error. The proposed method is then experimentally with varies load and compares with Nonlinear PID controller. The result shows that the proposed controller reduced the overshoot and steady state error of the pneumatic actuator system to no overshoot and 0.025mm respectively. Index terms: System identification, recursive least square, ARX, dead zone compensator, pneumatic actuato

Continuous time controller based on SMC and disturbance observer for piezoelectric actuators

Abstract – In this work, analog application for the Sliding Mode Control (SMC) to piezoelectric actuators (PEA) is presented. DSP application of the algorithm suffers from ADC and DAC conversions and mainly faces limitations in sampling time interval. Moreover piezoelectric actuators are known to have very large bandwidth close to the DSP operation frequency. Therefore, with the direct analog application, improvement of the performance and high frequency operation are expected. Design of an appropriate SMC together with a disturbance observer is suggested to have continuous control output and related experimental results for position tracking are presented with comparison of DSP and analog control application

Nonlinear position and stiffness Backstepping controller for a two Degrees of Freedom pneumatic robot

This paper presents an architecture of a 2 Degrees of Freedom pneumatic robot which can be used as a haptic interface. To improve the haptic rendering of this device, a nonlinear position and stiffness controller without force measurement based on a Backstepping synthesis is presented. Thus, the robot can follow a targeted trajectory in Cartesian position with a variable compliant behavior when disturbance forces are applied. An appropriate tuning methodology of the closed-loop stiffness and closed-loop damping of the robot is given to obtain a desired disturbance response. The models, the synthesis and the stability analysis of this controller are described in this paper. Two models are presented in this paper, the first one is an accurate simulation model which describes the mechanical behavior of the robot, the thermodynamics phenomena in the pneumatic actuators, and the servovalves characteristics. The second model is the model used to synthesize the controller. This control model is obtained by simplifying the simulation model to obtain a MIMO strict feedback form. Finally, some simulation and experimental results are given and the controller performances are discussed and compared with a classical linear impedance controller

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions

Design and control of a novel variable stiffness soft arm

Soft robot arms possess such characteristics as light weight, simple structure and good adaptability to the environment, among others. On the other hand, robust control of soft robot arms presents many difficulties. Based on these reasons, this paper presents a novel design and modelling of a fuzzy active disturbance rejection control (FADRC) controller for a soft PAM arm. The soft arm comprises three contractile and one extensor PAMs, which can vary its stiffness independently of its position in space. Force analysis for the soft arm is conducted, and stiffness model of the arm is established based on the relational model of contractile and extensor PAM. The accuracy of stiffness model for the soft arm was verified through experiments. Associated to this, a controller based on the fuzzy adaptive theory and ADRC, FADRC, has been designed to control the arm. The fuzzy adaptive theory is used to adjust the parameters of the ADRC, the control algorithm has the ability to control stiffness and position of the soft arm. In this paper, FADRC was further verified through comparative experiments on the soft arm. This paper reinforces the hypothesis that FADRC control, as an algorithm, indeed possesses good robustness and adaptive abilities. Key words: soft robot, variable stiffness, PAM, stiffness modelling, FADR