A pneumatic parallel platform driven by an air cylinder and three circumambient pneumatic muscles was considered. Firstly, a mathematical model of the pneumatic servo system was developed for the MIMO nonlinear model-...A pneumatic parallel platform driven by an air cylinder and three circumambient pneumatic muscles was considered. Firstly, a mathematical model of the pneumatic servo system was developed for the MIMO nonlinear model-based controller designed. The pneumatic muscles were controlled by three proportional position valves, and the air cylinder was controlled by a proportional pressure valve. As the forward kinematics of this structure had no analytical solution, the control strategy should be designed in joint space. A cross-coupling integral adaptive robust controller(CCIARC) which combined cross-coupling control strategy and traditional adaptive robust control(ARC) theory was developed by back-stepping method to accomplish trajectory tracking control of the parallel platform. The cross-coupling part of the controller stabilized the length error in joint space as well as the synchronization error, and the adaptive robust control part attenuated the adverse effects of modelling error and disturbance. The force character of the pneumatic muscles was difficult to model precisely, so the on-line recursive least square estimation(RLSE) method was employed to modify the model compensation. The projector mapping method was used to condition the RLSE algorithm to bound the parameters estimated. An integral feedback part was added to the traditional robust function to reduce the negative influence of the slow time-varying characteristic of pneumatic muscles and enhance the ability of trajectory tracking. The stability of the controller designed was proved through Laypunov's theory. Various contrast controllers were designed to testify the newly designed components of the CCIARC. Extensive experiments were conducted to illustrate the performance of the controller.展开更多
The pneumatic rotary position system, in which an electro-pneumatic proportional flow valve controled a rotary cylinder, was studied, and its mathematical model was built. The model indicated that the controlled pneum...The pneumatic rotary position system, in which an electro-pneumatic proportional flow valve controled a rotary cylinder, was studied, and its mathematical model was built. The model indicated that the controlled pneumatic system had disadvantages such as inherent non-linearity and variations of system parameters with working points. In order to improve the dynamic performance of the system, feed forward compensation self-tuning pole-placement strategy was adopted to place the poles of the system in a desired position in real time, and a recursive least square method with fixed forgetting factors was also used in the parameter estimation. Experimental results show that the steady state error of the pneumatic rotary position system is within 3% and the identified system parameters can be converged in 5 s. Under different loads, the controlled system has an excellent tracking performance and robustness of anti-disturbance.展开更多
递推最小二乘(Recursive Least Squares,RLS)算法因其简单、快速的特点,在微振动自适应控制领域被广泛应用。由于微振动主动控制系统中扰动环境的特殊性及复杂性,需要重点考虑微振动控制中所采用的参数自适应算法在参数估计过程中的鲁...递推最小二乘(Recursive Least Squares,RLS)算法因其简单、快速的特点,在微振动自适应控制领域被广泛应用。由于微振动主动控制系统中扰动环境的特殊性及复杂性,需要重点考虑微振动控制中所采用的参数自适应算法在参数估计过程中的鲁棒性。针对多输入多输出(Multiple Input Multiple Output,MIMO)微振动主动控制系统,基于无限冲激响应(Infinite Impulse Response,IIR)滤波器,提出一种结合死区和归一化的MIMO鲁棒参数自适应算法,并给出其详细的算法推导与收敛性分析。在此基础上,通过构建三自由度微振动主动振动控制实验系统,针对单频窄带扰动、双频窄带扰动展开了对比实验分析,相关的实验结果验证了所提出鲁棒参数自适应算法的可行性和鲁棒性。展开更多
基金Project(51375430)supported by the National Natural Science Foundation of China
文摘A pneumatic parallel platform driven by an air cylinder and three circumambient pneumatic muscles was considered. Firstly, a mathematical model of the pneumatic servo system was developed for the MIMO nonlinear model-based controller designed. The pneumatic muscles were controlled by three proportional position valves, and the air cylinder was controlled by a proportional pressure valve. As the forward kinematics of this structure had no analytical solution, the control strategy should be designed in joint space. A cross-coupling integral adaptive robust controller(CCIARC) which combined cross-coupling control strategy and traditional adaptive robust control(ARC) theory was developed by back-stepping method to accomplish trajectory tracking control of the parallel platform. The cross-coupling part of the controller stabilized the length error in joint space as well as the synchronization error, and the adaptive robust control part attenuated the adverse effects of modelling error and disturbance. The force character of the pneumatic muscles was difficult to model precisely, so the on-line recursive least square estimation(RLSE) method was employed to modify the model compensation. The projector mapping method was used to condition the RLSE algorithm to bound the parameters estimated. An integral feedback part was added to the traditional robust function to reduce the negative influence of the slow time-varying characteristic of pneumatic muscles and enhance the ability of trajectory tracking. The stability of the controller designed was proved through Laypunov's theory. Various contrast controllers were designed to testify the newly designed components of the CCIARC. Extensive experiments were conducted to illustrate the performance of the controller.
基金Project(50375034) supported by the National Natural Science Foundation of China
文摘The pneumatic rotary position system, in which an electro-pneumatic proportional flow valve controled a rotary cylinder, was studied, and its mathematical model was built. The model indicated that the controlled pneumatic system had disadvantages such as inherent non-linearity and variations of system parameters with working points. In order to improve the dynamic performance of the system, feed forward compensation self-tuning pole-placement strategy was adopted to place the poles of the system in a desired position in real time, and a recursive least square method with fixed forgetting factors was also used in the parameter estimation. Experimental results show that the steady state error of the pneumatic rotary position system is within 3% and the identified system parameters can be converged in 5 s. Under different loads, the controlled system has an excellent tracking performance and robustness of anti-disturbance.
