Iterative Learning Control For Linear Motor System In Network Environment

As a new type of distributed and intelligentized control system,network control system has been becoming a hot research topic in the field of international automation control due to the simple structure,sharing information resources,reducing system wiring,increasing the flexibility and reliability and so on.Linear motor is a kind of power transmission device which can directly convert electric energy into mechanical energy of linear motion.It higher conversion efficiency and positioning accuracy compared with rotary motor,so it is widely used in industrial field in recent years.Introduce the network control system to the traditional linear motor control system,give full play to the advantages of network control,develop a novel model of the iterative learning control(ILC)for linear motor system in network environment,it has good development prospect and engineering significance.This paper has selected the linear motor as controlled object,the iterative learning controller as the controller to set up the model of network control and discussed the controller can guarantee the convergence of the system when transfer delay and data packet dropout exist at the same time.The main contents are as following:(1)Considering measurement one-step delay,a P-type ILC algorithm is proposed in the ILC for linear motor system.The one-step delay is described as a stochastic Bernoulli process with a given probability.The probability of the data dropout is unknown but belongs to a known numerical interval.On this basis,we derive the convergence condition for the P-type algorithm by using ? norm theory.The convergence of the algorithm is proved theoretically and the simulation results demonstrate the validity of the proposed design scheme.(2)Considering one-step delay and data dropout at the same time,a P-type ILC algorithm is proposed in the ILC for linear motor system.The one-step delay is described as a stochastic Bernoulli process with a given probability.The probability of the data dropout is unknown but belongs to a known numerical interval.On this basis,we derive the convergence condition for the P-type algorithm by using ? norm theory.The convergence of the algorithm is proved theoretically and the simulation results demonstrate the validity of the proposed design scheme.(3)Considering control delay and measurement dropout at the same time,a PD-type ILC algorithm is proposed in the ILC for linear motor system.The probability of the measurement dropout is unknown but belongs to a known numerical interval.Using the given advanced method to deal with the control delay.The convergence of the algorithm is proved by using Bellman-gronwall inequality and ? norm theory.The simulation results demonstrate the validity of the algorithm.