Piotr Serkies

Application of the MPC to the Position Control of the Two-Mass Drive System

In this paper, a model predictive controller for the position control of an electrical drive with an elastic connection is presented. The control methodology enables the drives safety and physical limitations to be directly incorporated into control synthesis. The effect of the predictive horizon on the drive performance is examined. Also, the influence of parameter changes is tested in this paper. The simulation study is supported by experimental results.

Application of the MPC to the robust control of the two-mass drive system

In this paper, a model predictive controller (MPC) for the speed control for an electrical drive with elastic connection is presented. The control methodology enables the drives safety and physical limitations to be directly incorporated into control synthesis. The methodology for robust design based on the suitable selection of the system matrices of the MPC is presented. The simulation results show that the controller is very effective in regulating load speed for a wide-range of the changes of the load side inertia. Preliminary experimental results confirm the simulation study.

Model predictive speed and vibration control of dual-inertia PMSM Drives

In this paper, the application of model predictive control for speed and vibration control of dual-mass electrical drive systems with permanent magnet synchronous motors (PMSM) is presented. The control methodology proposed here relies on incorporating the drives safety and physical limitations directly into the control problem formulation so that future constraint violations are anticipated and prevented. In order to reduce the computational complexity, the MPC controller is pre-computed off-line in an explicit form represented by a piecewise affine state-feedback law thus requiring only a fraction of the real-time computational power. The proposed explicit MPC controller is evaluated through simulations demonstrating feasibility and high effectiveness.

Robust torque constraints handling in drive systems with elastic transmission

This paper investigates the effectiveness of Model Predictive Control (MPC) in dealing with torsional vibrations and torque constraints in a two-mass elastic drive system under plant uncertainty and parameter variation. The methodology for designing low complexity MPC controllers for speed regulation and vibration suppression is discussed and validated on a real two-mass drive system. Selected experimental results confirm that the proposed MPC speed controller is very effective in dealing with tight torque constraints requirements under significant plant parameter uncertainty.

Position tracking in electrical drives with elastic coupling using model predictive control

This paper presents a design methodology for optimal position control in electrical drives with mechanical elasticity subject to safety and physical constraints on torque and speed variables. The control problem is formulated within the framework of model predictive control (MPC) which ensures that the drives operational limitations are directly accounted for in the control problem formulation so that any potential constraint violations are anticipated and prevented. An efficient closed-form solution of the MPC problem is also developed which enables the reduction of the real-time computational complexity to a simple look-up table search. Experimental results carried out on a pilot-scale dual-mass drive demonstrate that the proposed controller is very effective in tracking arbitrary position references while meeting the demanding drive constraints requirements during operation.

Robust Control of the Two-mass Drive System Using Model Predictive Control

A demand for the miniaturization and reducing the total moment of inertia which allows to shorten the response time of the whole system is evident in modern drives system. However, reducing the size of the mechanical elements may result in disclosure of the finite stiffness of the drive shaft, which can lead to the occurrence of torsional vibrations. This problem is common in rolling-mill drives, belt-conveyors, paper machines, robotic-arm drives including space manipulators, servo-drives and throttle systems (Itoh et al., 2004, Hace et al., 2005 , Ferretti et al. 2005, Sugiura & Hori, Y., 1996, Szabat & Orlowska-Kowalska, 2007, O’Sullivan at al. 2007, Ryvkin et al., 2003 , Wang & Frayman, 2004, Vasak & Peric, 2009, Vukosovic & Stojic, 1998). To improve performances of the classical control structure with the PI controller, the additional feedback loop from one selected mechanical state variable can be used. The additional feedback allows setting the desired value of the damping coefficient, but the free value of the resonant frequency cannot be achieved simultaneously (Szabat & OrlowskaKowalska, 2007). According to the literature, the application of the additional feedback from the shaft torque is very common (Szabat & Orlowska-Kowalska, 2007). The design methodology of that system can be divided into two groups. In the first framework the shaft torque is treated as the disturbance. The simplest approach relies on feeding back the estimated shaft torque to the control structure, with the gain less than one. The more advanced methodology, called Resonance Ratio Control (RRC) is presented in (Hori et al., 1999). The system is said to have good damping ability when the ratio of the resonant to antiresonant frequency has a relatively big value (about 2). The second framework consists in the application of the modal theory. Parameters of the control structure are calculated by comparison of the characteristic equation of the whole system to the desired polynomial. To obtain a free design of the control structure parameters, i.e. the resonant frequency and the damping coefficient, the application of two feedbacks from different groups of mechanical state variables is necessary. The design methodology of this type of the systems is presented in (Szabat & Orlowska-Kowalska, 2007). The control structures presented so far are based on the classical cascade compensation schemes. Since the early 1960s a completely different approach to the analysis of the system dynamics has been developed – the state space methodology (Michels et al., 2006). The application of the state-space controller allows to place the system poles in an arbitrary position so theoretically it is possible to obtain any dynamic response of the system. The

Predictive position control of the induction two-mass system drive

In the paper, a model predictive controller (MPC) for the position control for an induction motor drive with an elastic connection is presented. The control methodology enables the drives safety and physical limitations to be directly incorporated into control synthesis. The effect of the predictive horizon on the drive performance is examined. The theoretical consideration are supported by experimental results.

Estimation of the state variables of the two-mass system using fuzzy Kalman filter

In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman Filter and adaptive state controller) is investigated through simulation and experimental tests.

Predictive speed control with fuzzy compensation of a two-mass drive with friction

Purpose The purpose of this paper is to design and test a linear predictive control algorithm with elements of fuzzy logic in the non-linear speed region of a two-mass system with a flexible shaft. Design/methodology/approach To compensate the non-linearity of friction in the low-speed region, the elements of the Q matrix have been retuned with the use of fuzzy logic. First, the influence of the Q matrix on the dynamics of the drive has been discussed. On the basis of these findings a fuzzy system has been developed. Findings It has been demonstrated that applying a relatively simple fuzzy system can reduce unwanted non-linear phenomena in the low-speed region; at the same time, the dynamics of the drive in the other regions is not deteriorated. Originality/value The solutions presented in the paper are original and have not been published so far. The influence of non-linear friction on the work of the drive in the low-speed region at different values of the matrix Q has been shown. Also, a novel system of online adjustment of the values of the Q matrix in a predictive speed controller has been introduced. Besides, the system has been compared against the classical predictive regulator.

Application of moving horizon observer for state estimation in drive system with elastic coupling

In the paper issues related to the application of the moving horizon estimation (MHE) method to state variable reconstruction of the drive system with a flexible connection are described. In the introduction the motivation of the work is presented briefly. Then the mathematical model of the drive is discussed. The MHE algorithm is described in detail. Next the considered estimator is tested under simulation tests. The influence of the system weight to the estimator performance is investigated. The theoretical considerations are supported by experimental tests.