Based on neural network adaptive linear quadratic regulator for inverter with voltage matching circuit

This paper describes a discrete adaptive linear quadratic regulator used to load current control in terms of variable DC voltage of inverter. Controller was designed by using linear quadratic optimization method. Adaptive LQR was used because of non-stationarity of the control system caused by Voltage Matching Circuit - VMC. Gain values of the adaptive controller were approximated by using an artificial neural network. The VMC was realized as an additional buck converter integrated with the main inverter. As the load of the 2-level inverter a 3-phase symmetric RL circuit was used. Simulation tests show the behavior of the load current regulation during DC bus voltage level step changes. The dependence between current RMS value and inverter DC bus voltage level was also shown. There were also made a comparison of the traditional 2-level inverter structure with the modified structure uses VMC. Simulation test was made by using Matlab Simulink and PLECS software

Proportional-Integral-Resonant AC Current Controller

In this paper an improved stationary-frame AC current controller based on the proportional-integral-resonant control action (PIR) is proposed. Namely, the novel two-parameter PIR controller is applied in the stationary-frame AC current control, accompanied by the corresponding parameter-tuning procedure. In this way, the proportional-resonant (PR) controller, common in the stationary-frame AC current control, is extended by the integral (I) action in order to enable the AC current DC component tracking, and, also, to enable the DC disturbance compensation, caused by the voltage source inverter (VSI) nonidealities and by nonlinear loads. The proposed controller parameter-tuning procedure is based on the three-phase back-EMF-type load, which corresponds to a wide range of AC power converter applications, such as AC motor drives, uninterruptible power supplies, and active filters. While the PIR controllers commonly have three parameters, the novel controller has two. Also, the provided parameter-tuning procedure needs only one parameter to be tuned in relation to the load and power converter model parameters, since the second controller parameter is directly derived from the required controller bandwidth value. The dynamic performance of the proposed controller is verified by means of simulation and experimental runs

Artifical potential fields with extended Bug algorithm for Mars rover path planning in an unknown environment

In this paper artificial potential fields method applied to autonomous mobile robot -mars rover is presented. It is assumed that Mars rover operates in an unknown environment. In order to visualize the robot's path in environment Matlab software is used. The object can be inserted by graphic data input interface in top view mode. The method of artificial potential fields is extended by an additional algorithm to avoid a local minimum. The proposed algorithm is implemented as a state machine. In this paper simulations results of the developed algorithm are presented. Extended algorithm is used because in the environment may be located complex obstacles

Neural network based adaptive state feedback controller for inverter with voltage matching circuit

This paper describes a discrete adaptive state feedback controller used to load current control in terms of variable DC voltage of inverter. Controller was designed by using linear quadratic optimization method. Adaptive LQR was used because of non-stationarity of the control system caused by Voltage Matching Circuit - VMC. Gain values of the adaptive controller were approximated by using an artificial neural network. The VMC was realized as an additional buck converter integrated with the main inverter. As the load of the 2-level inverter a 3-phase symmetric RL circuit was used. Simulation tests show the behavior of the load current regulation during DC bus voltage level step changes. The dependence between current RMS value and inverter DC bus voltage level was also shown. Simulation test was made by using Matlab Simulink and PLECS software

PMSM drive based on STM32F4 microcontroller

In this paper based on STM32F4 microcontroller and dedicated for permanent magnet synchronous motor (PMSM) drive is presented. Information concern structure and implementation of the program main blocks such as: modulator, speed and position calculation, communication interface are depicted. Designing process of cascade control structure with PI controllers is shown. An internal model control (IMC) was used to calculate coefficients of current controllers while the symmetric optimum criterion was applied to compute angular speed controller. Since mathematical model of the drive is non-linear, linearization and decoupling procedure as well as dead-time compensation are also included. Finally, experimental test results for PMSM with FOC control algorithm are shown

PMSM drive with adaptive state feedback speed controller

In this paper, the issue related to control of the plant with nonconstant parameters is addressed. In order to assure the unchanged response of the system, an adaptive state feedback speed controller for permanent magnet synchronous motor is proposed. The model-reference adaptive system is applied while the Widrow-Hoff rule is used as adjustment mechanism of controller’s coefficients. Necessary modifications related to construction of the cost function and formulas responsible for adjustment of state feedback speed controller’s coefficients are depicted. The impact of adaptation gain, which is the only parameter in proposed adjustment mechanism, on system behaviour is experimentally examined. The discussion about computational resources consumption of the proposed adaptation algorithm and implementation issues is included. The proposed approach is utilized in numerous experimental tests on modern SiC based drive with nonconstant moment of inertia. Comparison between adaptive and nonadaptive control schemes is also shown

Artifical potential fields algorithm for Mars rover path planning in an unknown enviroment

In this paper artificial potential fields method applied to autonomous mobile robot - Mars rover is presented. It is assumed that Mars rover operates in an unknown environment. In order to visualize the robot's path in environment Matlab software is used. Inserted by graphic data input interface in top view mode obstacles are deployed in environment area. The method of artificial potential fields is extended by an additional algorithm to avoid a local minimum. The proposed algorithm is implemented as a state machine. In this paper simulations results of the developed algorithm are presented

Silicon carbide based DC-DC converter – operating analysis

In this paper operating analysis of DC-DC converter is presented. Silicon Carbide based DC-DC converter is investigated. SiC power switches (i.e. MOSFETs and diodes) were used. Synchronous buck topology is applied for converter structure. The DC-DC converter mathematical model is also presented. The parameters of LC circuit were calculated using shown equations. Working conditions determine the values of output LC circuit (inductance and capacitance). The analysis of working conditions is presented for different switching frequencies. The size of passive components (LC) is compared for different operating points. Experimental tests results were presented. Waveforms of voltage and current signals were also shown

Artificial bee colony based state feedback position controller for PMSM servo-drive – the efficiency analysis

This paper presents a state feedback controller (SFC) for position control of PMSM servo-drive. Firstly, a short review of the commonly used swarm-based optimization algorithms for tuning of SFC is presented. Then designing process of current control loop as well as of SFC with feedforward path is depicted. Next, coefficients of controller are tuned by using an artificial bee colony (ABC) optimization algorithm. Three of the most commonly applied tuning methods (i.e. linear-quadratic optimization, pole placement technique and direct selection of coefficients) are used and investigated in terms of positioning performance, disturbance compensation and robustness against plant parameter changes. Simulation analysis is supported by experimental tests conducted on laboratory stand with modern PMSM servo-drive

Application of extended Kalman filter for estimation of periodic disturbance and velocity ripple reduction in PMSM drive

In this paper an application of extended Kalman filter (EKF) for estimation and attenuation of periodic disturbance in permanent magnet synchronous motor (PMSM) drive is investigated. Most types of disturbances present into PMSM drive were discussed and described. The mathematical model of the plant is presented. Detailed information about the design process of the disturbance estimator was introduced. A state feedback controller (SFC) with feedforward realizes the regulation and disturbance compensation. The theoretical analysis was supported by experimental tests on the laboratory stand. Both time- and frequency-domain analysis of the estimation results and angular velocity were performed. A significant reduction of velocity ripple has been achieved