Cascaded predictive controller design for speed control and load torque rejection of induction motor

The wide availability of microprocessors with much higher computational power capabilities has encouraged many researchers during the last decade to introduce the predictive control techniques to the field of power electronics and motor drives. One technique of predictive control, which is called model predictive control, is introduced in this paper and its application to control a five-phase induction motor is also presented. The mathematical formulation of both model predictive torque control and model predictive speed control algorithms are explained, which shows that the algorithms' equations are intuitive so they can be easily understood and implemented. Since a load torque estimate is needed in the predictive speed controller, an observer based on the minimal-order Gopinath's method is designed to get the load torque value. A comparison between the two techniques is carried out based on a simulation study. Also, the simulation results show the effectiveness of the predictive control in achieving a high dynamic performance control of multiphase induction motor drives.

Finite Control Set-Model Predictive Speed Control for Induction Motors with Optimal Duration

Induction motor is very popular in industrial applications due to simple construction, low cost, and cheap maintenance costs. Speed control of induction motor requires frequency and magnitude voltage control. Some Volt/Hz control strategies are applied in speed control of induction motor with various methods such as direct torque control, vector control, harmonic elimination. These methods are very popular but require complex calculations. This paper discusses a simple method to operate an induction motor using the SPWM Volt/Hz, by using a lookup table method. This method contains important numbers as a reference for sinusoidal reference signal used to produce SPWM signal by comparing reference signals and triangular wave carrier signals from dsPIC microprocessor. SPWM Volt/Hz is used because the manufacturing process does not require complex calculations, easy to operate and reliable for induction motor speed operations. To prove that SPWM Volt/Hz can apply on speed control of induction motor, analysis simulation and experimental works were done. They show the proposed control strategy is capable to operate induction motor at the proper speed.

Sliding mode control (SMC) of electric drives constitutes a very popular control method for nonlinear multivariable and time-varying systems, e.g., induction motor (IM) drives. Nowadays, IM are the most popular electrical machines (EM) applied in many industrial applications as motion control devices, including electrical and hybrid vehicles. Nowadays, the control systems of EM are mostly realized using digital techniques (microprocessors and microcontrollers). Therefore, all control algorithms should be discretized or the whole control system should be designed in the discrete-time domain. This paper deals with a discrete-time sliding mode control (DSMC) for IM drives. The discrete algorithms for sliding mode control of the motor speed and rotor flux are derived in detail and next tested in simulation research. The simulation tests include the discrete nature of the power converter supplying the IM and present excellent performance of the developed control structure. To obtain the rotor speed regulation invariant to external disturbances, like load torque or inertia, especially during the reaching phase of the switching line, the discrete version of a time-varying switching line was introduced. It is shown that the assumed dynamics of the IM flux and speed is achieved and the proposed control algorithm can be realized using commonly available microcontrollers. The paper is illustrated with comprehensive simulation results for 1.5 kW IM drive, which are verified by experimental tests.

Because of its low maintenance and robustness, induction motors have many applications in the industries. Most of these applications need fast and smart speed control system. This paper introduces a smart speed control system for induction motor using fuzzy logic controller. Induction motor is modeled in synchronous reference frame in terms of dq form. The speed control of induction motor is the main issue achieves maximum torque and efficiency. Two speed control techniques, Scalar Control and Indirect Field Oriented Control are used to compare the performance of the control system with fuzzy logic controller. Indirect field oriented control technique with fuzzy logic controller provides better speed control of induction motor especially with high dynamic disturbances. The model is carried out by using Matlab/Simulink computer package. The simulation results show the superiority of the fuzzy logic controller in controlling three-phase induction motor with indirect field oriented control technique.

With more than three phases, multi-phase induction machines provide an alluring substitute for lowering the strains placed on the machine's switches and windings. The management of overly produced current is one of the most important issues when making quick and significant adjustments to the speed control of a multi-phase induction motor. Thus, if the speed controller lacks an output amplitude limitation, it may cause harm to both the motor and the power electronics converter. The speed control loop and the two internal current control loops are the first two areas in which this research suggests using polynomial predictive controllers to solve the saturation phenomena of the speed regulator. Then, by convexly optimizing the Youla parameter while accounting for time and frequency constraints, the external predictive speed controller is readjusted. This ensures that the speed response to the reference stays in an imposed model with minimal current control during transient periods, while also preserving the closed-loop functionalities that the initial predictive controller had achieved. The results of the simulation demonstrate how well the suggested control system controls speed under different multi-phase induction machine operating situations.

Two new types of control method have been developed based on model predictive control for stable-target tracking of a nonholonomic mobile robot. One method (Method 1) is a new nonlinear control method. This was developed based on model predictive control (predictive nonlinear control) to predict the next position of a mobile robot using the current velocities of the right and left wheels. This technique uses a tuning guideline in predictive nonlinear control. The other method (Method 2) is a combination of Method 1 and proportional control (predictive proportional nonlinear control). Method 2 involves a tuning guideline not only in a predictive nonlinear controller, but also in a proportional controller. In this technique, the selection of a tuning guideline in the proportional controller is enhanced, and thereby increases the control action in closed-loop responses. In Method 1, the nonlinear controller is derived from Liapunov stability theory, and is used to control the linear and angular velocities for locomotion control. Tuning parameters in the nonlinear controller (in Method 1) are selected to satisfy various design criteria, such as stability, performance, and robustness. Method 1 has certain limitations that result in a decrease of the performance criteria specified. Strong nonlinearities in the mobile robot system result in accumulated errors. To enhance performance further, we developed Method 2 as the solution for decreasing cumulative errors. Hence, the proportional controller is added to Method 1 in the closed-loop form in order to eliminate errors. The advantage of Method 2 is that it can cope with strong nonlinearities in the mobile vehicle system. The results of the performances of Method 1 and Method 2 are shown to demonstrate the effectiveness of both methods, and also the better performance of Method 2. The two new methods are effective in stable-target tracking, yielding an increase in performance and stability.

Fuzzy controlled sensorless speed control of induction motor with MRAS based approach is proposed in this paper. Fuzzy logic controller is expected to be better controller as compared to traditional PI and PID controllers. The mathematical modeling of the MRAS module with inputs from induction motor stator voltages and currents taken as feedback to estimate the speed of the machine is described. The speed control of the induction motor is achieved by IRFOC without speed sensor at the motor. Induction motor speed and electromagnetic torque comparison with PI and FIS controllers integrated into the structure are represented by graphs plotted with time as a reference. Fuzzy controller is modeled with 49 rule base including two inputs and one output variable. All the modules design and the analysis is carried out in MATLAB software with ‘powergui’ toolbox for generating graphs.

Finite set model predictive speed control of induction motor with long horizon

Recently, many studies have been performed for the variable speed control of an induction motor. Direct torque control (DTC) is an emerging technique for the variable speed control of PWM inverter driven induction motors. DTC allows the direct control of stator flux and instantaneous torque through a simple algorithm. In this paper, an ASIC design technique using VHDL is applied to DTC based speed control of an induction motor. ASIC for DTC based speed control is designed through the descriptions of coordinate transformation, speed controller stator flux and torque estimator, stator flux and torque controller stator flux position detector, FSM (finite state machine) and inverter voltage switching vector. Finally the above system has been implemented on the FPGA (XC4052XL-PG411). Simulation and experiments have been performed to verify the performance of the designed ASIC.

In this article, sensorless finite control set model predictive speed control of induction motor using adaptive full-order observer is proposed. Firstly, finite control set model predictive speed control is introduced. It is composed of direct speed control and model predictive control, which gets over the limitations of cascaded structure and obtains high dynamics response. Due to lack of speed loop, stator flux linkage, rotor speed and stator current are taken as the control targets in the cost function. Then, adaptive full-order observer is used to estimate rotor speed and stator flux linkage to improve the reliability and keep the system cost down. Finally, the simulation results indicate that the proposed method has well dynamic performance in the wide speed range.

Induction motor is a cast of alternating current motor where charge endures allotted to the rotor close-at-hand deputation of conductive charge. These motors are broadly applied in industrial claim due to they are arduous along with adhere no contacts. The speed controller of deltoid phase induction motor is applied to alleviate the aberration of speed. The central constructivist of this paper is to accrue the performance of speed sensorless control of three phase induction motor. To increase its performance, this paper presents a modified method for speed controller of an indirect vector-controlled induction motor drive using cloud computing technique. Our methodology depends on speed sensorless scheme to obtain the speed signal feedback; the speed estimator is based on model reference adaptive control that uses the stator current and rotor flux as state variables for estimating the speed. In this method, the stator current error is represented as a function of first degree of the estimated speed error. An analysis and simulation of the tried algorithm is birthed and applied easing a TMS320C31 floating-point notational alert Processor. And accumulate the action of the three phase induction motor we conceived our appraisals affixed to the accountant based on cloud computing tactics. This intelligent policy uses the guidelines of the speed controller efficiently. Simulation and experimental results depicted that the motor speed is decelerated articulately to destine its illusion apprise without above and inferior smack and with about zero steady state error. The apprised accelerate alert and its dispatching buoy amassed off line from burlesque. After effects display an advantageous affinity among the accounted speed alert and it's dispatching allocated as well as aped speed flares.

To enhance the dynamic performance and disturbance rejection capability of the permanent magnet synchronous motor speed control system, a novel speed control method based on a novel sliding mode control (NSMC) and load torque observer is proposed on the basis of model predictive current control (MPCC) with a sliding mode disturbance observer. First, on the basis of MPCC, the influence of parameters such as resistance, inductance, and flux linkage on MPCC is analyzed. To address the aggregated disturbance caused by parameter mismatches, a piecewise square-root switching function sliding mode disturbance observer (SMDO) is designed to enhance the robustness of the parameters. To address the poor dynamic performance and inadequate robustness resulting from the proportional-integral-controller (PI) velocity loop control in the MPCC, a novel NSMC velocity control method is proposed. This method utilizes the hyperbolic sine function and fractional-order integral sliding mode surface, resolving the dilemma faced by traditional slide mode controllers (SMC) in balancing fast response and reduced vibration. Additionally, to enhance the system’s disturbance rejection capability, a sliding mode torque observer (SMTO) is designed to continuously update the observed load torque value into the NSMC controller, achieving speed compensation control. Finally, through comparative experiments among the proportional integral controller (PI), SMC, NSMC, and NSMC + SMTO, the results indicate that the proposed NSMC + SMTO exhibits the best speed response, steady-state characteristics, and disturbance rejection capability.

In this paper we are conveying a new method for speed control system for induction motor which is based on fuzzy logic instead of obsolete indirect vector control using PI controller as a speed regulator in outer speed loop. In obsolete method for speed control system of a induction motor drive uses a voltage source pulse width modulation inverter-fed vector controlled indirectly which is having low precision for the speed control giving bad speed regulation characteristics and decreasing the performance of the whole induction motor drive. To prevail over this PI controller by a automatically sensing fuzzy control system which is based on fuzzy set theory. The execution of this automatically sensing fuzzy control system can be inquired through digital simulation which is based on MATLAB-SIMULINK package. By using this digital simulation system the performance of fuzzy control system can be seen by creating variable operating conditions by varying reference speeds and at different load torques. Consequences of this digital simulation system shows improved performance characteristics of the suggested fuzzy control system over the obsolete PI controller as a speed regulator in outer speed loop

In order to improve the capability of load disturbance resistance of vector control system for a bearingless induction motor, a control strategy of the bearingless induction motor based on sliding mode speed controller and load torque observer is proposed. The control strategy uses fractional integral of velocity error and designs the nonlinear integral order sliding mode surface, and then a new bearingless induction motor speed control system is constructed. The extended sliding mode observer is designed with the rotor position, rotational speed and load torque as the observation object. The low-pass filter is used to weaken the high-frequency chattering of the sliding mode control to improve the accuracy of the observation, and the load torque observation value is compensated to the fractional-order integral sliding mode speed controller. The simulation and experimental results show that the proposed scheme achieves accurate and fast tracking of the load torque, effectively suppresses the chattering and improves the robustness of the system. The control system improves the resistance capacity against load disturbance and has better dynamic performance.