An Application of Symmetrical Optimum Method to Servo Systems with Variable Inertia

The paper presents an application of the Symmetrical Optimum method under the form of the Extended Symmetrical Optimum method to the design of controllers for servo systems with variable inertia. A brushless direct current servo system with variable inertia is considered as the plant. A proportional-integral controller is tuned for the speed control of this plant using the Extended Symmetrical Optimum method. The results are shown for four values of the moment of inertia and two variable reference input shapes

Performance Analysis Stability Of Speed Control Of BLDC Motor Using PID-BAT Algorithm In Electric Vehicle

The research on the development of electric vehicles includes such as power electronics, energy storage capability that the higher the battery, reducing fuel emissions, and the motor efficiency.  The electric motor efficiency requires the automatic control on the main parameters such as speed, position, and acceleration.  The performance setting of speed Brushless DC (BLDC) Motor can be improved by using the controller Proportional Integral Derivative (PID), a combination of PID using nature inspired optimization algorithms such as Bat Algorithm (BA). BA is one of the optimization algorithm that mimics the behavior of bats on the move using a vibration or sound pulses emitted a very loud (echolocation) and listen to the echoes that bounce back from the object to determine the circumstances surrounding vicinity   In this paper, simulate of Bat Algorithm to find the best value PID controller parameter to speed control BLDC motor  and analyze performance such as the value of overshoot, steady state. The result  simulation shows that values for the PID parameters without using algorithm bat is Kp = 208.1177, Ki = 1767, and Kd = -8.6025. While using the algorithm bat got value Kp = 5.4303e+04, Ki = -1.3059e+06, and Kd = 3.0193e+04. The performance of the motor obtained through value rise time of  0. 282,  settling time of 1.5, overshoot  value  of 20.5%  and the peak value of  1.21.

Analysis and control of chaos for lateral dynamics of electric vehicles

In this paper, the nonlinear dynamic model of the lateral system for electric vehicles (EVs) is proposed. Different from the traditional steering system, a driver’s reaction model is introduced and meanwhile the disturbance caused by irregularities of road surface is also considered in this paper. Based on the integrated nonlinear dynamic equations, it shows that the stability of lateral system of EVs is closely related to the heading speed of the vehicle. The lateral system has a Hopf bifurcation when the vehicle heading speed equals a critical value, and then enters into chaos domain along with the increment of the vehicle heading speed. The unstable behaviors may make EVs spin and even turn over, which are quite harmful to the safety of EVs. As for this issue, a control method is proposed and implemented to protect the vehicle from spinning and thus improve the safety of EVs. The computer simulation is utilized in this paper to analyze nonlinear dynamics, as well as to validate the existence of chaotic motions and the feasibility of the control scheme. From the simulation results, it shows that the chaotic motions existing in the EV lateral dynamics can be suppressed by the proposed control method, and thus the corresponding cornering performance and safety are improved.published_or_final_versio

Energy-oriented Modeling And Control of Robotic Systems

This research focuses on the energy-oriented control of robotic systems using an ultracapacitor as the energy source. The primary objective is to simultaneously achieve the motion task objective and to increase energy efficiency through energy regeneration. To achieve this objective, three aims have been introduced and studied: brushless DC motors (BLDC) control by achieving optimum current in the motor, such that the motion task is achieved, and the energy consumption is minimized. A proof-ofconcept study to design a BLDC motor driver which has superiority compare to an off-the-shelf driver in terms of energy regeneration, and finally, the third aim is to develop a framework to study energy-oriented control in cooperative robots. The first aim is achieved by introducing an analytical solution which finds the optimal currents based on the desired torque generated by a virtual. Furthermore, it is shown that the well-known choice of a zero direct current component in the direct-quadrature frame is sub-optimal relative to our energy optimization objective. The second aim is achieved by introducing a novel BLDC motor driver, composed of three independent regenerative drives. To run the motor, the control law is obtained by specifying an outer-loop torque controller followed by minimization of power consumption via online constrained quadratic optimization. An experiment is conducted to assess the performance of the proposed concept against an off-the-shelf driver. It is shown that, in terms of energy regeneration and consumption, the developed driver has better performance, and a reduction of 15% energy consumption is achieved. v For the third aim, an impedance-based control scheme is introduced for cooperative manipulators grasping a rigid object. The position and orientation of the payload are to be maintained close to a desired trajectory, trading off tracking accuracy by low energy consumption and maintaining stability. To this end, an optimization problem is formulated using energy balance equations. The optimization finds the damping and stiffness gains of the impedance relation such that the energy consumption is minimized. Furthermore, L2 stability techniques are used to allow for time-varying damping and stiffness in the desired impedance. A numerical example is provided to demonstrate the results

Modeling and control of a brushless DC motor

Permanent magnet brushless DC motors (PMBLDC) find wide applications in industries due to their high power density and ease of control. These motors are generally controlled using a three phase power semiconductor bridge. For starting and the providing proper commutation sequence to turn on the power devices in the inverter bridge the rotor position sensors required. Based on the rotor position, the power devices are commutated sequentially every 60 degrees. To achieve desired level of performance the motor requires suitable speed controllers. In case of permanent magnet motors, usually speed control is achieved by using proportional-integral(PI) controller. Although conventional PI controllers are widely used in the industry due to their simple control structure and ease of implementation, these controllers pose difficulties where there are some control complexity such as nonlinearity, load disturbances and parametric variations. Moreover PI controllers require precise linear mathematical models. This thesis presents a Fuzzy Logic Controller(FLC) for speed control of a BLDC by using. The Fuzzy Logic(FL) approach applied to speed control leads to an improved dynamic behavior of the motor drive system and an immune to load perturbations and parameter variations. The FLC is designed using based on a simple analogy between the control surfaces of the FLC and a given Proportional-Integral controller(PIC) for the same application. Fuzzy logic control offers an improvement in the quality of the speed response, compared to PI control. This work focuses on investigation and evaluation of the performance of a permanent magnet brushless DC motor (PMBLDC) drive, controlled by PI, and Fuzzy logic speed controllers. The Controllers are for the PMBLDC motor drive simulated using MATLAB soft ware package. Further, the PI controller has been implemented on an experimental BLDC motor set up

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

State-of-art on permanent magnet brushless DC motor drives

Permanent magnet brushless DC (PMBLDC) motors are the latest choice of researchers due to their high efficiency, silent operation, compact size, high reliability and low maintenance requirements. These motors are preferred for numerous applications; however, most of them require sensorless control of these motors. The operation of PMBLDC motors requires rotor-position sensing for controlling the winding currents. The sensorless control would need estimation of rotor position from the voltage and current signals, which are easy to be sensed. This paper presents a state of art on PMBLDC motor drives with emphasis on sensorless control of these motors