Time-varying Load Torque Research Articles

Hierarchical optimal intelligent battery thermal management strategy for an electric vehicle based on ant colony sliding mode control

Excessive temperature of battery pack causes the performance degradation, affecting the normal operation and safety of the electric vehicles (EVs). This paper proposes an ant colony optimization-fuzzy sliding mode control (ACO-FSMC) hierarchical strategy for the battery thermal management system (BTMS) of EVs. Ignoring the dynamic process of the pump and compressor leads to the deviation of the cooling efficiency of EVs. Therefore, a control-oriented BTMS model is established to describe the temperature dynamics of battery pack and coolant, considering driving current effect on the speed of pump and compressor. Then, a hierarchical optimization strategy is designed to realize the control of the battery cooling rate as well as the speed of the pump and compressor. The upper layer of controller use an ant colony optimization (ACO) to solve the reference speed of the pump and compressor while satisfying constraints of physical characteristics of actuators, aiming at reducing battery temperature deviation and saving energy of BTMS. Considering the nonlinearity of lower layer of BTMS caused by the disturbance of time-varying load torque, fuzzy sliding mode control (FSMC) is applied to control the speed of pump and compressor, in which an integral sliding surface is designed to reduce the influence of disturbance. In order to weaken the chattering of sliding mode control and reduce energy consumption, fuzzy controller is used to adjust the reaching law parameters of sliding mode surface. The simulation results show that compared with PID, the maximum temperature deviation of ACO-FSMC is reduced by 43%, and the energy consumption is reduced by 23%.

Sensorless Scheme for Permanent-Magnet Synchronous Motors Susceptible to Time-Varying Load Torques

This paper is devoted to designing a sensorless high-speed tracking control for surface-mount permanent-magnet synchronous motors, considering a time-varying load torque. This proposal consists of an extended-state observer interconnected with a PI-compensated controller, considering only the measurement of electrical variables for feedback. First, to design the extended-state observer, a rotary coordinate model of the motor is extended in one state to estimate the load torque and the rotor’s position and speed. Later, the estimations are fedback to a PI-compensated controller to attenuate the time-varying load torques. Our proposed methodology aims to overcome a restriction regarding the solution of the Riccati equation respecting the Lipschitz condition for observer stability analysis. Therefore, a PI-compensated controller described as a closed-loop provides a sensorless scheme. Lyapunov stability analysis is applied to determine sufficient conditions to ensure that the states of the closed-loop system are ultimately bounded, which is one of our main contributions. The proposed observer-based controller scheme deals with unmeasured load torque fluctuations. Furthermore, we carry out high-precision emulations to provide testing scenarios of the permanent-magnet synchronous motor with some challenging load torque magnitudes and behaviors. Finally, we conduct experiments on the Technosoft® development platform to corroborate the feasibility of the proposed control scheme in a real-world scenario.

Additive-state-decomposition-based model predictive tracking control for PMSM servo system with multiple disturbances

This paper presents an additive-state-decomposition-based model predictive tracking control and disturbance rejection method for a permanent magnet synchronous motor (PMSM) servo system subject to unknown parameter perturbations, unmodeled dynamics, and time-varying load torque. The basic idea of this method is to equivalently decompose the original system into a primary system for handling the tracking control subproblem and a secondary system for dealing with the robust stabilization subproblem. A model predictive controller is designed for the primary system to achieve high-accuracy tracking of the reference speed. As for the secondary system, a novel high-order generalized extended state observer (HGESO) is constructed to estimate the multiple disturbances simultaneously, and a state feedback control law incorporating a disturbance compensator is developed to eliminate the adverse effect of the multiple disturbances on the system output. By combining the control inputs of the two subsystems together, the control objectives of the original system can be achieved. Both the stability criterion and design procedure of the closed-loop control system are developed. Finally, hardware-in-the-loop-based comparative experiments are conducted to demonstrate that the proposed method effectively suppresses the influence of the multiple disturbances on motor speed tracking accuracy and that the control system has both satisfactory dynamic performance and robustness.

ADP-Based Optimal Control for Systems With Mismatched Disturbances: A PMSM Application

In this brief, in order to optimize the tracking accuracy and enhance the robustness of the tracking process for permanent magnet synchronous motor (PMSM), an adaptive dynamic programming(ADP)-based optimal control strategy combining with anti-disturbance control method is proposed. We consider the unknown, mismatched and time-varying load torque as a disturbance and a disturbance observer is then designed. Based on the output of the disturbance observer, a feedforward control can compensate the disturbance in the PMSM in real time. For the easy implementation of optimal control, this brief adopts the actor-critic neural network to approximate the value function and the optimal controller, respectively. A composite controller is then proposed to ensure that the speed can track the reference signal in an optimal and robust way. Finally, an experiment based on a motor towed platform is given to prove the optimality and robustness.

Enhanced dynamic performance in DC–DC converter‐PMDC motor combination through an intelligent non‐linear adaptive control scheme

A novel neuro-adaptive control scheme is proposed in the context of angular velocity tracking in DC–DC buck converter driven permanent magnet DC motor system. The controller builds upon the idea of backstepping and consists of a fast single hidden layer Hermite neural network (HNN) module equipped with on-board (adaptive) learning to counteract the unknown non-linear time-varying load torque and to ensure nominal tracking performance. The HNN has a simple structure and exhibits promising speed and accuracy in estimating dynamic variations in the unknown load torque apart from being computationally efficient. The proposed method guarantees a rapid recovery of nominal angular velocity tracking under parametric and non-parametric uncertainties. In order to verify the performance of the proposed neuro-adaptive speed controller, extensive experimentation has been conducted in the laboratory under various real-time scenarios. Results are obtained for start-up, time-varying angular velocity tracking and under the influence of highly non-linear unknown load torque. The performance metrics such as peak undershoot/overshoot and settling time are computed to quantify the transient response behaviour. The results clearly substantiate theoretical propositions and demonstrate an enhanced dynamic speed tracking under a wide operating regime, thus confirming the suitability of proposed method for fast industrial applications.

Disturbance observer-based adaptive position control for a cutterhead anti-torque system

To conveniently replace worn cutterhead tools in complicated strata, a novel cutterhead attitude control mechanism was recently designed. Meanwhile, the mechanism also causes an engineering problem of how to control a matching cutterhead anti-torque system (CATS) effectively, which is used to prevent a drive box of the cutterhead from rotation during a complex excavation process. In this paper, a disturbance observer-based adaptive position controller is proposed for the CATS. The proposed method presents a nonlinear adaptive controller with adaptation laws to compensate for the unknown time-varying load torque and damping uncertainty in the system. Based on the disturbance observer method and sliding mode control, an asymptotically stable controller proven by Lyapunov theory is constructed using the back-stepping technique. In addition, a virtual test rig based on MATLAB and AMESim co-simulation is built to verify the validity of the proposed controller. The simulation results show that the proposed method has good performance for tracking tasks in the presence of uncertainties compared with PID control. Together, the data support targeting disturbance observer-based adaptive position control as a potential control strategy for cutterhead anti-torque systems.

Experimental output regulation of permanent magnet synchronous motor position servo system: An internal model-based two-step control approach

It is well known that the position tracking control problem of permanent magnet synchronous motor (PMSM) is a challenging task when parameter uncertainties and time-varying load torque disturbances are taken into account. In this paper, a two-step controller design strategy composed of triple-loop control and internal model control is proposed to achieve a wide range of position tracking control of PMSM, where the reference position can be a relatively large value. In contrast, only local position tracking control problem has been solved by an internal model approach from output regulation theory in the recent work. In addition to the simulation results, the first experimental study is conducted to demonstrate the effectiveness of the proposed two-step control method. It is worth mentioning that our design can guarantee precise position tracking with a wide position range despite parameter uncertainties and time-varying load torque disturbances.

Nonlinear speed tracking control of PMSM servo system: A global robust output regulation approach

It is well known that load torque disturbance and parametric uncertainties commonly exist in permanent magnet synchronous motor (PMSM) and may reduce the tracking accuracy especially when the reference trajectory is time-varying. Thus it is challenging to achieve precise speed tracking control with both load torque disturbance and parametric uncertainties being taken into account. This task can be formulated as a global robust output regulation problem (GRORP) of multi-input, multi-output nonlinear system. In this paper, a systematic internal model control (IMC) method is proposed to solve the GRORP. By constructing a suitable internal model, we convert the GRORP into a global stabilization problem of an augmented system, and then design a stabilization controller to globally stabilize the augmented system. To validate the advantages of the proposed IMC method, comparative studies with conventional proportional–integral speed control method and linear active disturbance rejection control method are conducted via simulations and experiments. It is worthy of mentioning that our method can not only achieve high precision speed tracking performance under time-varying reference speed and/or load torque disturbance, but also allow all the motor parameters to be uncertain.

Robust sensorless FCS-PCC control for inverter-based induction machine systems with high-order disturbance compensation

Due to its theoretically fast dynamic response with unlimited bandwidth for direct switch-driven-based induction machines, the finite control set predictive current control (FCS-PCC) method has been verified to be an effective solution in recent years. However, dynamic limitations of the outer speed PI controller exist, especially with high-order time-varying disturbances. In addition, hardware cost can be reduced. Using the universal proportional integral observer (UPIO) method, a robust deadbeat-like encoderless-based FCS-PCC control scheme is investigated for induction machine systems in this paper. The encoder is avoided using the proposed sensorless method. In addition, the system response and disturbance attenuation are enhanced in presence of time-varying unknown load torque and uncertainties. The squared norm is adopted for the cost function design to ensure system stability. Experimental results illustrate that it has good performance such as fast dynamics, good low-speed steady-state accuracy, and robustness.

Robust Output Regulation of Permanent Magnet Synchronous Motors by Enhanced Extended Observer

This paper presents an application of the enhanced extended observer design with regard to the problem of robust output regulation of permanent magnet synchronous motors. The control framework is further advanced by means of the internal model so as to cope with disturbances represented by the time-varying load torque. The paper shows simulation of regulating a motor for different cases of torque loads and references and provides an explicit procedure of the recursive calculation of the enhanced extended observer coefficients.

Robust Predictive Speed Regulation of Converter-Driven DC Motors via a Discrete-Time Reduced-Order GPIO

Converter-driven direct current (dc) motors exhibit various advantages in industry, but impose several challenges to higher precision speed regulation in the presence of parametric uncertainties and exogenous, time-varying load torque disturbances. In this paper, the robust predictive speed regulation problem of a generic dc–dc buck converter-driven permanent magnet dc motors is addressed by using an output feedback discrete-time model predictive control algorithm. A new discrete-time reduced-order generalized proportional-integral observer (GPIO) is proposed to reconstruct the virtual system states as well as the lumped disturbances. The estimates of GPIO are then collected for output speed prediction. An optimized duty ratio law of the converter is obtained by solving a constrained receding horizon optimization problem, where the operational constraint on control input is explicitly taken into account. Finally, the effectiveness of the proposed new algorithm is demonstrated by various experimental testing results.

New approach to control the induction motors based on immersion and invariance technique

In this study, a new adaptive controller is introduced for the induction motors (IMs) based on immersion and invariance (I&I) technique. The dynamics of the IM system are perturbed by some disturbances such as time-varying rotor resistance and load torque. Accordingly, an adaptive controller is designed and the uncertain parameters are online estimated. The adaptation laws are obtained from the stability analysis based on I&I method. The simulation results verified the effectiveness of the proposed control method. It is revealed that the outputs of the IM could track the desired signals in the presence of the mentioned disturbances. Also, the results are compared with the conventional control methods and it is concluded that the proposed control approach resulted in better performance.

Nonlinear adaptive speed control of a permanent magnet synchronous motor: A perturbation estimation approach

This paper presents a nonlinear adaptive control (NAC) scheme for the speed regulation of a permanent magnet synchronous motor (PMSM) based on perturbation estimation and feedback linearizing control. All PMSM system’s unknown nonlinearities, parameter uncertainties, and external disturbances including unknown time-varying load torque disturbance, are defined as lumped perturbation terms, which are estimated by designing perturbation observers. The estimates are used to adaptively compensate the real perturbations and achieve adaptive feedback linearizing control of the original nonlinear system. The proposed control scheme does not require accurate system model and full state feedback. Stability of the close-loop system with proposed NAC is investigated via Lyapunov theory, and the effectiveness of proposed NAC scheme is verified through both simulation and experimental studies. Both simulation and experimental results show that the proposed NAC scheme can provide less regulation error in speed tracking, better dynamic performance and robustness against parameter uncertainties and load torque disturbance, compared with conventional vector control and load torque estimated based control.

Synchronous control of two counter-rotating eccentric rotors in nonlinear coupling vibration system

Abstract In this paper, the problem of speed and phase synchronization control of two eccentric rotors (ERs) driven by asynchronous motors in a nonlinear vibration system (NVS) with nonlinear time-varying load torque is investigated. The electromechanical dynamic coupling model of NVS is established, in which the complex control of the electromechanical coupling model converts to speed and phase synchronization control of two ERs. A precise control method of speed and phase synchronization of ERs for NVS is proposed. Design the speed and phase synchronization controller by cross-coupling control (CCC) strategy and adaptive global sliding mode control (AGSMC) algorithm. The controller stability is verified by Lyapunov theorem and Barbalat lemma. The performance of the proposed control system is proved by simulation analysis and compared with the traditional self-synchronization method. The results show that the proposed control system considering the cross-coupling characteristics of ERs can effectively control the speed and phase synchronization of two ERs in NVS. The proposed control method can reduce the chattering clearly and improve the control precision. The influence of the nonlinear force of the material on the vibration system is analyzed. The influence of reference speed and parameter perturbation on the synchronization performance is discussed, and the proposed controller is proved with strong robustness. The proposed control system considering the cross-coupling characteristics of ERs can make the NVS implement stable linear vibration locus in the working direction.

Energy Optimal Control of PMSM Drive for Time-Varying Load Torque

Speed and position controller respecting principles of energy optimal control for the drives with permanent magnet synchronous motor and time varying load torque are developed as a contribution to the energy saving and environmental protection. Two approaches to the energy saving controller design are analyzed and compared. The first one is strictly based on energy optimal control theory and derives analytical solutions of the control problem. The second approach for comparison presents approximated solution for the drive’s position controller when the optimal speed trajectory is modified to trapezoidal profile. Results are verified by simulation.

High-Order Sliding Mode Block Control of Single-Phase Induction Motor

A new sliding mode (SM) observer-based controller for single-phase induction motor is designed. The proposed control scheme is formulated using block control feedback linearization technique and high-order SM algorithms with measurements of the rotor speed and stator currents. The stability of the complete closed-loop system, including the rotor flux second-order SM observer, is analyzed in the presence of model uncertainty, namely, rotor resistance variation and bounded time-varying load torque.

Design and Implementation of Speed Controller with Anti-Windup Scheme for Three Phase Induction Motor Used in Electric Vehicle

of reliable and robust controller for electric vehicle in urban and sub urban areas is very much challenging task due to time varying load torque requirement at the wheel of the vehicle. In this paper indirect field oriented vector control of induction motor, PI speed control with anti-windup scheme and hysteresis current control scheme have been proposed for three phase induction motor drive train and simulated in MATLAB Platform. For its hardware implementation, a laboratory level experimental set up has been build up and the control logic has been tested successfully by performing a no of experiments at different operating conditions. KeywordsVehicle, Three Phase Induction Motor, IFOC, Anti- windup PI controller, Hysteresis Current Controller

Passivity-Based Control Strategies of Doubly Fed Induction Wind Power Generator without Speed Sensors

Due to its great potential value in theory and application, nonlinear control strategies of doubly fed induction generator (DFIG), especially passivity-based control (PBC) methods, have been a focus in the literature. A PBC strategy for DFIG with time-varying load torque to track flux and speed trajectories is proposed in this paper. The key point of this method is the identification of terms, known as workless forces, which appear in the dynamic equations of DFIG but have no effect on the energy balance equation of the closed loop. The speed of DFIG is estimated via an ANN estimator avoiding the use of mechanical sensors. PBC combined with ANN speed estimator not only reserves the advantages of PBC such as nonexistence of singularity, but also rejects the flux and speed tracking error caused by stator and rotor resistance variation. This algorithm simplifies the control structure and enhances the robustness of the control system. The feasibility and effectiveness is testified by the experimental results based on dSPACE.

Robust nonlinear receding-horizon control of induction motors

Nonlinear robust receding-horizon control is designed and applied to fifth-order model of induction motor in cascade structure. The controller is based on a finite horizon continuous time minimization of the predicted tracking errors and no online optimization is needed. The initial system is decomposed into two sub-systems (mechanical and electromagnetic sub-systems) in cascade form. An integral action is incorporated in external loop to increase the robustness of the controller with respect to unknown time-varying load torque and mechanical parameters uncertainties. The control uses only measurement of the rotor speed and stator currents. The rotor flux is estimated by Kalman filter. The proposed nonlinear controller permits to achieve asymptotic speed and flux tracking in presence of mechanical parameters uncertainties, unknown variable load torque and resistances variations. In addition, it assures asymptotic decoupling of the speed and flux subsystems. The controller is applied, via simulation, to a benchmark example.

Adaptive backstepping control of a speed-sensorless induction motor under time-varying load torque and rotor resistance uncertainty

A new global adaptive backstepping controller is designed for induction motor speed control based on measurements of stator current and estimation of rotor speed. The designed partial state feedback controller is singularity free and guarantees asymptotic tracking of smooth reference trajectories for the speed of the motor under time varying load torque and rotor resistance uncertainty. The new control algorithm generates estimates for unknown time varying load torque, rotor resistance and rotor speed, which asymptotically tracks and converges to their true values. The rotor flux modulus asymptotically tracks a desired reference signal which allows the motor to operate within its specifications. As in the field-oriented control scheme; the control algorithm generates references for the magnetising flux component and for the speed component of the stator current. The control strategy yields decoupled rotor speed and rotor flux amplitude tracking control goals which allow the selection of an appropriate flu...