A DSP-based implementation of a nonlinear model reference adaptive control for a three-phase three-level NPC boost rectifier prototype

In this paper, the design and the implementation of a model reference adaptive control (MRAC) applied to a three-phase three-level neutral-point-clamped (NPC) boost rectifier are presented. This control strategy is developed with a view to regulate dc output and neutral point voltages and to reduce the influence of parameter variations while maintaining unity power factor. A nonlinear multiple-input multiple-output (MIMO) state space model of the rectifier is then developed in dq0 reference frame. The proposed controller is based on the use of a feedback linearization technique followed by a robust MRAC scheme allowing the design of a suitable controller applied to the plant. The control law is designed in Simulink/Matlab and applied to the converter via a 1920-Hz pulse width modulator both executed in real time using the DS1104 DSP of dSPACE. A 1.25 kW laboratory prototype is developed for validation. The experimental results are given for different operating conditions: nominal power operation, balanced and unbalanced dc load steps, boost inductor variation, and reactive power control. The proposed control law performs perfectly in a wide operation range giving low output voltage ripple, low line-current THD, a small overshoot and a fast settling time under system parameters variation.     

Fuzzy adaptive vector control of induction motor drives

This paper deals with the design and experimental realization of a model reference adaptive control (MRAC) system for the speed control of indirect field-oriented (IFO) induction motor drives based on using fuzzy laws for the adaptive process and a neuro-fuzzy procedure to optimize the fuzzy rules. Variation of the rotor time constant is also accounted for by performing a fuzzy fusion of three simple compensation strategies. A performance comparison between the new controller and a conventional MRAC control scheme is carried out by extensive simulations confirming the superiority of the proposed fuzzy adaptive regulator. A prototype based on an induction motor drive has been assembled and used to practically verify the features of the proposed control strategy     

Adaptive on-line parameter identification of a steer-by-wire system

Adaptive compliance control strategy can be a significant advantage for control of steer-by-wire systems. Initially the method is proposed for robotic applications where the main concern is the interaction forces between the robot and its environment. There are several studies about cooperative working of a robot and a human. As long as the steering system is a part of the vehicle where driver interaction is involved, it is reasonable to think that compliance control strategies can be adapted to steer-by-wire systems. Compliance control is a model reference control (MRC) strategy where the measured external force/torque is used as an input to a reference model to calculate its output and where the real system is controlled appropriately to track the reference system output. If a sensor is available to measure the external force/torque, system parameters need not to be estimated. A constant gain feedback controller can be used in such a case. However, if the parameter variations of the system are not within certain bounds, a model reference adaptive controller (MRAC) is needed. In addition to this, examining the change in the dynamics of the system due to the compliance of the driver arms is not possible by direct MRAC, because the driver effect is considered as a disturbance in this strategy. Therefore, in this study, instead of estimating controller parameters using direct MRAC where the main concern is the tracking performance, it is considered to use indirect MRAC in which the system parameters are estimated to observe their variations in the presence of parametric uncertainty and disturbances and to further examine the change in the dynamics of the system due to the compliance of the driver arms forming a closed kinematic structure by constraining the steering wheel. Hence, a steer-by-wire experimental setup including driver interaction and vehicle directional control units has been developed and three well-known adaptive on-line estimation methods, which are output-error method, equation-error method and modified recursive least squares method are evaluated on the driver interaction unit. These three methods are compared in terms of computational complexity, convergence, stability and applicability to real vehicles.     

An MRAC-based nonlinear speed control of an interior PM synchronous motor with improved maximum torque operation

A model reference adaptive control (MRAC)-based nonlinear speed control strategy of an interior permanent magnet (IPM) synchronous motor with an improved maximum torque operation is presented. In most servo systems, the controller is designed under the assumption that the electrical dynamics are neglected by the field-oriented control. This requires a high-performance inner-loop current control strategy. However, the separate designs for a high-performance current regulator and a robust speed controller need considerable effort. To overcome this limitation, an MRAC-based nonlinear speed control strategy for the IPM synchronous motor is presented, considering the whole nonlinear dynamics. Nonlinear speed control is achieved by an input–output linearization scheme. This scheme, however, gives an unsatisfactory performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters are estimated by an MRAC technique in which the disturbance torque and flux linkage are estimated. The adaptation laws are derived from Lyapunov stability theory. In view of the drive efficiency, the motor has to provide the maximum torque for a given input. To drive the IPM synchronous motor under improved maximum torque operation, the estimated flux linkage is employed for the generation of the d-axis current command. The robustness and output performance of the proposed control scheme are verified through simulation results.     

A new method of rotor resistance estimation for vector-controlledinduction machines

The estimation of rotor time constant, or rotor resistance, in a vector-controlled induction machine is necessary to achieve high-performance torque control. A new method of estimating the rotor resistance online, for use in a vector-controlled induction machine, is presented. It uses short duration pulses added to the constant flux reference current i_dse* and based on the resultant torque command current produced by a proportional-integral controller i_qse * adjusts the rotor resistance estimate. This method of self-tuning the vector controller to the rotor time constant, when operating in a closed-loop speed control loop, does not produce torque pulsations when correctly tuned. In comparison to other online methods such as the extended Kalman filter and the extended Luenberger observer, this method does not require voltage sensors and is computationally simpler. The rotor resistance estimation technique is illustrated through simulation and practical implementation of a vector-controlled induction machine     

Model Reference Adaptive Controller-Based Rotor Resistance and Speed Estimation Techniques for Vector Controlled Induction Motor Drive Utilizing Reactive Power

In this paper, a detailed study on the model reference adaptive controller (MRAC) utilizing the reactive power is presented for the online estimation of rotor resistance to maintain proper flux orientation in an indirect vector controlled induction motor drive. Selection of reactive power as the functional candidate in the MRAC automatically makes the system immune to the variation of stator resistance. Moreover, the unique formation of the MRAC with the instantaneous and steady-state reactive power completely eliminates the requirement of any flux estimation in the process of computation. Thus, the method is less sensitive to integrator-related problems like drift and saturation (requiring no integration). This also makes the estimation at or near zero speed quite accurate. Adding flux estimators to the MRAC, a speed sensorless scheme is developed. Simulation and experimental results have been presented to confirm the effectiveness of the technique.     

Parameter Estimation Using Microprocessors and Adaptive Random Search Optimization

An optimization procedure is presented which can be used for off-line system parameter estimation. The technique utilizes a model reference adaptive control configuration and an adaptive random search to identify the parameter values for an arc voltage control system of an automatic welding process. An 8-bit microprocessor is used to acquire data from the system, and a microprocessor development system performs the optimization routine.     

Adaptive decoupling control of induction motor drives

A novel control approach for a robust induction motor drive system with a voltage source inverter has been developed. In the scheme, the induction motor and its corresponding inverter gating signal are controlled using the decoupling control theory. In addition, an adaptive optimal speed regulator employing the model reference adaptive control (MRAC) is incorporated into the drive system to compensate for unfavorable errors. The principles and special features of the control scheme are discussed, and the configuration of the drive system is presented. Comparison is made between conventional proportional plus integral (PI) control and the MRAC. Test results show the robustness and superior dynamic performance of the proposed control system     

Model reference adaptive control for vehicle active suspensionsystems

A model reference adaptive control (MRAC) technique for vehicle active suspension subsystems is presented. The MRAC automatically self-tunes the active suspension so that disturbance and vibration of a vehicle is reduced to a level determined by an ideal conceptual suspension reference model. The Lyapunov stability method was used in the design of the MRAC. It is shown that the MRAC suspension can accommodate large variances in sprung load and suspension component characteristics and achieves significant improvements over the passive suspension. Real-time simulation and animation (RTSA) software was developed to provide a visual aid for understanding and interpreting the performance of the MRAC suspension     

Online identification of induction machine electrical parameters for vector control loop tuning

In a vector-controlled induction machine drive, accurate knowledge of the machine electrical parameters is required to ensure correct alignment of the stator current vector relative to the rotor flux vector, to decouple the fluxand torque-producing currents and to tune the current control loops. This paper presents a new method for online identification of the induction machine parameters required to tune a rotor-flux-oriented (RFO) vector control scheme. Accuracy of the slip frequency estimation required for RFO vector control is achieved by utilizing the parameter independent "flux pulse" rotor time constant estimation scheme, which utilizes short-duration pulses injected into the flux-producing current. The parameters required to tune the synchronous frame current control loops with a decoupling circuit are estimated using a recursive estimation scheme derived from the synchronous frame voltage equations. As the "flux pulse" scheme requires signal injection into the flux-producing current a new rotor time constant estimation scheme is presented, based on the sensitivity analysis of the recursive parameter estimation scheme. Simulation and experimental results are presented which demonstrate the effectiveness of the online parameter identification and control loop tuning technique.     

A simple and robust digital current control technique of a PMsynchronous motor using time delay control approach

A simple and robust digital current control technique of a permanent magnet (PM) synchronous motor using a time delay control approach is presented. Among the various current control schemes for a voltage source inverter-fed PM synchronous motor drive, the predictive control is known to give a superior performance. This control technique, however, requires the full knowledge of machine parameters and operating conditions, and gives an unsatisfactory response under the parameter mismatch between the motor and controller. To overcome such a limitation, the disturbances caused by the parameter variations are estimated by using a time delay control approach and used for the computation of the reference voltages by a simple feedforward control. Thus, the steady-state control performance can be significantly improved in an extremely simple manner, while retaining the good characteristics of the predictive control such as the good transient response and stable inverter operation. The proposed control scheme is implemented on a PM synchronous motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simulations and experiments     

A discrete adaptive field-oriented induction motor drive

A discrete model reference adaptive controller (MRAC) is designed and implemented. This MRAC makes the performance of the field-oriented induction motor drives insensitive to parameter changes. Only the information of the reference model and the plant output are required. Hence, the proposed controller is easy to implement practically. For designing the proposed adaptive controller, the dynamic model of the drive system is estimated from the sampled input-output data using the stochastic modeling technique. The theoretical basis of the adaptive control is derived and simulation is made. The hardware of the drive system and the microprocessor-based adaptive controller are discussed. Some experimental results are given to demonstrate the effectiveness of the proposed controller     

Adaptive neural network feedback control of a passive line-of-sight stabilization system

An adaptive neural network full-state feedback controller has been designed and applied to the passive line-of-sight (LOS) stabilization system. Model reference adaptive control (MRAC) is well established for linear systems. However, this method cannot be utilized directly since the LOS system is nonlinear in nature. Utilizing the universal approximation property of neural networks, an adaptive neural network controller is presented by generalizing the model reference adaptive control technique, in which the gains of the controller are approximated by neural networks. This removes the requirement of linearizing the dynamics of the system, and the stability properties of the closed-loop system can be guaranteed.     

A nonlinear speed control for a PM synchronous motor using a simpledisturbance estimation technique

A nonlinear speed control for a permanent-magnet (PM) synchronous motor using a simple disturbance estimation technique is presented. By using a feedback linearization scheme, the nonlinear motor model can be linearized in the Brunovski canonical form, and the speed controller can be easily designed based on the linearized model. This technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. An adaptive linearization technique and a sliding-mode control technique have been reported. Although good performance can be obtained, the controller designs are quite complex. To overcome this drawback, the controller parameters are estimated by using a disturbance observer theory where the disturbance torque and flux linkage are estimated. Since only the two reduced-order observers are used for the parameter estimation, the observer designs are considerably simple and the computational load of the controller for parameter estimation is negligibly small. The nonlinear disturbances caused by the incomplete linearization can be effectively compensated by using this control scheme. Thus, a desired dynamic performance and a zero steady-state error can be obtained. The proposed control scheme is implemented on a PM synchronous motor using a digital signal processor (TMS320C31) and the effectiveness is verified through the comparative simulations and experiments     

New robust adaptive control algorithm for high-performance ACdrives

This paper presents a new robust structure for a model reference adaptive control (MRAC) controller for field-oriented-controlled (FOC) drives which requires no prior knowledge of the drive parameters and is guaranteed to provide global asymptotic stability of the closed-loop system. This structure simplifies the design and implementation of the adaptive controller requiring less effort to synthesis than a standard MRAC system. Discussion on theoretical aspects, such as selection of a reference model, stability analysis proof, gain adaptive process, steady-state error elimination, and robustness to unmodeled dynamics are included. The paper describes many practical aspects of the implementation, such as adaptive gain analysis, adaptive rate selection, the gain variation limits, gain windup prevention measure, and initial values. The new robust adaptive controller has been successfully implemented on an FOC drive and experiment results for dynamic tracking, sudden loading and unloading, and gains adaptation under different operation conditions are presented to support the robustness of the proposed controller     

Hot carrier induced bipolar transistor degradation due to basedopant compensation by hydrogen: theory and experiment

New experimental and analytical results are presented which show that extrinsic and intrinsic base dopant compensation by hydrogen is responsible for large changes in the bipolar transistor parameters of emitter-base breakdown voltage (V_ebo), forward collector current (I_c) and series base resistance (R_bx) when such transistors are operated under avalanche and inverted mode stress conditions. A new physical model has been developed to explain the observed changes in V_ebo and I_c as a function of stress time, and the analytical results are shown to be well correlated with the experimental data. Lastly, the effects of degradation on transistor voltage gain bandwidth (f_max) and emitter coupled bipolar comparator delay (τ_delay) are assessed and discussed in terms of circuit performance degradation     

Model Reference Adaptive Control Based on Adjustable Reference Model during Mode Transition for Hybrid Electric Vehicles

Hybrid elective vehicles (HEVs) operate in multiple driving modes, e.g., motor driving mode, engine driving mode, and combined driving mode, under various different scenarios. Therefore, mode transition between different driving modes is necessary to ensure high-efficiency operation of HEVs under various running conditions. This paper proposes adjustable reference model (ARM)-based model reference adaptive control (MRAC) to solve the problems of deviation from driver's intention and lack of adaptability to parameter changes. The driveline dynamics model during mode transition is built and validated. The dynamics in the mode before the mode transition is taken as the reference model whose parameters are estimated online. Thereafter, the adaptive law is derived. Simulation and hardware-in-loop experiments are carried out. The results show that the mode transition performance under varying driver's demand torque is satisfactory in terms of not only vehicle jerk, but also clutch slipping time and frictional loss. And, the controller has good adaptability to different vehicle masses and road slopes. The ability to deal with the disturbance in clutch torque with low frequency is also validated.     

An RMRAC Current Regulator for Permanent-Magnet Synchronous Motor Based on Statistical Model Interpretation

A new robust model reference adaptive control (RMRAC) scheme for the current regulation of a permanent-magnet synchronous motor (PMSM) is proposed in a synchronous frame, which is completely free from the control performance degradation caused by parameter uncertainties. The current regulator of the PMSM is the innermost loop of its electromechanical driving system and plays an important role in the control hierarchy. When the PMSM runs precisely at high speeds, the cross-coupling terms must be compensated for. In the proposed RMRAC, the input signal is composed of the control voltage obtained by the model reference adaptive control (MRAC) law and the output of the disturbance estimator. The gains of the feedforward and feedback controllers are estimated by the proposed modified gradient method, where the system disturbances are filtered out by the estimated current regulation error. A voltage corresponding to the estimated system disturbances is fed forward to the control input in order to filter out the disturbances. The proposed method compensates the cross-coupling terms in a synchronous current model regardless of parameter variations. It also shows a good real-time performance due to the simplicity of control structure. Through simulations and real experiments, the efficiency of the proposed method is verified.     

DC-Voltage-Ratio Control Strategy for Multilevel Cascaded Converters Fed With a Single DC Source

Recently, a multilevel cascaded converter fed with a single dc source has been presented. An analysis of the steady-state working limits of this type of converter is presented in this paper. Limits of the maximum output voltage and the minimum and maximum loading conditions for stable operation of the converter are addressed. In this paper, a way to achieve any dc voltage ratio (inside the stable operation area of the converter) between the H-bridges of the single-dc-source cascaded H-bridge converter is presented. The proposed dc-voltage-ratio control is based on a time-domain modulation strategy that avoids the use of inappropriate states to achieve the dc-voltage-ratio control. The proposed technique is a feedforward-modulation technique which takes into account the actual dc voltage of each H-bridge of the converter, leading to output waveforms with low distortion. In this way, the dc voltage of the floating H-bridge can be controlled while the output voltage has low distortion independently of the desired dc voltage ratio. Experimental results from a two-cell cascaded converter are presented in order to validate the proposed dc-voltage-ratio control strategy and the introduced concepts.