Discrete-time sliding mode control based on disturbance observer applied to current control of permanent magnet synchronous motor

This paper proposes a robust current control technique based on a discrete-time sliding mode controller and a disturbance observer for high-performance permanent magnet synchronous motor (PMSM) drives. This scheme is applied in the PMSM current control loops to enable the decoupling between the dq current axes, rejection of disturbances caused by mechanical load changes and robustness under parametric uncertainties. In order to ensure the discrete-time sliding mode properties, which make the system cross the sliding surface at each sampling period, the PMSM model is extended, including the digital implementation delay resulting from the discrete-time algorithm execution. The development of this method allows direct implementation in microcontrollers and digital signal processors. Stability and convergence analysis are developed in the discrete-time domain. Simulation and experimental results demonstrate the effectiveness and good performance of the proposed current control approach

On Vibration Suppression and Trajectory Tracking in Largely Uncertain Torsional System: An Error-based ADRC Approach

In this work, a practically relevant control problem of compensating harmonic uncertainties is tackled. The problem is formulated and solved here using an active disturbance rejection control (ADRC) methodology. A novel, custom ADRC structure is proposed that utilizes an innovative resonant extended state observer (RESO), dedicated to systems subjected to harmonic interferences. In order to make the introduced solution more industry-friendly, the entire observer-centered control topology is additionally restructured into one degree-of-freedom, compact, feedback error-based form (similar to ubiquitous in practice PID controller). Such reorganization enables a straightforward implementation and commission of the proposed technique in wide range of industrial control platforms, thus potentially increasing its outreach. In order to verify the efficiency of the introduced method, a multi-criteria experimental case study using a torsional plant is conducted in a trajectory tracking task, showing satisfactory performance in vibration suppression, without the often problem of noise amplification due to high observer/controller gains. Finally, a frequency analysis and a rigorous stability proof of the proposed control structure are given

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

ADRC and Feedforward Hybrid Control System of PMSM

The permanent-magnet synchronous motor (PMSM) is a complex controlled object that is difficult to drive and control. In this study, the vector control strategy is adopted to drive the PMSM. The active disturbance rejection controller is used to achieve the closed-loop control of PMSM, which simplifies the computational complexity. A load torque observer and feedforward compensation component are designed to overcome the PMSM speed fluctuation of the load disturbance. An experimental system based on the DSP board is designed to test the controller performance. The results validate the control algorithm

Nonlinear constrained and saturated control of power electronics and electromechanical systems

Power electronic converters are extensively adopted for the solution of timely issues, such as power quality improvement in industrial plants, energy management in hybrid electrical systems, and control of electrical generators for renewables. Beside nonlinearity, this systems are typically characterized by hard constraints on the control inputs, and sometimes the state variables. In this respect, control laws able to handle input saturation are crucial to formally characterize the systems stability and performance properties. From a practical viewpoint, a proper saturation management allows to extend the systems transient and steady-state operating ranges, improving their reliability and availability. The main topic of this thesis concern saturated control methodologies, based on modern approaches, applied to power electronics and electromechanical systems. The pursued objective is to provide formal results under any saturation scenario, overcoming the drawbacks of the classic solution commonly applied to cope with saturation of power converters, and enhancing performance. For this purpose two main approaches are exploited and extended to deal with power electronic applications: modern anti-windup strategies, providing formal results and systematic design rules for the anti-windup compensator, devoted to handle control saturation, and “one step” saturated feedback design techniques, relying on a suitable characterization of the saturation nonlinearity and less conservative extensions of standard absolute stability theory results. The first part of the thesis is devoted to present and develop a novel general anti-windup scheme, which is then specifically applied to a class of power converters adopted for power quality enhancement in industrial plants. In the second part a polytopic differential inclusion representation of saturation nonlinearity is presented and extended to deal with a class of multiple input power converters, used to manage hybrid electrical energy sources. The third part regards adaptive observers design for robust estimation of the parameters required for high performance control of power systems

Performance investigation of H control and port controlled Hamilton with dissipation based nonlinear control for IPMSM drives

Within the field of electrical drive systems, there has been increasing popularity in the use of permanent magnetic synchronous machines as an execution unit, and the cooperation with high performance control strategy. Industrial engineers and researchers have developed countless applications with PM motors such as wind energy, hybrid vehicle and even in the elevator field. PMSM is a multivariate, nonlinear, time-varying system. Its entire operation is influenced by parameter variation, external load disturbance and unmodelled uncertainty. To eliminate such negative impacts and develop better performing PMSM control system, advanced control algorithms are critical. Therefore, this thesis forces on developing two different control techniques such as mixed-sensitivity based H∞ controller and port controlled Hamilton with dissipation (PCHD) controller to handle the uncertainties of the drives. Former one establishes the controller in terms of frequency domain, successfully converted IPMSM control problem to a standard H∞ based mixed-sensitivity problem by selecting proper weight functions and solving its correspond Ricatti equations. While the latter one realizes the control objective in energy aspects by assigning interconnection and damping matrix for IPMSM system to prove its passivity and ensure global stability. The performances of both controllers for IPMSM drive have been investigated in both simulations and experiments using MATLAB-Simulink and dSPACE DSP board DS1104 for a 5 hp prototype motor. A direct current (DC) machine is coupled with IPMSM shaft to use as dynamic load. It is found that the performances of both controllers are robust at different operating conditions while PCHD exhibits better dynamic performance than that of H∞ control

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications

Nonlinear PI control for variable pitch wind turbine

Wind turbine uses a pitch angle controller to reduce the power captured above the rated wind speed and release the mechanical stress of the drive train. This paper investigates a nonlinear PI (N-PI) based pitch angle controller, by designing an extended-order state and perturbation observer to estimate and compensate unknown time-varying nonlinearities and disturbances. The proposed N-PI does not require the accurate model and uses only one set of PI parameters to provide a global optimal performance under wind speed changes. Simulation verification is based on a simplified two-mass wind turbine model and a detailed aero-elastic wind turbine simulator (FAST), respectively. Simulation results show that the N-PI controller can provide better dynamic performances of power regulation, load stress reduction and actuator usage, comparing with the conventional PI and gain-scheduled PI controller, and better robustness against of model uncertainties than feedback linearization control