A classification of techniques for the compensation of time delayed processes. Part 2: Structurally optimised controllers

Following on from Part 1, Part 2 of the paper considers the use of structurally optimised controllers to compensate time delayed processes

Controllers, observers, and applications thereof

Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed

Local and Central Controllers for Microgrids

The main objective of this thesis is to serve as a guide, so readers are able to learn about microgrids and to design simple controllers for different AC microgrid applications. In addition, this thesis has the objective to provide examples of simulation cases for the hierarchical structure of a basic AC microgrid which can be used as a foundation to build upon, and achieve more complex microgrid structures as well as more sophisticated power-converter control techniques. To achieve these objectives, the modeling of voltage source converters and control design in the z-domain are presented. Moreover, the implementation and transient analysis of the power-converter operating modes are executed through MATLAB/SimulinkTM simulations. Then, an energy management case for the central controller of the AC microgrid is performed utilizing real-time simulation tools, Typhoon HIL software and hardware devices in addition to Texas instruments digital signal processors as local controllers

An on-line equivalent system identification scheme for adaptive control

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance

Design and Implementation of Control Techniques of Power Electronic Interfaces for Photovoltaic Power Systems

The aim of this thesis is to scrutinize and develop four state-of-the-art power electronics converter control techniques utilized in various photovoltaic (PV) power conversion schemes accounting for maximum power extraction and efficiency. First, Cascade Proportional and Integral (PI) Controller-Based Robust Model Reference Adaptive Control (MRAC) of a DC-DC boost converter has been designed and investigated. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection. Second, (P)roportional Gain (R)esonant and Gain Scheduled (P)roportional (PR-P) Controller has been designed and investigated. The aim of this controller is to create a variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm. The proposed control scheme resolved the drawbacks of conventional P&O MPPT method associated with the use of constant perturbation size that leads to a poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update best estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in a P&O algorithm that characterizes the overall system learning-based real time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcome the challenges namely, complexity, computational burden, implantation cost and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.Third, the interleaved buck converter based photovoltaic (PV) emulator current control has been investigated. A proportional-resonant-proportional (PR-P) controller is designed to resolve the drawbacks of conventional PI controllers in terms of phase management which means balancing currents evenly between active phases to avoid thermally stressing and provide optimal ripple cancellation in the presence of parameter uncertainties. The proposed controller shows superior performance in terms of 10 times faster-converging transient response, zero steady-state error with significant reduction in current ripple. Equal load sharing that constitutes the primary concern in multi-phase converters has been achieved with the proposed controller. Implementing of robust control theory involving comprehensive time and frequency domain analysis reveals 13% improvement in the robust stability margin and 12-degree bigger phase toleration with the PR-P controller. Fourth, a symmetrical pole placement Method-based Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller has been designed and investigated. The proposed PR-P controller resolved the issues associated with the use of the PI controller which are tracking repeating control input signal with zero steady-state and mitigating the 3rd order harmonic component injected into the grid for single-phase PV systems. Additionally, the PR-P controller has overcome the drawbacks of frequency detuning in the grid and increase in the magnitude of odd number harmonics in the system that constitute the common concerns in the implementation of conventional PR controller. Moreover, the unprecedented design process based on changing notch filter dynamics with symmetrical pole placement around resonant frequency overcomes the limitations that are essentially complexity and dependency on the precisely modelled system. The verification and validation process of the proposed control schemes has been conducted using MATLAB/Simulink and implementing MATLAB/Simulink/State flow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D and CP4002 Timing and Digital I/O boards

Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems

In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of the conventional P&O MPPT method associated with the use of constant perturbation size that leads to poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update the best-estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in the P&O algorithm that characterizes the overall system learning-based real-time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcomes the challenges namely, complexity, computational burden, implantation cost, and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The proposed control scheme is verified using MATLAB/Simulink by applying comparative analysis with PI-controlled conventional P&O MPPT algorithm. Moreover, the performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor board, DS2004 A/D, and CP4002 Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency