Optimal Control Design for Multiterminal HVDC

This thesis proposes an optimal-control based design for distributed frequency control in multi-terminal high voltage direct current (MTDC) systems. The current power grid has become overstressed by rapid growth in the demand for electric power and penetration of renewable energy. To address these challenges, MTDC technology has been developed, which has the potential to increase the flexibility and reliability of power transmission in the grid. Several control strategies have been proposed to regulate the MTDC system and its interaction with connected AC systems. However, all the existing control strategies are based on proportional and integral (PI) control with predetermined controller structures. The objective of the thesis is to first determine if existing control structures are optimal, and if improved controller structures can be developed.The thesis proposes a general framework to determine the optimal structure for the control system in MTDC transmission through optimal feedback control. The proposed method is validated and demonstrated using an example of frequency control in a MTDC system connecting five AC areas

Proportional-Integral-Plus Control Strategy of an Intelligent Excavator

This article considers the application of Proportional-Integral-Plus (PIP) control to the Lancaster University Computerised Intelligent Excavator (LUCIE), which is being developed to dig foundation trenches on a building site. Previous work using LUCIE was based on the ubiquitous PI/PID control algorithm, tuned on-line, and implemented in a rather ad hoc manner. By contrast, the present research utilizes new hardware and advanced model-based control system design methods to improve the joint control and so provide smoother, more accurate movement of the excavator arm. In this article, a novel nonlinear simulation model of the system is developed for MATLAB/SIMULINK, allowing for straightforward refinement of the control algorithm and initial evaluation. The PIP controller is compared with a conventionally tuned PID algorithm, with the final designs implemented on-line for the control of dipper angle. The simulated responses and preliminary implementation results demonstrate the feasibility of the approach

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Active sensor fault tolerant output feedback tracking control for wind turbine systems via T-S model

This paper presents a new approach to active sensor fault tolerant tracking control (FTTC) for offshore wind turbine (OWT) described via Takagi–Sugeno (T–S) multiple models. The FTTC strategy is designed in such way that aims to maintain nominal wind turbine controller without any change in both fault and fault-free cases. This is achieved by inserting T–S proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators to be capable to estimate different generators and rotor speed sensors fault for compensation purposes. Due to the dependency of the FTTC strategy on the fault estimation the designed observer has the capability to estimate a wide range of time varying fault signals. Moreover, the robustness of the observer against the difference between the anemometer wind speed measurement and the immeasurable effective wind speed signal has been taken into account. The corrected measurements fed to a T–S fuzzy dynamic output feedback controller (TSDOFC) designed to track the desired trajectory. The stability proof with H∞ performance and D-stability constraints is formulated as a Linear Matrix Inequality (LMI) problem. The strategy is illustrated using a non-linear benchmark system model of a wind turbine offered within a competition led by the companies Mathworks and KK-Electronic

Proportional-integral-plus (PIP) control of the ALSTOM gasifier problem

Although it is able to exploit the full power of optimal state variable feedback within a non-minimum state-space (NMSS) setting, the proportional-integral-plus (PIP) controller is simple to implement and provides a logical extension of conventional proportional-integral and proportional-integral-derivative (PI/PID) controllers, with additional dynamic feedback and input compensators introduced automatically by the NMSS formulation of the problem when the process is of greater than first order or has appreciable pure time delays. The present paper applies the PIP methodology to the ALSTOM benchmark challenge, which takes the form of a highly coupled multi-variable linear model, representing the gasifier system of an integrated gasification combined cycle (IGCC) power plant. In particular, a straightforwardly tuned discrete-time PIP control system based on a reduced-order backward-shift model of the gasifier is found to yield good control of the benchmark, meeting most of the specified performance requirements at three different operating points

Proportional-integral-plus control applications of state-dependent parameter models

This paper considers proportional-integral-plus (PIP) control of non-linear systems defined by state-dependent parameter models, with particular emphasis on three practical demonstrators: a microclimate test chamber, a 1/5th-scale laboratory representation of an intelligent excavator, and a full-scale (commercial) vibrolance system used for ground improvement on a construction site. In each case, the system is represented using a quasi-linear state-dependent parameter (SDP) model structure, in which the parameters are functionally dependent on other variables in the system. The approach yields novel SDP-PIP control algorithms with improved performance and robustness in comparison with conventional linear PIP control. In particular, the new approach better handles the large disturbances and other non-linearities typical in the application areas considered

Proportional-integral-plus (PIP) control of the ALSTOM gasifier problem

Although it is able to exploit the full power of optimal state variable feedback within a non-minimum state-space (NMSS) setting, the proportional-integral-plus (PIP) controller is simple to implement and provides a logical extension of conventional proportional-integral and proportional-integral-derivative (PI/PID) controllers, with additional dynamic feedback and input compensators introduced automatically by the NMSS formulation of the problem when the process is of greater than first order or has appreciable pure time delays. The present paper applies the PIP methodology to the ALSTOM benchmark challenge, which takes the form of a highly coupled multi-variable linear model, representing the gasifier system of an integrated gasification combined cycle (IGCC) power plant. In particular, a straightforwardly tuned discrete-time PIP control system based on a reduced-order backward-shift model of the gasifier is found to yield good control of the benchmark, meeting most of the specified performance requirements at three different operating points

On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes

In this paper, a comparative study is done on the time and frequency domain tuning strategies for fractional order (FO) PID controllers to handle higher order processes. A new fractional order template for reduced parameter modeling of stable minimum/non-minimum phase higher order processes is introduced and its advantage in frequency domain tuning of FOPID controllers is also presented. The time domain optimal tuning of FOPID controllers have also been carried out to handle these higher order processes by performing optimization with various integral performance indices. The paper highlights on the practical control system implementation issues like flexibility of online autotuning, reduced control signal and actuator size, capability of measurement noise filtration, load disturbance suppression, robustness against parameter uncertainties etc. in light of the above tuning methodologies.Comment: 27 pages, 10 figure