Non-linear position control for hover and automatic landing of unmanned aerial vehicles

This study presents a disturbance attenuation controller for horizontal position stabilisation for hover and automatic landings of a rotary-wing unmanned aerial vehicle (RUAV) operating close to the landing deck in rough seas. Based on a helicopter model representing aerodynamics during the landing phase, a non-linear state feedback H∞ controller is designed to achieve rapid horizontal position tracking in a gusty environment. Practical constraints including flapping dynamics, servo dynamics and time lag effect are considered. A high-fidelity closed-loop simulation using parameters of the Vario XLC gas-turbine helicopter verifies performance of the proposed horizontal position controller. The proposed controller not only increases the disturbance attenuation capability of the RUAV, but also enables rapid position response when gusts occur. Comparative studies show that the H∞ controller exhibits performance improvement and can be applied to ship/RUAV landing systems.

Voltage unbalance improvement in low voltage residential feeders with rooftop PVs using custom power devices

Voltage unbalance is a major power quality problem in low voltage residential feeders due to the random location and rating of single-phase rooftop photovoltaic cells (PV). In this paper, two different improvement methods based on the application of series (DVR) and parallel (DSTATCOM) custom power devices are investigated to improve the voltage unbalance problem in these feeders. First, based on the load flow analysis carried out in MATLAB, the effectiveness of these two custom power devices is studied vis-à-vis the voltage unbalance reduction in urban and semi-urban/rural feeders containing rooftop PVs. Their effectiveness is studied from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is carried out to investigate their efficacy for different uncertainties of load and PV rating and location in the network. After the numerical analyses, a converter topology and control algorithm is proposed for the DSTATCOM and DVR for balancing the network voltage at their point of common coupling. A state feedback control, based on pole-shift technique, is developed to regulate the voltage in the output of the DSTATCOM and DVR converters such that the voltage balancing is achieved in the network. The dynamic feasibility of voltage unbalance and profile improvement in LV feeders, by the proposed structure and control algorithm for the DSTATCOM and DVR, is verified through detailed PSCAD/EMTDC simulations.

Primary control level of parallel distributed energy resources converters in system of multiple interconnected autonomous microgrids within self-healing networks

To minimise the number of load sheddings in a microgrid (MG) during autonomous operation, islanded neighbour MGs can be interconnected if they are on a self-healing network and an extra generation capacity is available in the distributed energy resources (DER) of one of the MGs. In this way, the total load in the system of interconnected MGs can be shared by all the DERs within those MGs. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and MG levels. In this study, first, a hierarchical control structure is discussed for interconnecting the neighbour autonomous MGs where the introduced primary control level is the main focus of this study. Through the developed primary control level, this study demonstrates how the parallel DERs in the system of multiple interconnected autonomous MGs can properly share the load of the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralised power sharing algorithm based on droop control. DER converters are controlled based on a per-phase technique instead of a conventional direct-quadratic transformation technique. In addition, linear quadratic regulator-based state feedback controllers, which are more stable than conventional proportional integrator controllers, are utilised to prevent instability and weak dynamic performances of the DERs when autonomous MGs are interconnected. The efficacy of the primary control level of the DERs in the system of multiple interconnected autonomous MGs is validated through the PSCAD/EMTDC simulations considering detailed dynamic models of DERs and converters.

Interconnected autonomous microgrids in smart grids with self-healing

In order to minimize the number of load shedding in a Microgrid during autonomous operation, islanded neighbour microgrids can be interconnected if they are on a self-healing network and an extra generation capacity is available in Distributed Energy Resources (DER) in one of the microgrids. In this way, the total load in the system of interconnected microgrids can be shared by all the DERs within these microgrids. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and microgrid levels. In this chapter, first a hierarchical control structure is discussed for interconnecting the neighbour autonomous microgrids where the introduced primary control level is the main focus. Through the developed primary control level, it demonstrates how the parallel DERs in the system of multiple interconnected autonomous microgrids can properly share the load in the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralized power sharing algorithm based on droop control. The switching in the converters is controlled using a linear quadratic regulator based state feedback which is more stable than conventional proportional integrator controllers and this prevents instability among parallel DERs when two microgrids are interconnected. The efficacy of the primary control level of DERs in the system of multiple interconnected autonomous microgrids is validated through simulations considering detailed dynamic models of DERs and converters.

Active vibration suppression of non-linear beams using optimal dynamic inversion

Euler–Bernoulli beams are distributed parameter systems that are governed by a non-linear partial differential equation (PDE) of motion. This paper presents a vibration control approach for such beams that directly utilizes the non-linear PDE of motion, and hence, it is free from approximation errors (such as model reduction, linearization etc.). Two state feedback controllers are presented based on a newly developed optimal dynamic inversion technique which leads to closed-form solutions for the control variable. In one formulation a continuous controller structure is assumed in the spatial domain, whereas in the other approach it is assumed that the control force is applied through a finite number of discrete actuators located at predefined discrete locations in the spatial domain. An implicit finite difference technique with unconditional stability has been used to solve the PDE with control actions. Numerical simulation studies show that the beam vibration can effectively be decreased using either of the two formulations.

Optimal Nonlinear Control and Estimation for a Reusable Launch Vehicle During Reentry Phase

In this paper a nonlinear optimal controller has been designed for aerodynamic control during the reentry phase of the Reusable Launch Vehicle (RLV). The controller has been designed based on a recently developed technique Optimal Dynamic Inversion (ODI). For full state feedback the controller has required full information about the system states. In this work an Extended Kalman filter (EKF) is developed to estimate the states. The vehicle (RLV) has been has been consider as a nonlinear Six-Degree-Of-Freedom (6-DOF) model. The simulation results shows that EKF gives a very good estimation of the states and it is working well with ODI. The resultant trajectories are very similar to those obtained by perfect state feedback using ODI only.

A homotopy approach for stabilizing single-input systems with control structure constraints

A linear state feedback gain vector used in the control of a single input dynamical system may be constrained because of the way feedback is realized. Some examples of feedback realizations which impose constraints on the gain vector are: static output feedback, constant gain feedback for several operating points of a system, and two-controller feedback. We consider a general class of problems of stabilization of single input dynamical systems with such structural constraints and give a numerical method to solve them. Each of these problems is cast into a problem of solving a system of equalities and inequalities. In this formulation, the coefficients of the quadratic and linear factors of the closed-loop characteristic polynomial are the variables. To solve the system of equalities and inequalities, a continuous realization of the gradient projection method and a barrier method are used under the homotopy framework. Our method is illustrated with an example for each class of control structure constraint.

Relationship between the controllability grammian and closed-loop eigenvalues: the single input case

The controllability grammian is important in many control applications. Given a set of closed-loop eigenvalues the corresponding controllability grammian can be obtained by computing the controller which assigns the eigenvalues and then by solving the Lyapunov equation that defines the grammian. The relationship between the controllability grammian, resulting from state feedback, and the closed-loop eigenvalues of a single input linear time invariant (LTI) system is obtained. The proposed methodology does not require the computation of the controller that assigns the specified eigenvalues. The closed-loop system matrix is obtained from the knowledge of the open-loop system matrix, control influence matrix and the specified closed-loop eigenvalues. Knowing the closed-loop system matrix, the grammian is then obtained from the solution of the Lyapunov equation that defines it. Finally the proposed idea is extended to find the state covariance matrix for a specified set of closed-loop eigenvalues (without computing the controller), due to impulsive input in the disturbance channel and to solve the eigenvalue assignment problem for the single input case.

Matrix method for eigenstructure assignment - The multi-input case with application

The eigenvalue and eigenstructure assignment procedure has found application in a wide variety of control problems. In this paper a method for assigning eigenstructure to a linear time invariant multi-input system is proposed. The algorithm determines a matrix that has eigenvalues and eigenvectors at the desired locations. It is obtained from the knowledge of the open-loop system and the desired eigenstructure. Solution of the matrix equation, involving unknown controller gams, open-loop system matrices, and desired eigenvalues and eigenvectors, results hi the state feedback controller. The proposed algorithm requires the closed-loop eigenvalues to be different from those of the open-loop case. This apparent constraint can easily be overcome by a negligible shift in the values. Application of the procedure is illustrated through the offset control of a satellite supported, from an orbiting platform, by a flexible tether.

Matrix method for eigenvalue assignment: The single input case

The eigenvalue assignment/pole placement procedure has found application in a wide variety of control problems. The associated literature is rather extensive with a number of techniques discussed to that end. In this paper a method for assigning eigenvalues to a Linear Time Invariant (LTI) single input system is proposed. The algorithm determines a matrix, which has eigenvalues at the desired locations. It is obtained from the knowledge of the open-loop system and the desired eigenvalues. Solution of the matrix equation, involving unknown controller gains, open-loop system matrices and desired eigenvalues, results in the state feedback controller. The proposed algorithm requires the closed-loop eigenvalues to be different from those of the open-loop case. This apparent constraint is easily overcome by a negligible shift in the values. Two examples are considered to verify the proposed algorithm. The first one pertains to the in-plane libration of a Tethered Satellite System (TSS) while the second is concerned with control of the short period dynamics of a flexible airplane. Finally, the method is extended to determine the Controllability Grammian, corresponding to the specified closed-loop eigenvalues, without computing the controller gains.

Matrix method for eigenstructure assignment - The multi-input case with application

The eigenvalue and eigenstructure assignment procedure has found application in a wide variety of control problems. In this paper a method for assigning eigenstructure to a Linear time invariant multi-input system is proposed. The algorithm determines a matrix that has eigenvalues and eigenvectors at the desired locations. It is obtained from the knowledge of the open-loop system and the desired eigenstructure. solution of the matrix equation, involving unknown controller gains, open-loop system matrices, and desired eigenvalues and eigenvectors, results in the state feedback controller. The proposed algorithm requires the closed-loop eigenvalues to be different from those of the open-loop case. This apparent constraint can easily be overcome by a negligible shift in the values. Application of the procedure is illustrated through the offset control of a satellite supported, from an orbiting platform, by a flexible tether,

Matrix method for eigenvalue assignment: The single input case

The eigenvalue assignment/pole placement procedure has found application in a wide variety of control problems. The associated literature is rather extensive with a number of techniques discussed to that end. In this paper a method for assigning eigenvalues to a Linear Time Invariant (LTI) single input system is proposed. The algorithm determines a matrix, which has eigenvalues at the desired locations. It is obtained from the knowledge of the open-loop system and the desired eigenvalues. Solution of the matrix equation, involving unknown controller gains, open-loop system matrices and desired eigenvalues, results in the state feedback controller. The proposed algorithm requires the closed-loop eigenvalues to be different from those of the open-loop case. This apparent constraint is easily overcome by a negligible shift in the values. Two examples are considered to verify the proposed algorithm. The first one pertains to the in-plane libration of a Tethered Satellite System (TSS) while the second is concerned with control of the short period dynamics of a flexible airplane. Finally, the method is extended to determine the Controllability Grammian, corresponding to the specified closed-loop eigenvalues, without computing the controller gains.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Common-Mode and Differential-Mode Active Damping for PWM Rectifiers

Modern pulse-width-modulated (PWM) rectifiers use LC L filters that can be applied in both the common mode and differential mode to obtain high-performance filtering. Interaction between the passive L and C components in the filter leads to resonance oscillations. These oscillations need to be damped either by the passive damping or active damping. The passive damping increases power loss and can reduce the effectiveness of the filter. Methods of active damping, using control strategy, are lossless while maintaining the effectiveness of the filters. In this paper, an active damping strategy is proposed to damp the oscillations in both line-to-line and line-to-ground. An approach based on pole placement by the state feedback is used to actively damp both the differential-and common-mode filter oscillations. Analytical expressions for the state-feedback controller gains are derived for both continuous and discrete-time model of the filter. Tradeoff in selection of the active damping gain on the lower order power converter harmonics is analyzed using a weighted admittance function. Experimental results on a 10-kVA laboratory prototype PWM rectifier are presented. The results validate the effectiveness of the active damping method, and the tradeoff in the settings of the damping gain.

Síntese evolucionária de circuitos sequenciais inspirada nos princípios da computação quântica.

Esta dissertação investiga a aplicação dos algoritmos evolucionários inspirados na computação quântica na síntese de circuitos sequenciais. Os sistemas digitais sequenciais representam uma classe de circuitos que é capaz de executar operações em uma determinada sequência. Nos circuitos sequenciais, os valores dos sinais de saída dependem não só dos valores dos sinais de entrada como também do estado atual do sistema. Os requisitos cada vez mais exigentes quanto à funcionalidade e ao desempenho dos sistemas digitais exigem projetos cada vez mais eficientes. O projeto destes circuitos, quando executado de forma manual, se tornou demorado e, com isso, a importância das ferramentas para a síntese automática de circuitos cresceu rapidamente. Estas ferramentas conhecidas como ECAD (Electronic Computer-Aided Design) são programas de computador normalmente baseados em heurísticas. Recentemente, os algoritmos evolucionários também começaram a ser utilizados como base para as ferramentas ECAD. Estas aplicações são referenciadas na literatura como eletrônica evolucionária. Os algoritmos mais comumente utilizados na eletrônica evolucionária são os algoritmos genéticos e a programação genética. Este trabalho apresenta um estudo da aplicação dos algoritmos evolucionários inspirados na computação quântica como uma ferramenta para a síntese automática de circuitos sequenciais. Esta classe de algoritmos utiliza os princípios da computação quântica para melhorar o desempenho dos algoritmos evolucionários. Tradicionalmente, o projeto dos circuitos sequenciais é dividido em cinco etapas principais: (i) Especificação da máquina de estados; (ii) Redução de estados; (iii) Atribuição de estados; (iv) Síntese da lógica de controle e (v) Implementação da máquina de estados. O Algoritmo Evolucionário Inspirado na Computação Quântica (AEICQ) proposto neste trabalho é utilizado na etapa de atribuição de estados. A escolha de uma atribuição de estados ótima é tratada na literatura como um problema ainda sem solução. A atribuição de estados escolhida para uma determinada máquina de estados tem um impacto direto na complexidade da sua lógica de controle. Os resultados mostram que as atribuições de estados obtidas pelo AEICQ de fato conduzem à implementação de circuitos de menor complexidade quando comparados com os circuitos gerados a partir de atribuições obtidas por outros métodos. O AEICQ e utilizado também na etapa de síntese da lógica de controle das máquinas de estados. Os circuitos evoluídos pelo AEICQ são otimizados segundo a área ocupada e o atraso de propagação. Estes circuitos são compatíveis com os circuitos obtidos por outros métodos e em alguns casos até mesmo superior em termos de área e de desempenho, sugerindo que existe um potencial de aplicação desta classe de algoritmos no projeto de circuitos eletrônicos.