Adaptation of motor control to training and disuse : contribution of muscle synergy analysis and movement variability

The well-known degrees of freedom problem originally introduced by Nikolai Bernstein (1967) results from the high abundance of degrees of freedom in the musculoskeletal system. Such abundance in motor control have two sides: i) because it is unlikely that the Central Nervous System controls each degree of freedom independently, the complexity of the control needs to be reduced, and ii) because there are many options to perform a movement, a repetition of a given movement is never the same. It leads to two main topics in motor control and biomechanics: motor coordination and motor variability. The present thesis aimed to understand how motor systems behave and adapt under specific conditions. This thesis comprises three studies that focused on three topics of major interest in the field of sports sciences and medicine: expertise, injury risk and fatigue. The first study (expertise) has focused on the muscle coordination topic to further investigate the effect of expertise on the muscle synergistic organization, which ultimately may represent the underlying neural strategies. Studies 2 (excessive medial knee displacement) and 3 (fatigue) both aimed to better understand its impact on the dynamic local stability. The main findings of the present thesis suggest: 1) there is a great robustness in muscle synergistic organization between swimmers at different levels of expertise (study 1, chapter II), which ultimately indicate that differences in muscle coordination is mainly explained by peripheral adaptations; 2) injury risk factors such as excessive medial knee displacement (study 2, chapter III) and fatigue (study 3, chapter IV) alter the dynamic local stability of the neuromuscular system towards a more unstable state. This change in dynamic local stability represents a loss of adaptability in the neuromuscular system reducing the flexibility to adapt to a perturbation.

Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

AN ENERGY BASED MINIMUM-TIME OPTIMAL CONTROL OF DC-DC CONVERTERS

Time-optimal response is an important and sometimes necessary characteristic of dynamic systems for specific applications. Power converters are widely used in different electrical systems and their dynamic response will affect the whole system. In many electrical systems like microgrids or voltage regulators which supplies sensitive loads fast dynamic response is a must. Minimum time is the fastest converter to compensate the step output reference or load change. Boost converters as one of the wildly used power converters in the electrical systems are aimed to be controlled in optimal time in this study. Linear controllers are not able to provide the optimal response for a boost converter however they are still useful and functional for other applications like reference tracking or stabilization. To obtain the fastest possible response from boost converters, a nonlinear control approach based on the total energy of the system is studied in this research. Total energy of the system considers as the basis for developing the presented method, since it is easy and accurate to measure besides that the total energy of the system represents the actual operating condition of the boost converter. The detailed model of a boost converter is simulated in MATLAB/Simulink to achieve the time optimal response of the boost converter by applying the developed method. The simulation results confirmed the ability of the presented method to secure the time optimal response of the boost converter under four different scenarios.

The study of agricultural non-point source pollution control policy system

As the agricultural non-point source pollution(ANPSP) has become the most significant threat for water environmental deterioration and lake eutrophication in China, more and more scientists and technologists are focusing on the control countermeasure and pollution mechanism of agricultural non-point source pollution. The unreasonable rural production structure and limited scientific management measures are the main reasons for acute ANSPS problems in China. At present, the problem for pollution control is a lack of specific regulations, which affects the government's management efficiency. According to these characteristics and problems, this paper puts forward some corresponding policies. The status of the agricultural non-point source pollution of China is analyzed, and ANSPS prevention and control model is provided based on governance policy, environmental legislation, technical system and subsidy policy. At last, the case analysis of Qiandao Lake is given, and an economic policy is adopted based on its situation.

Advanced 4DT flight guidance and control software system

The work presented in this thesis has been part of a Cranfield University research project. This thesis aims to design a flight control law for large cargo aircraft by using predictive control, which can assure flight motion along the flight path exactly and on time. In particular this work involves the modelling of a Boeing C-17 Globemaster III 6DOF model (used as study case), by using DATCOM and Matlab Simulink software. Then a predictive control algorithm has been developed. The majority of the work is done in a Matlab/Simulink environment. Finally the predictive control algorithm has been applied on the aircraft model and its performances, in tracking given trajectory optimized through a 4DT Research Software, have been evaluated.

Autonomous formation flying: unified control and collision avoidance methods for close manoeuvring spacecraft

The idea of spacecraft formations, flying in tight configurations with maximum baselines of a few hundred meters in low-Earth orbits, has generated widespread interest over the last several years. Nevertheless, controlling the movement of spacecraft in formation poses difficulties, such as in-orbit high-computing demand and collision avoidance capabilities, which escalate as the number of units in the formation is increased and complicated nonlinear effects are imposed to the dynamics, together with uncertainty which may arise from the lack of knowledge of system parameters. These requirements have led to the need of reliable linear and nonlinear controllers in terms of relative and absolute dynamics. The objective of this thesis is, therefore, to introduce new control methods to allow spacecraft in formation, with circular/elliptical reference orbits, to efficiently execute safe autonomous manoeuvres. These controllers distinguish from the bulk of literature in that they merge guidance laws never applied before to spacecraft formation flying and collision avoidance capacities into a single control strategy. For this purpose, three control schemes are presented: linear optimal regulation, linear optimal estimation and adaptive nonlinear control. In general terms, the proposed control approaches command the dynamical performance of one or several followers with respect to a leader to asymptotically track a time-varying nominal trajectory (TVNT), while the threat of collision between the followers is reduced by repelling accelerations obtained from the collision avoidance scheme during the periods of closest proximity. Linear optimal regulation is achieved through a Riccati-based tracking controller. Within this control strategy, the controller provides guidance and tracking toward a desired TVNT, optimizing fuel consumption by Riccati procedure using a non-infinite cost function defined in terms of the desired TVNT, while repelling accelerations generated from the CAS will ensure evasive actions between the elements of the formation. The relative dynamics model, suitable for circular and eccentric low-Earth reference orbits, is based on the Tschauner and Hempel equations, and includes a control input and a nonlinear term corresponding to the CAS repelling accelerations. Linear optimal estimation is built on the forward-in-time separation principle. This controller encompasses two stages: regulation and estimation. The first stage requires the design of a full state feedback controller using the state vector reconstructed by means of the estimator. The second stage requires the design of an additional dynamical system, the estimator, to obtain the states which cannot be measured in order to approximately reconstruct the full state vector. Then, the separation principle states that an observer built for a known input can also be used to estimate the state of the system and to generate the control input. This allows the design of the observer and the feedback independently, by exploiting the advantages of linear quadratic regulator theory, in order to estimate the states of a dynamical system with model and sensor uncertainty. The relative dynamics is described with the linear system used in the previous controller, with a control input and nonlinearities entering via the repelling accelerations from the CAS during collision avoidance events. Moreover, sensor uncertainty is added to the control process by considering carrier-phase differential GPS (CDGPS) velocity measurement error. An adaptive control law capable of delivering superior closed-loop performance when compared to the certainty-equivalence (CE) adaptive controllers is finally presented. A novel noncertainty-equivalence controller based on the Immersion and Invariance paradigm for close-manoeuvring spacecraft formation flying in both circular and elliptical low-Earth reference orbits is introduced. The proposed control scheme achieves stabilization by immersing the plant dynamics into a target dynamical system (or manifold) that captures the desired dynamical behaviour. They key feature of this methodology is the addition of a new term to the classical certainty-equivalence control approach that, in conjunction with the parameter update law, is designed to achieve adaptive stabilization. This parameter has the ultimate task of shaping the manifold into which the adaptive system is immersed. The performance of the controller is proven stable via a Lyapunov-based analysis and Barbalat’s lemma. In order to evaluate the design of the controllers, test cases based on the physical and orbital features of the Prototype Research Instruments and Space Mission Technology Advancement (PRISMA) are implemented, extending the number of elements in the formation into scenarios with reconfigurations and on-orbit position switching in elliptical low-Earth reference orbits. An extensive analysis and comparison of the performance of the controllers in terms of total Δv and fuel consumption, with and without the effects of the CAS, is presented. These results show that the three proposed controllers allow the followers to asymptotically track the desired nominal trajectory and, additionally, those simulations including CAS show an effective decrease of collision risk during the performance of the manoeuvre.

Modelling and PI Control of an Irrigation Canal

The main goal of this paper is to expose and validate a methodology to design efficient automatic controllers for irrigation canals, based on the Saint-Venant model. This model-based methodology enables to design controllers at the design stage (when the canal is not already built). The methodology is applied on an experimental canal located in Portugal. First the full nonlinear PDE model is calibrated, using a single steady-state experiment. The model is then linearized around a functioning point, in order to design linear PI controllers. Two classical control strategies are tested (local upstream control and distant downstream control) and compared on the canal. The experimental results show the effectiveness of the model.

Blade pitch control malfunction simulation in a wind energy conversion system with MPC five-level converter

This paper is on a wind energy conversion system simulation of a transient analysis due to a blade pitch control malfunction. The aim of the transient analysis is the study of the behavior of a back-to-back multiple point clamped five-level full-power converter implemented in a wind energy conversion system equipped with a permanent magnet synchronous generator. An alternate current link connects the system to the grid. The drive train is modeled by a three-mass model in order to simulate the dynamic effect of the wind on the tower. The control strategy is based on fractional-order control. Unbalance voltages in the DC-link capacitors are lessen due to the control strategy, balancing the capacitor banks voltages by a selection of the output voltage vectors. Simulation studies are carried out to evaluate not only the system behavior, but also the quality of the energy injected into the electric grid.

Design of an Efficient Hybrid System for Electricity Production with Supervisory Control

This chapter aims to develop a new method for the economical evaluation of Hybrid Systems for electricity production. The different types of renewable sources are specifically evaluated in the economical performance of the overall equipment. The presented methodology was applied to evaluate the design of a photovoltaic-wind-diesel hybrid system to produce electricity for a community in the neighbourhood of Luanda, Angola. Once the hybrid generator is selected, it is proposed to provide the system with a supervisory control strategy to maximize its operating efficiency.

Rapid Control Prototyping of an L2+ Highway Assist System

Advanced Driver Assistance Systems (ADAS) are proving to have huge potential in road safety, comfort, and efficiency. In recent years, car manufacturers have equipped their high-end vehicles with Level 2 ADAS, which are, according to SAE International, systems that combine both longitudinal and lateral active motion control. These automated driving features, while only available in highway scenarios, appear to be very promising towards the introduction of hands-free driving. However, as they rely only on an on-board sensor suite, their continuative operation may be affected by the current environmental conditions: this prevents certain functionalities such as the automated lane change, other than requiring the driver to keep constantly the hands on the steering wheel. The enabling factor for hands-free highway driving proposed by Mobileye is the integration of high-definition maps, thus leading to the so-called Level 2+. This thesis was carried out during an internship in Maserati's Virtual Engineering team. The activity consisted of the design of an L2+ Highway Assist System following the Rapid Control Prototyping approach, starting from the definition of the requirements up to the real-time implementation and testing on a simulator of the brand new compact SUV Maserati Grecale. The objective was to enhance the current Level 2 highway driving assistance system with hands-free driving capability; for this purpose an Autonomous Lane Change functionality has been designed, proposing a Model Predictive Control-based decision-maker, in charge of assessing both the feasibility and convenience of performing a lane-change maneuver. The result is a Highway Assist System capable of driving the vehicle in a traffic scenario safely and efficiently, never requiring driver intervention.

Hardware-In-The Loop setup and test of an air spring control system

In this work, a Hardware-in-the-loop test bench is designed. The bench is used to test the behaviour of an electronic control unit used in Maserati to control the dynamics of an air spring system. First the mathematical model of the plant has been defined, then the simulation enviroment and the test environment have been set up. The performed tests succesfully highlighted some bugs in the device under test.

Unified control system for three-phase electric drives operating in magnetic saturation region

The research project aims to study and develop control techniques for a generalized three-phase and multi-phase electric drive able to efficiently manage most of the drive types available for traction application. The generalized approach is expanded to both linear and non- linear machines in magnetic saturation region starting from experimental flux characterization and applying the general inductance definition. The algorithm is able to manage fragmented drives powered from different batteries or energy sources and will be able to ensure operability even in case of faults in parts of the system. The algorithm was tested using model-in-the-loop in software environment and then applied on experimental test benches with collaboration of an external company.

Radical chemistry of the catechol/quinone system and its role in the control of lipid peroxidation and melanin biosynthesis

The catechol (1,2-dihydroxybenzene) is a privileged structural motif among natural antioxidants like flavonoids, owing to its reactivity with alkylperoxyl radicals due to the stability of the semiquinone radical. The exploration of the relevance and mechanism of this non-conventional antioxidant chemistry in heterogenous biomimetic systems (aqueous micelles and unilamellar liposomes) is explored for the first time in Chapter 1. Results show antioxidant behaviour that surpasses that of nature’s premiere antioxidant α-tocopherol and relies on the cross-dismutation of alkylperoxyl and hydroperoxyl radicals at the water-lipid interface with regeneration of the catechol function from the oxidized quinone. The design and synthesis of new biomimetic catechol-type antioxidants by conjugation of thiols (e.g. cysteine) with quinones highlighted an unusual 1,6-type regioselectivity, which had been previously reported but never fully rationalized. Owing to its importance both in nature and in the development of new antioxidants, we investigated it in detail in Chapter 2. We could prove the onsetting of a radical-chain mechanism intermediated by thiyl and thiosemiquinone radicals at the basis of the “anomalous nucleophilic addition” of thiols to ortho-quinones, which paves the way to better understanding of the chemistry of such systems. The oxidation of catechols to the corresponding quinones is also a key reaction in the biosynthesis of melanins, mediated by enzyme Tyrosinase.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Fractional Order Modeling and Control of a Flexible Satellite

Researchers have engrossed fractional-order modeling because of its ability to capture phenomena that are nearly impossible to describe owing to its long-term memory and inherited properties. Motivated by the research in fractional modeling, a fractional-order prototype for a flexible satellite whose dynamics are governed by fractional differential equations is proposed for the first time. These relations are derived using fractional attitude dynamic description of rigid body simultaneously coupled with the fractional Lagrange equation that governs the vibration of the appendages. Two attitude controls are designed in the presence of the faults and uncertainties of the system. The first is the fractional-order feedback linearization controller, in which the stability of the internal dynamics of the system is proved. The second is the fractional-order sliding mode control, whose asymptotic stability is demonstrated using the quadratic Lyapunov function. Several nonlinear simulations are implemented to analyze the performance of the proposed controllers.