The document presents an experimental validation of an adaptive control scheme for quadrotor MAVs that is robust to uncertainties in mass, center of mass location, and external disturbances. The control scheme uses adaptive techniques to estimate unknown parameters and compensate for their effects. Experimental results show that the adaptive controller more accurately tracks a desired trajectory than a non-adaptive controller, especially when an additional weight is added to introduce parameter uncertainties. The adaptive controller maintains tracking accuracy even in the presence of external disturbances and unknown variations in vehicle parameters.
The paper presents an adaptive trajectory tracking control strategy for quadrotor Micro Aerial Vehicles. The proposed approach, while keeping the typical assumption of an orientation dynamics faster than the translational one, removes that of absence of external disturbances and of perfect symmetry of the vehicle. In particular, the trajectory tracking control law is made adaptive with respect to the presence of external forces and moments, and to the uncertainty of dynamic parameters as the position of the center of mass of the vehicle. A stability analysis as well as numerical simulations are provided to support the control design.
Distributed solution of stochastic optimal control problem on GPUsPantelis Sopasakis
Stochastic optimal control problems arise in many
applications and are, in principle,
large-scale involving up to millions of decision variables. Their
applicability in control applications is often limited by the
availability of algorithms that can solve them efficiently and within
the sampling time of the controlled system.
In this paper we propose a dual accelerated proximal
gradient algorithm which is amenable to parallelization and
demonstrate that its GPU implementation affords high speed-up
values (with respect to a CPU implementation) and greatly outperforms
well-established commercial optimizers such as Gurobi.
The paper presents an adaptive trajectory tracking control strategy for quadrotor Micro Aerial Vehicles. The proposed approach, while keeping the typical assumption of an orientation dynamics faster than the translational one, removes that of absence of external disturbances and of perfect symmetry of the vehicle. In particular, the trajectory tracking control law is made adaptive with respect to the presence of external forces and moments, and to the uncertainty of dynamic parameters as the position of the center of mass of the vehicle. A stability analysis as well as numerical simulations are provided to support the control design.
Distributed solution of stochastic optimal control problem on GPUsPantelis Sopasakis
Stochastic optimal control problems arise in many
applications and are, in principle,
large-scale involving up to millions of decision variables. Their
applicability in control applications is often limited by the
availability of algorithms that can solve them efficiently and within
the sampling time of the controlled system.
In this paper we propose a dual accelerated proximal
gradient algorithm which is amenable to parallelization and
demonstrate that its GPU implementation affords high speed-up
values (with respect to a CPU implementation) and greatly outperforms
well-established commercial optimizers such as Gurobi.
We present a novel modeling
methodology to derive a nonlinear dynamical model which
adequately describes the effect of fuel sloshing on the attitude dynamics of a spacecraft. We model the impulsive thrusters using mixed logic and dynamics leading to a hybrid formulation.
We design a hybrid model predictive control scheme for the
attitude control of a launcher during its long coasting period,
aiming at minimising the actuation count of the thrusters.
A Fast Implicit Gaussian Curvature FilterYuanhao Gong
Minimizing Gaussian curvature is computationally expensive in traditional way. We present a new method that can minimize the Gaussian curvature without computing it. Our filter is 100 times faster than traditional solvers.
A very wide spectrum of optimization problems can be efficiently solved with proximal gradient methods which hinge on the celebrated forward-backward splitting (FBS) schema. But such first-order methods are only effective when low or medium accuracy is required and are known to be rather slow or even impractical for badly conditioned problems. Moreover, the straightforward introduction of second-order (Hessian) information is beset with shortcomings as, typically, at every iteration we need to solve a non-separable optimisation problem. In this talk we will follow a different route to the solution of such optimisation problems. We will recast non-smooth optimisation problems as the minimisation of a real-valued, continuously differentiable function known as the forward-backward envelope. We will then employ a semismooth Newton method to solve the equivalent optimisation problem instead of the original one. We will then apply the proposed semismooth Newton method to L1-regularised least squares (LASSO) problems which is motivated by an an interesting application: recursive compressed sensing. Compressed sensing is a signal processing methodology for the reconstruction of sparsely sampled signals and it offers a new paradigm for sampling signals based on their innovation, that is, the minimum number of coefficients sufficient to accurately represent it in an appropriately selected basis. Compressed sensing leads to a lower sampling rate compared to theories using some fixed basis and has many applications in image processing, medical imaging and MRI, photography, holography, facial recognition, radio astronomy, radar technology and more. The traditional compressed sensing approach is naturally offline, in that it amounts to sparsely sampling and reconstructing a given dataset. Recently, an online algorithm for performing compressed sensing on streaming data was proposed; the scheme uses recursive sampling of the input stream and recursive decompression to accurately estimate stream entries from the acquired noisy measurements. We will see how we can tailor the forward-backward Newton method to solve recursive compressed sensing problems at one tenth of the time required by other algorithms such as ISTA, FISTA, ADMM and interior-point methods (L1LS).
Assessment on how to enhance thermal comfort simulation studies, by adding a human thermal model. A coupled fluid-structure simulation with CFD and Matlab involved.
G. Antonelli and S. Chiaverini and A. Marino, A coordination strategy for multi-robot sampling of dynamic fields, Proceedings 2012 IEEE International Conference on Robotics and Automation, St Paul, MN, pp. 1113--1118, 2012.
We present a novel modeling
methodology to derive a nonlinear dynamical model which
adequately describes the effect of fuel sloshing on the attitude dynamics of a spacecraft. We model the impulsive thrusters using mixed logic and dynamics leading to a hybrid formulation.
We design a hybrid model predictive control scheme for the
attitude control of a launcher during its long coasting period,
aiming at minimising the actuation count of the thrusters.
A Fast Implicit Gaussian Curvature FilterYuanhao Gong
Minimizing Gaussian curvature is computationally expensive in traditional way. We present a new method that can minimize the Gaussian curvature without computing it. Our filter is 100 times faster than traditional solvers.
A very wide spectrum of optimization problems can be efficiently solved with proximal gradient methods which hinge on the celebrated forward-backward splitting (FBS) schema. But such first-order methods are only effective when low or medium accuracy is required and are known to be rather slow or even impractical for badly conditioned problems. Moreover, the straightforward introduction of second-order (Hessian) information is beset with shortcomings as, typically, at every iteration we need to solve a non-separable optimisation problem. In this talk we will follow a different route to the solution of such optimisation problems. We will recast non-smooth optimisation problems as the minimisation of a real-valued, continuously differentiable function known as the forward-backward envelope. We will then employ a semismooth Newton method to solve the equivalent optimisation problem instead of the original one. We will then apply the proposed semismooth Newton method to L1-regularised least squares (LASSO) problems which is motivated by an an interesting application: recursive compressed sensing. Compressed sensing is a signal processing methodology for the reconstruction of sparsely sampled signals and it offers a new paradigm for sampling signals based on their innovation, that is, the minimum number of coefficients sufficient to accurately represent it in an appropriately selected basis. Compressed sensing leads to a lower sampling rate compared to theories using some fixed basis and has many applications in image processing, medical imaging and MRI, photography, holography, facial recognition, radio astronomy, radar technology and more. The traditional compressed sensing approach is naturally offline, in that it amounts to sparsely sampling and reconstructing a given dataset. Recently, an online algorithm for performing compressed sensing on streaming data was proposed; the scheme uses recursive sampling of the input stream and recursive decompression to accurately estimate stream entries from the acquired noisy measurements. We will see how we can tailor the forward-backward Newton method to solve recursive compressed sensing problems at one tenth of the time required by other algorithms such as ISTA, FISTA, ADMM and interior-point methods (L1LS).
Assessment on how to enhance thermal comfort simulation studies, by adding a human thermal model. A coupled fluid-structure simulation with CFD and Matlab involved.
G. Antonelli and S. Chiaverini and A. Marino, A coordination strategy for multi-robot sampling of dynamic fields, Proceedings 2012 IEEE International Conference on Robotics and Automation, St Paul, MN, pp. 1113--1118, 2012.
In this paper, a decentralized control strategy for networked multi-robot systems that allows the tracking of the team centroid and the relative formation is presented. The proposed solution consists of a distributed observer-controller scheme where, based only on local information, each robot
estimates the collective state and tracks the two assigned control variables. We provide a formal stability analysis of the observer-controller scheme and we
relate convergence properties to the topology of the connectivity graph. Experiments are presented to validate the approach.
Inverse kinematics is an active research domain in robotics since several years due to its importance in several robotics application. Among the various approaches, differential inverse kinematics is widely used due to the possibility to real-time implementation. Redundant robotic systems exhibit more degrees of freedom than those strictly required to execute a given end-effector task, in such a case, multiple tasks can be handled simultaneously in, e.g., a task-priority architecture. This paper addresses the systematic extension of the multiple tasks singularity robust solution, also known as Null-space Based Behavioral control, to the case of set-based control tasks, i.e., tasks for which a range, rather than a specific value, is assigned. This is the case for several tasks such as, for example, mechanical joint limits of robotic arm as well as obstacle avoidance for any kind of robots. Numerical validation are provided to support the solution proposed.
F. Arrichiello and G. Antonelli and A.P. Aguiar and A. Pascoal, Observability metrics for the relative localization of AUVs based on range and depth measurements: theory and experiments, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Franscisco, CA, pp. 3166--3171, 2011.
G. Antonelli and F. Arrichiello and F. Caccavale and A. Marino, A decentralized controller-observer scheme for weighted centroid tracking, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Franscisco, CA, pp. 2778--2783, 2011.
A. Marino and G. Antonelli and A.P. Aguiar and A. Pascoal, Multi-robot harbor patrolling: a probabilistic approach, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Algarve, PT, pp. , 2012.
Coverage of a given area by means of coordinated autonomous robots is a mission
required in several applications such as, for example, patrolling, monitoring or
environmental sampling. From a mathematical perspective, this can often be
modeled as the need to estimate a scalar field, eventually time varying as in
the security applications. In this paper, the problem is addressed for the
challenging underwater scenario, where localization and communication pose
additional constraints. The solution exploits the appealing properties of the
Voronoi partition of a convex set within a probabilistic framework. In addition,
the algorithm is totally distributed and characterized by a strong engineering
perspective allowing the handling of asynchronous communication or possible loss
or adjunct of vehicles. Beyond the test in dozen of numerical case studies, the
algorithm has been validated by a challenging underwater test in 3 dimension
involving two Autonomous Underwater Vehicles (AUVs). The experiments were run in
the La Spezia harbor, in Italy, in February 2012 as demo
of the European project \co3auvs.
CELEBRATION 2000 (3rd Deployment) & ALP 2002Generation of a 3D-Model of the ...gigax2
CELEBRATION 2000 and ALP 2002 are two large 3-D-refraction campaigns which target the crustal and upper mantle structure in Central Europe. This study is based on these seismic data sets and concentrates on the area of the Eastern Alps region and the surrounding forelands and basins. The tectonic setting of the investigation area is characterized by a continent-continent-collision of the Adriatic and European plate and subsequently by a lateral extrusion eastwards to the Pannonian basin. (Fig. Xxx)
The 3-D-model is described by a tomographic solution of the crust and depths and velocities for the Moho. In both cases, lateral resolution is 20 km on a 31x34-horizontal grid. The vertical distance of the depth nodes for the crust is 1 km down to 20 km depth and larger intervals from there on.
The merged datasets of ALP2002 and of the 3rd deployment of CELEBRATION 2000 result in approximately 78000 seismic traces. Signal detection (STA/LTA) and stacking techniques (offset bins) were applied to the data in order to guarantee a reliable interpretation even in areas of degraded seismic energy transmission. Refractors like the Moho are modeled by a delaytime approach at a first step. The following depth conversion will make use of the velocity model of the crust. These techniques will be presented at this meeting on Friday .
Modelling the crust
To obtain the tomographic image of the crust, for each gridpoint with sufficient coverage CMP-sorted traces over all azimuths were stacked. The stack is treated as a 1D-traveltime-curve, subsequently picked (Pg only !) and inverted. On the expense of detailed images of shallow layers, the stacking process enhances Pg at large (over-critical) offsets, so that the average penetration depth is 16 km, with a maximum of over 40 km.
Platoon Control of Nonholonomic Robots using Quintic Bezier SplinesKaustav Mondal
In this project, quintic polynomials were used to perform platooning in nonholonomic robots. Both hardware and simulations results have been presented.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A walk through the intersection between machine learning and mechanistic mode...JuanPabloCarbajal3
Talk at EURECOM, France.
It overviews regression in several of its forms: regularized, constrained, and mixed. It builds the bridge between machine learning and dynamical models.
PROPAN - Potential Flow Code for Foils and Rotors: PROPAN is short for Propeller Panel Method. PROPAN is a panel code for the calculation of steady and unsteady potential flow around foils, open and ducted propellers, and wind and marine current turbines. PROPAN was developed by MARETEC (Marine and Environmental Technology Research Centre) at Instituto Superior Técnico (IST) which belongs to Lisbon University.
In this work we discuss how to compute KLE with complexity O(k n log n), how to approximate large covariance matrices (in H-matrix format), how to use the Lanczos method.
We solve elliptic PDE with uncertain coefficients. We apply Karhunen-Loeve expansion to separate stochastic part from spatial part. The corresponding eigenvalue problem with covariance function is solved via the Hierarchical Matrix technique. We also demonstrate how low-rank tensor method can be applied for high-dimensional problems (e.g., to compute higher order statistical moments) . We provide explicit formulas to compute statistical moments of order k with linear complexity.
Dynamic modelling and optimal controlscheme of wheel inverted pendulum for mo...ijctcm
Unstable wheel inverted pendulum is modelled and controlled deploying Kane’s method and optimal
partial-state PID control scheme. A correct derivation of nonlinear mathematical model of a wheel inverted
pendulum is obtained using a proper definition of the geometric context of active and inertia forces. Then
the model is decoupled to two linear subsystems namely balancing and heading subsystems. Afterward
partial-state PID controller is proposed and formulated to quadratic optimal regulation tuning method. It
enables partial-state PID to be optimally tuned and guarantees a satisfactory level of states error and a
realistic utilization of torque energy. Simulation and numerical analyses are carried out to analyse
system’s stability and to determine the performance of the proposed controller for mobile wheel inverted
pendulum application.
Experience the thrill of Progressive Puzzle Adventures, like Scavenger Hunt Games and Escape Room Activities combined Solve Treasure Hunt Puzzles online.
From the Editor's Desk: 115th Father's day Celebration - When we see Father's day in Hindu context, Nanda Baba is the most vivid figure which comes to the mind. Nanda Baba who was the foster father of Lord Krishna is known to provide love, care and affection to Lord Krishna and Balarama along with his wife Yashoda; Letter’s to the Editor: Mother's Day - Mother is a precious life for their children. Mother is life breath for her children. Mother's lap is the world happiness whose debt can never be paid.
Meet Dinah Mattingly – Larry Bird’s Partner in Life and Loveget joys
Get an intimate look at Dinah Mattingly’s life alongside NBA icon Larry Bird. From their humble beginnings to their life today, discover the love and partnership that have defined their relationship.
As a film director, I have always been awestruck by the magic of animation. Animation, a medium once considered solely for the amusement of children, has undergone a significant transformation over the years. Its evolution from a rudimentary form of entertainment to a sophisticated form of storytelling has stirred my creativity and expanded my vision, offering limitless possibilities in the realm of cinematic storytelling.
From Slave to Scourge: The Existential Choice of Django Unchained. The Philos...Rodney Thomas Jr
#SSAPhilosophy #DjangoUnchained #DjangoFreeman #ExistentialPhilosophy #Freedom #Identity #Justice #Courage #Rebellion #Transformation
Welcome to SSA Philosophy, your ultimate destination for diving deep into the profound philosophies of iconic characters from video games, movies, and TV shows. In this episode, we explore the powerful journey and existential philosophy of Django Freeman from Quentin Tarantino’s masterful film, "Django Unchained," in our video titled, "From Slave to Scourge: The Existential Choice of Django Unchained. The Philosophy of Django Freeman!"
From Slave to Scourge: The Existential Choice of Django Unchained – The Philosophy of Django Freeman!
Join me as we delve into the existential philosophy of Django Freeman, uncovering the profound lessons and timeless wisdom his character offers. Through his story, we find inspiration in the power of choice, the quest for justice, and the courage to defy oppression. Django Freeman’s philosophy is a testament to the human spirit’s unyielding drive for freedom and justice.
Don’t forget to like, comment, and subscribe to SSA Philosophy for more in-depth explorations of the philosophies behind your favorite characters. Hit the notification bell to stay updated on our latest videos. Let’s discover the principles that shape these icons and the profound lessons they offer.
Django Freeman’s story is one of the most compelling narratives of transformation and empowerment in cinema. A former slave turned relentless bounty hunter, Django’s journey is not just a physical liberation but an existential quest for identity, justice, and retribution. This video delves into the core philosophical elements that define Django’s character and the profound choices he makes throughout his journey.
Link to video: https://youtu.be/GszqrXk38qk
In the vast landscape of cinema, stories have been told, retold, and reimagined in countless ways. At the heart of this narrative evolution lies the concept of a "remake". A successful remake allows us to revisit cherished tales through a fresh lens, often reflecting a different era's perspective or harnessing the power of advanced technology. Yet, the question remains, what makes a remake successful? Today, we will delve deeper into this subject, identifying the key ingredients that contribute to the success of a remake.
Skeem Saam in June 2024 available on ForumIsaac More
Monday, June 3, 2024 - Episode 241: Sergeant Rathebe nabs a top scammer in Turfloop. Meikie is furious at her uncle's reaction to the truth about Ntswaki.
Tuesday, June 4, 2024 - Episode 242: Babeile uncovers the truth behind Rathebe’s latest actions. Leeto's announcement shocks his employees, and Ntswaki’s ordeal haunts her family.
Wednesday, June 5, 2024 - Episode 243: Rathebe blocks Babeile from investigating further. Melita warns Eunice to stay clear of Mr. Kgomo.
Thursday, June 6, 2024 - Episode 244: Tbose surrenders to the police while an intruder meddles in his affairs. Rathebe's secret mission faces a setback.
Friday, June 7, 2024 - Episode 245: Rathebe’s antics reach Kganyago. Tbose dodges a bullet, but a nightmare looms. Mr. Kgomo accuses Melita of witchcraft.
Monday, June 10, 2024 - Episode 246: Ntswaki struggles on her first day back at school. Babeile is stunned by Rathebe’s romance with Bullet Mabuza.
Tuesday, June 11, 2024 - Episode 247: An unexpected turn halts Rathebe’s investigation. The press discovers Mr. Kgomo’s affair with a young employee.
Wednesday, June 12, 2024 - Episode 248: Rathebe chases a criminal, resorting to gunfire. Turf High is rife with tension and transfer threats.
Thursday, June 13, 2024 - Episode 249: Rathebe traps Kganyago. John warns Toby to stop harassing Ntswaki.
Friday, June 14, 2024 - Episode 250: Babeile is cleared to investigate Rathebe. Melita gains Mr. Kgomo’s trust, and Jacobeth devises a financial solution.
Monday, June 17, 2024 - Episode 251: Rathebe feels the pressure as Babeile closes in. Mr. Kgomo and Eunice clash. Jacobeth risks her safety in pursuit of Kganyago.
Tuesday, June 18, 2024 - Episode 252: Bullet Mabuza retaliates against Jacobeth. Pitsi inadvertently reveals his parents’ plans. Nkosi is shocked by Khwezi’s decision on LJ’s future.
Wednesday, June 19, 2024 - Episode 253: Jacobeth is ensnared in deceit. Evelyn is stressed over Toby’s case, and Letetswe reveals shocking academic results.
Thursday, June 20, 2024 - Episode 254: Elizabeth learns Jacobeth is in Mpumalanga. Kganyago's past is exposed, and Lehasa discovers his son is in KZN.
Friday, June 21, 2024 - Episode 255: Elizabeth confirms Jacobeth’s dubious activities in Mpumalanga. Rathebe lies about her relationship with Bullet, and Jacobeth faces theft accusations.
Monday, June 24, 2024 - Episode 256: Rathebe spies on Kganyago. Lehasa plans to retrieve his son from KZN, fearing what awaits.
Tuesday, June 25, 2024 - Episode 257: MaNtuli fears for Kwaito’s safety in Mpumalanga. Mr. Kgomo and Melita reconcile.
Wednesday, June 26, 2024 - Episode 258: Kganyago makes a bold escape. Elizabeth receives a shocking message from Kwaito. Mrs. Khoza defends her husband against scam accusations.
Thursday, June 27, 2024 - Episode 259: Babeile's skillful arrest changes the game. Tbose and Kwaito face a hostage crisis.
Friday, June 28, 2024 - Episode 260: Two women face the reality of being scammed. Turf is rocked by breaking
Young Tom Selleck: A Journey Through His Early Years and Rise to Stardomgreendigital
Introduction
When one thinks of Hollywood legends, Tom Selleck is a name that comes to mind. Known for his charming smile, rugged good looks. and the iconic mustache that has become synonymous with his persona. Tom Selleck has had a prolific career spanning decades. But, the journey of young Tom Selleck, from his early years to becoming a household name. is a story filled with determination, talent, and a touch of luck. This article delves into young Tom Selleck's life, background, early struggles. and pivotal moments that led to his rise in Hollywood.
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Early Life and Background
Family Roots and Childhood
Thomas William Selleck was born in Detroit, Michigan, on January 29, 1945. He was the second of four children in a close-knit family. His father, Robert Dean Selleck, was a real estate investor and executive. while his mother, Martha Selleck, was a homemaker. The Selleck family relocated to Sherman Oaks, California. when Tom was a child, setting the stage for his future in the entertainment industry.
Education and Early Interests
Growing up, young Tom Selleck was an active and athletic child. He attended Grant High School in Van Nuys, California. where he excelled in sports, particularly basketball. His tall and athletic build made him a standout player, and he earned a basketball scholarship to the University of Southern California (U.S.C.). While at U.S.C., Selleck studied business administration. but his interests shifted toward acting.
Discovery of Acting Passion
Tom Selleck's journey into acting was serendipitous. During his time at U.S.C., a drama coach encouraged him to try acting. This nudge led him to join the Hills Playhouse, where he began honing his craft. Transitioning from an aspiring athlete to an actor took time. but young Tom Selleck became drawn to the performance world.
Early Career Struggles
Breaking Into the Industry
The path to stardom was a challenging one for young Tom Selleck. Like many aspiring actors, he faced many rejections and struggled to find steady work. A series of minor roles and guest appearances on television shows marked his early career. In 1965, he debuted on the syndicated show "The Dating Game." which gave him some exposure but did not lead to immediate success.
The Commercial Breakthrough
During the late 1960s and early 1970s, Selleck began appearing in television commercials. His rugged good looks and charismatic presence made him a popular brand choice. He starred in advertisements for Pepsi-Cola, Revlon, and Close-Up toothpaste. These commercials provided financial stability and helped him gain visibility in the industry.
Struggling Actor in Hollywood
Despite his success in commercials. breaking into large acting roles remained a challenge for young Tom Selleck. He auditioned and took on small parts in T.V. shows and movies. Some of his early television appearances included roles in popular series like Lancer, The F.B.I., and Bracken's World. But, it would take a
240529_Teleprotection Global Market Report 2024.pdfMadhura TBRC
The teleprotection market size has grown
exponentially in recent years. It will grow from
$21.92 billion in 2023 to $28.11 billion in 2024 at a
compound annual growth rate (CAGR) of 28.2%. The
teleprotection market size is expected to see
exponential growth in the next few years. It will grow
to $70.77 billion in 2028 at a compound annual
growth rate (CAGR) of 26.0%.
Meet Crazyjamjam - A TikTok Sensation | Blog EternalBlog Eternal
Crazyjamjam, the TikTok star everyone's talking about! Uncover her secrets to success, viral trends, and more in this exclusive feature on Blog Eternal.
Source: https://blogeternal.com/celebrity/crazyjamjam-leaks/
Tom Selleck Net Worth: A Comprehensive Analysisgreendigital
Over several decades, Tom Selleck, a name synonymous with charisma. From his iconic role as Thomas Magnum in the television series "Magnum, P.I." to his enduring presence in "Blue Bloods," Selleck has captivated audiences with his versatility and charm. As a result, "Tom Selleck net worth" has become a topic of great interest among fans. and financial enthusiasts alike. This article delves deep into Tom Selleck's wealth, exploring his career, assets, endorsements. and business ventures that contribute to his impressive economic standing.
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Early Life and Career Beginnings
The Foundation of Tom Selleck's Wealth
Born on January 29, 1945, in Detroit, Michigan, Tom Selleck grew up in Sherman Oaks, California. His journey towards building a large net worth began with humble origins. , Selleck pursued a business administration degree at the University of Southern California (USC) on a basketball scholarship. But, his interest shifted towards acting. leading him to study at the Hills Playhouse under Milton Katselas.
Minor roles in television and films marked Selleck's early career. He appeared in commercials and took on small parts in T.V. series such as "The Dating Game" and "Lancer." These initial steps, although modest. laid the groundwork for his future success and the growth of Tom Selleck net worth. Breakthrough with "Magnum, P.I."
The Role that Defined Tom Selleck's Career
Tom Selleck's breakthrough came with the role of Thomas Magnum in the CBS television series "Magnum, P.I." (1980-1988). This role made him a household name and boosted his net worth. The series' popularity resulted in Selleck earning large salaries. leading to financial stability and increased recognition in Hollywood.
"Magnum P.I." garnered high ratings and critical acclaim during its run. Selleck's portrayal of the charming and resourceful private investigator resonated with audiences. making him one of the most beloved television actors of the 1980s. The success of "Magnum P.I." played a pivotal role in shaping Tom Selleck net worth, establishing him as a major star.
Film Career and Diversification
Expanding Tom Selleck's Financial Portfolio
While "Magnum, P.I." was a cornerstone of Selleck's career, he did not limit himself to television. He ventured into films, further enhancing Tom Selleck net worth. His filmography includes notable movies such as "Three Men and a Baby" (1987). which became the highest-grossing film of the year, and its sequel, "Three Men and a Little Lady" (1990). These box office successes contributed to his wealth.
Selleck's versatility allowed him to transition between genres. from comedies like "Mr. Baseball" (1992) to westerns such as "Quigley Down Under" (1990). This diversification showcased his acting range. and provided many income streams, reinforcing Tom Selleck net worth.
Television Resurgence with "Blue Bloods"
Sustaining Wealth through Consistent Success
In 2010, Tom Selleck began starring as Frank Reagan i
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Create a Seamless Viewing Experience with Your Own Custom OTT Player.pdfGenny Knight
As the popularity of online streaming continues to rise, the significance of providing outstanding viewing experiences cannot be emphasized enough. Tailored OTT players present a robust solution for service providers aiming to enhance their offerings and engage audiences in a competitive market. Through embracing customization, companies can craft immersive, individualized experiences that effectively hold viewers' attention, entertain them, and encourage repeat usage.
Maximizing Your Streaming Experience with XCIPTV- Tips for 2024.pdfXtreame HDTV
In today’s digital age, streaming services have become an integral part of our entertainment lives. Among the myriad of options available, XCIPTV stands out as a premier choice for those seeking seamless, high-quality streaming. This comprehensive guide will delve into the features, benefits, and user experience of XCIPTV, illustrating why it is a top contender in the IPTV industry.
Panchayat Season 3 - Official Trailer.pdfSuleman Rana
The dearest series "Panchayat" is set to make a victorious return with its third season, and the fervor is discernible. The authority trailer, delivered on May 28, guarantees one more enamoring venture through the country heartland of India.
Jitendra Kumar keeps on sparkling as Abhishek Tripathi, the city-reared engineer who ends up functioning as the secretary of the Panchayat office in the curious town of Phulera. His nuanced depiction of a young fellow exploring the difficulties of country life while endeavoring to adjust to his new environmental factors has earned far and wide recognition.
Neena Gupta and Raghubir Yadav return as Manju Devi and Brij Bhushan Dubey, separately. Their dynamic science and immaculate acting rejuvenate the hardships of town administration. Gupta's depiction of the town Pradhan with an ever-evolving outlook, matched with Yadav's carefully prepared exhibition, adds profundity and credibility to the story.
New Difficulties and Experiences
The trailer indicates new difficulties anticipating the characters, as Abhishek keeps on wrestling with his part in the town and his yearnings for a superior future. The series has reliably offset humor with social editorial, and Season 3 looks ready to dig much more profound into the intricacies of rustic organization and self-awareness.
Watchers can hope to see a greater amount of the enchanting and particular residents who have become fan top picks. Their connections and the one of a kind cut of-life situations give a reviving and interesting portrayal of provincial India, featuring the two its appeal and its difficulties.
A Mix of Humor and Heart
One of the signs of "Panchayat" is its capacity to mix humor with sincere narrating. The trailer features minutes that guarantee to convey giggles, as well as scenes that pull at the heartstrings. This equilibrium has been a critical calculate the show's prosperity, resounding with crowds across different socioeconomics.
Creation Greatness
The creation quality remaining parts first rate, with the beautiful setting of Phulera town filling in as a scenery that upgrades the narrating. The meticulousness in portraying provincial life, joined with sharp composition and solid exhibitions, guarantees that "Panchayat" keeps on hanging out in the packed web series scene.
Expectation and Delivery
As the delivery date draws near, expectation for "Panchayat" Season 3 is at a record-breaking high. The authority trailer has previously created critical buzz, with fans enthusiastically anticipating the continuation of Abhishek Tripathi's excursion and the new undertakings that lie ahead in Phulera.
All in all, the authority trailer for "Panchayat" Season 3 recommends that watchers are in for another drawing in and engaging ride. Yet again with its charming characters, convincing story, and ideal mix of humor and show, the new season is set to enamor crowds. Write in your schedules and prepare to get back to the endearing universe of "Panchayat."
Scandal! Teasers June 2024 on etv Forum.co.zaIsaac More
Monday, 3 June 2024
Episode 47
A friend is compelled to expose a manipulative scheme to prevent another from making a grave mistake. In a frantic bid to save Jojo, Phakamile agrees to a meeting that unbeknownst to her, will seal her fate.
Tuesday, 4 June 2024
Episode 48
A mother, with her son's best interests at heart, finds him unready to heed her advice. Motshabi finds herself in an unmanageable situation, sinking fast like in quicksand.
Wednesday, 5 June 2024
Episode 49
A woman fabricates a diabolical lie to cover up an indiscretion. Overwhelmed by guilt, she makes a spontaneous confession that could be devastating to another heart.
Thursday, 6 June 2024
Episode 50
Linda unwittingly discloses damning information. Nhlamulo and Vuvu try to guide their friend towards the right decision.
Friday, 7 June 2024
Episode 51
Jojo's life continues to spiral out of control. Dintle weaves a web of lies to conceal that she is not as successful as everyone believes.
Monday, 10 June 2024
Episode 52
A heated confrontation between lovers leads to a devastating admission of guilt. Dintle's desperation takes a new turn, leaving her with dwindling options.
Tuesday, 11 June 2024
Episode 53
Unable to resort to violence, Taps issues a verbal threat, leaving Mdala unsettled. A sister must explain her life choices to regain her brother's trust.
Wednesday, 12 June 2024
Episode 54
Winnie makes a very troubling discovery. Taps follows through on his threat, leaving a woman reeling. Layla, oblivious to the truth, offers an incentive.
Thursday, 13 June 2024
Episode 55
A nosy relative arrives just in time to thwart a man's fatal decision. Dintle manipulates Khanyi to tug at Mo's heartstrings and get what she wants.
Friday, 14 June 2024
Episode 56
Tlhogi is shocked by Mdala's reaction following the revelation of their indiscretion. Jojo is in disbelief when the punishment for his crime is revealed.
Monday, 17 June 2024
Episode 57
A woman reprimands another to stay in her lane, leading to a damning revelation. A man decides to leave his broken life behind.
Tuesday, 18 June 2024
Episode 58
Nhlamulo learns that due to his actions, his worst fears have come true. Caiphus' extravagant promises to suppliers get him into trouble with Ndu.
Wednesday, 19 June 2024
Episode 59
A woman manages to kill two birds with one stone. Business doom looms over Chillax. A sobering incident makes a woman realize how far she's fallen.
Thursday, 20 June 2024
Episode 60
Taps' offer to help Nhlamulo comes with hidden motives. Caiphus' new ideas for Chillax have MaHilda excited. A blast from the past recognizes Dintle, not for her newfound fame.
Friday, 21 June 2024
Episode 61
Taps is hungry for revenge and finds a rope to hang Mdala with. Chillax's new job opportunity elicits mixed reactions from the public. Roommates' initial meeting starts off on the wrong foot.
Monday, 24 June 2024
Episode 62
Taps seizes new information and recruits someone on the inside. Mary's new job
1. Experimental validation of a new adaptive
control scheme for quadrotors MAVs
Gianluca Antonelli† , Elisabetta Cataldi† ,
Paolo Robuffo Giordano⊕ , Stefano Chiaverini† , Antonio Franchi≀
† University
of Cassino and Southern Lazio, Italy
http://webuser.unicas.it/lai/robotica
⊕ CNRS at IRISA and Inria Bretagne Atlantique, France
http://www.irisa.fr/lagadic
≀ Max Planck Institute for Biol. Cybernetics, Germany
http://www.kyb.mpg.de/research/dep/bu/hri/
IROS 2013
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
2. Trajectory tracking control for quadrotor
Adaptive with respect to
uncertainty in total mass
uncertainty in Center Of Mass (CoM)
presence of 6-DOF external disturbances
Assumption: closed-loop orientation dynamics faster than
translational one
Stability analysis & numerical simulations1
Experimental results
1
Antonelli, Arrichiello, Chiaverini, Robuffo Giordano, “Adaptive
trajectory tracking for quadrotor MAVs in presence of parameter
uncertainties and external disturbances”, AIM 2013
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
3. Kinematics
body-fixed u, surge
xb
p, roll
Ob
q, pitch
η1
r, yaw
yb
v, sway
zb
w, heave
η1 =
η2 =
O
x
earth-fixed
x y z
φ θ ψ
ν 1 = RB η 1
I ˙
˙
ν 2 = T (η 2 )η 2
y
z
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
T
T
4. Dynamics
Mathematical model expressed in body-fixed frame
˙
M ν + C(ν)ν + τ W + g(RB ) = τ ,
I
beyond the common terms, we model
τW =
γ W ∈ R6 external disturbance
RB O 3×3
I
γW
O 3×3 RB
I
constant in the inertial frame (wind)
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
5. Dynamics -2Exploiting the linearity in the parameters
˙
Φ(ν, ν, RB )γ = τ
I
and rewriting with respect to the inertial frame while separating the
xy dynamics from z:
˙ ¨
Φxy (η, η, η )
γ = RI τ 1
B
˙ ¨
φz (η, η, η )
with γ ∈ R16 :
mass (1 parameter)
first moment of inertia (3 p.)
inertia tensor (6 p.)
τ =
τ1
τ2
external disturbance (6 p.)
Antonelli Cataldi Robuffo Chiaverini Franchi
0
0
Z
=
K
M
N
Tokyo, 5 November 2013
6. Thrust
Assuming CoM coincident with Ob
f2
2
τt,3
l
f3
ωt,2
f4
yb z
b
ωt,4
τt,4
4
τt,2
f1
Ob
ωt,3
3
2
fi = bωt,i
ωt,1
xb
1
O
y
τt,1
x
z
Antonelli Cataldi Robuffo Chiaverini Franchi
2
τt,i = dωt,i
0
0
τ1 = 4
i=1
fi
l(f2 − f4 )
l(f1 − f3 )
τ2 =
−τt,1 + τt,2 − τt,3 + τt,4
Tokyo, 5 November 2013
7. Mapping from the angular velocities to the force-torques
Assuming CoM of coordinates r C :
2
ωt,1
Z
2
K
ωt,2
= Bv
M
ω 2
t,3
2
N
ωt,4
with
b
b
b
b
0
b(l + rC,y )
0
−b(l − rC,y )
Bv =
b(l + rC,x )
0
−b(l − rC,x )
0
−d
d
−d
d
CoM influences the mapping from thrust generated from the
motors to the vehicle forces/moments
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
8. Inverse mapping
Any controller determines a control action Zc Kc Mc Nc
projected onto the motor input u ∈ R4
Zc
Kc
u = B −1
v
Mc
Nc
where B −1 ∈ R4×4 is
v
B −1
v
l − rC,x
4bl
l − r
C,y
4bl
= l + r
C,x
4bl
l + rC,y
4bl
0
1
2bl
0
1
−
2bl
Antonelli Cataldi Robuffo Chiaverini Franchi
1
2bl
0
1
−
2bl
0
l − rC,x
−
4dl
l − rC,y
4dl
l + rC,x
−
4dl
l + rC,y
4dl
Tokyo, 5 November 2013
T
further
9. Current inverse mapping
ˆ
When the CoM position estimate r C is affected
mapping becomes
1
0
Z
Zc
rC,y
˜
1
K
Kc
= B v | B −1
2
ˆ
r C v r C Mc = rC,x
M
˜
0
2
N
Nc
0
0
by an error, the real
0
b˜C,y Zc
r
0
2d Kc
b˜C,x Mc
r
1 −
2d
Nc
0
1
0
wrong CoM estimate ⇒ a coupling from altitude and yaw control
actions onto roll and pitch dynamics
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
10. Controller block diagram
Z
K
M
N
η 1d
ψd
Zc
pos φd , θd
Kc
Mc B −1
v
or
Nc
u
motors
2
wt,i
τW
η
Bv
plant
Classical MAV control architecture with adaptation wrt parameters
and compensation of the CoM position
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
11. Altitude controller
error
z = zd − z ∈ R
˜
˙
s z = z + λz z ∈ R
˜
˜
full version
1
ˆ
(φ γ + kvz sz )
cos φ cos θ z
˙
γ = K −1 φT sz
ˆ
γ,z z
Z =
ˆ
with γ ∈ R16
reduced version
1
(ˆz + kvz sz )
γ
cos φ cos θ
−1
= kγ,z sz
Z =
˙
γz
ˆ
ˆ
with γ z ∈ R1
the reduced version designed to compensate only for persistent
terms ⇒ null steady state error wrt a minimal set of parameters!
(λz > 0, kvz > 0, K γ,z > O, kγ,z > 0)
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
12. Horizontal controller
error
T
˜
η xy = xd − x yd − y ∈ R2
˙
˜
sxy = η xy + λxy η xy ∈ R2
˜
full version
reduced version
virtual input solutions of:
virtual input solutions of:
1
cφ sθ
ˆ
Rz (Φxy γ + kv,xy sxy )
=
−sφ
Z
˙
γ = K −1 ΦT sxy
ˆ
γ,xy xy
ˆ
with γ ∈ R16
1
cφ sθ
ˆ
Rz γ xy + kv,xy sxy
=
−sφ
Z
−1
˙
γ xy = kγ,xy sxy
ˆ
ˆ
with γ xy ∈ R2
again: the reduced version compensates only for persistent terms
⇒ null steady state error wrt a minimal set of parameters!
(λxy > 0, kv,xy > 0, K γ,xy > O, kγ,xy > 0)
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
13. Orientation controller
The inputs are the desired roll, pitch and yaw
The commanded forces map onto the real ones according to
K
=
M
N
=
=
b˜C,y
rC,y
˜
r
Zc +
Nc
2
2d
b˜C,x
rC,x
˜
r
Zc −
Nc
Mc +
2
2d
Nc
Kc +
˜
Neither the altitude nor the yaw control loop are affected by rC , thus both Zc
and Nc convergence to a steady state value
Roll and pitch control can be designed by considering the estimation error as
an external, constant, disturbance:
K
=
M
=
1
b
Zc + Nc rC,y
˜
2
d
1
b
Mc +
Zc − Nc rC,x
˜
2
d
Kc +
The disturbance value is unknown and its effect may be compensated by
resorting to several adaptive control laws well known in the literature
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
14. CoM estimation
PD control for roll and pitch =⇒ steady-state error because of the
wrong CoM estimate
A simple integral action can counteract this effect resulting a zero
steady-state error
˙
θ −θ
rC,x
ˆ
= −krC d
,
˙
φd − φ
rC,y
ˆ
krC > 0
As a byproduct, in absence of moment disturbance, the estimates
(ˆC,x , rC,y ) are driven towards the real CoM offsets (rC,x , rC,y )
r
ˆ
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
15. Stability analysis
˜
ˆ
Altitude controller: let γ = γ − γ and consider the Lyapunov function
˜
V (sz , γ ) =
m 2 1 T
˜
˜
s + γ K γ,z γ
2 z 2
Along the system trajectories
˙
˙
˙
˜
˜
z
z
˜
ˆ
V (sz , γ ) = sz m¨d − m¨ + mλz z − γ T K γ,z γ
˙
˜
= sz (φz γ − cos φ cos θZ) − γ T K γ,z γ = −kvz s2 ≤ 0
ˆ
z
State trajectories are bounded
Asymptotic stability can be further proven by resorting to Barbalat’s
Lemma as in classical adaptive control schemes
Similar machinery for the horizontal controller case
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
16. Experimental results
Experiments run at the Max Planck Institute of T¨bingen, Germany
u
case
a)
b)
c)
d)
additional
weight
Antonelli Cataldi Robuffo Chiaverini Franchi
weight
no
no
yes
yes
gain
λz
kvz
kγ,z
λxy
kv,xy
kγ,xy
kv,ϕθψ
kv,ϕθψ
krC
a/c
3
5.5
0
3
3
0
1
1
0
Tokyo, 5 November 2013
adaptive
no
yes
no
yes
b/d
3
5.5
1.5
3
3
1
1
1
.1
18. Experimental results
Norm of the 3D position errors for the cases a) (green) and b) (blue)
(no weight)
0.35
η 1,d − η 1 [m]
0.3
0.25
0.2
0.15
0.1
0.05
0
0
20
40
60
80
time [s]
Antonelli Cataldi Robuffo Chiaverini Franchi
100
120
140
Tokyo, 5 November 2013
19. Experimental results
Norm of the 3D position errors for the cases c) (green) and d) (blue)
(weight)
0.35
η 1,d − η 1 [m]
0.3
0.25
0.2
0.15
0.1
0.05
0
0
20
40
60
80
time [s]
Antonelli Cataldi Robuffo Chiaverini Franchi
100
120
140
Tokyo, 5 November 2013
20. Experimental results
Roll (top) and pitch (bottom) angles for cases c) (green) and d) (blue)
ϕ [deg]
2
0
−2
−4
0
20
40
20
40
60
80
100
120
140
60
80
100
120
140
time [s]
θ [deg]
10
5
0
−5
0
time [s]
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013
21. Experimental results
N [Nm] M [Nm] K [Nm]
Z [N]
Control forces for the cases c) (green) and d) (blue)
−14
−16
0
20
40
60
80
100
120
140
0
0
20
40
60
80
100
120
140
0.2
0
−0.2
−0.4
0
20
40
60
80
100
120
140
0.01
0
−0.01
−0.02
−0.03
0
20
40
60
80
100
120
140
time [s]
0.5
Antonelli Cataldi Robuffo Chiaverini Franchi
time [s]
time [s]
time [s]
Tokyo, 5 November 2013
22. Experimental results
ˆ
r C [m]
ˆ
γ xy [N]
γz [N]
ˆ
Time history of the parameters estimates for the case d). Top:
parameter γz , center: parameter γ xy , bottom: parameter r C .
−14
−16
−18
0
20
40
20
40
20
40
60
80
100
120
140
60
80
100
120
140
60
80
100
120
140
time [s]
1
0
−1
0
time [s]
0.05
0
−0.05
0
Antonelli Cataldi Robuffo Chiaverini Franchi
time [s]
Tokyo, 5 November 2013
23. Experimental validation of a new adaptive
control scheme for quadrotors MAVs
Gianluca Antonelli† , Elisabetta Cataldi† ,
Paolo Robuffo Giordano⊕ , Stefano Chiaverini† , Antonio Franchi≀
† University
of Cassino and Southern Lazio, Italy
http://webuser.unicas.it/lai/robotica
⊕ CNRS at IRISA and Inria Bretagne Atlantique, France
http://www.irisa.fr/lagadic
≀ Max Planck Institute for Biol. Cybernetics, Germany
http://www.kyb.mpg.de/research/dep/bu/hri/
IROS 2013
Antonelli Cataldi Robuffo Chiaverini Franchi
Tokyo, 5 November 2013