But by using our new Solid-Tune™ Intonation system, an Auto-Tune for Guitar equipped guitar constantly monitors the precise pitch of each individual string and makes any corrections necessary to ensure that every note of every chord and riff is always in tune. Apr 01, 2018 About Geekazine: A consumer tech, enterprise tech, music tech, and auto tech channel with Geek flare. I attend major events such as CES, SXSW, and more. I teach people to podcast, videocast,. Any musician knows that keeping your guitar or any other instrument in tune is crucial to your music performance. Chris Adams knows how crucial this is and out of frustration, and a decade of hard work, he came up with the Tronical Guitar Auto-Tuning System.It does exactly what Chris sought out to do – seamlessly self-tune your guitar in seconds, all while preserving the integrity and tone. I am a slide and open tuning specialized guitarist and I use to carry 3 or 4 guitars with me for a gig, so I always been interested in robot technology or auto tuning systems and I am agree with you that the Gibson robot guitar gives to the player a more correct vibe because it really changes the guitar tune; an open E is an open E! Nov 08, 2014 Gibson's new auto-tuning system, G FORCE, is now available on a range of 2015 guitars. Gibson G Force Tuning System Overview YouTube. Guitar Headstock Rant - Why Les Pauls Don't Stay in Tune! In control theory a self-tuning system is capable of optimizing its own internal running parameters in order to maximize or minimize the fulfilment of an objective function; typically the maximization of efficiency or error minimization. Self-tuning and auto-tuning often refer to the same concept. Roadie tuners are fully automated string instrument tuners that are quick, easy to use and three times more accurate than the human ear. They combine advanced audio algorithms with machine precision to deliver perfect tuning every time.

The Gibson Robot Guitar (a.k.a. GOR) is a limited-edition self-tuning Gibson guitar, typically a Les Paul.^[1][2] The first run of limited edition Robot Guitars was exclusively made up of Les Paul bodies.^[3] Five different Gibson models were available (2008-2011, Robot X-plorer 2008-2012)) with Robot Guitar features: The Robot Les Paul Studio,^[4] Robot SG,^[5] Robot Flying V, Robot X-plorer, and a Robot Les Paul Junior. Developed by Chris Adams, its most notable feature is that it uses an onboard computer to automatically tune itself. This is not the first guitar to be able to tune itself,^[6] but it is regarded as the most modern, unique, and non-invasive self-tuning model available, because it does not employ cams or cantilevers throughout the body of the guitar.^[7] The non-limited edition SG and Les Paul Studio are available in a variety of finishes. The Flying V and Explorer are only available in metallic red. The price can range from about $1,000-$3,000 or more for custom options. In the case of the 'Original 1st Production' Robot guitar the only finish available was Blue Silverburst nitrocellulose, a color which Gibson has stated will never be used on any other Gibson guitar (see photo to the right). The original Robot guitar also featured headstock and neck binding which are not standard on any current Les Paul Robot as well as a chrome truss rod cover with 'Robot Guitar' engraved. The production version featured 22-fret rosewood-bound (standard finishes) or white-bound (metallic finishes) ebony fingerboard with figured acrylic trapezoid inlays, white-bound headstock with MOP Gibson logo and flowerpot inlay (metallic finishes) or unbound headstock with screened logo (standard finishes), three-per-side robotic Powerhead Locking tuners, tune-o-matic Powertune bridge, Powertune stop tailpiece, two chrome covered humbucker pickups (490R, 498T), four knobs (three normal, and one Master Control Knob that controls the robotic actions of the guitar), three-way pickup switch, Neutrik jack on side of guitar, chrome hardware.

Technical information[edit]

The tuning system used on the Gibson Robot Guitar is based on the aftermarket Powertune system, which was developed by the Tronical Company of Germany.^[2] The Gibson system uses the standard Tune-o-matic style bridge typical on their guitars, but modifications were made to have individual piezo saddles that transmit each string's pitch to the microprocessor.^[7] Wayne gisslen professional cooking 7th edition free download. The computer analyzes the signal, and then controls each of the Powerhead Locking Tuners. Each tuner is run by a small servo motor that works in sync with the bridge to bring the string up to pitch by altering the string's tension until it is within a desired tolerance.^[2] The entire system is powered by a nickel metal hydride rechargeable battery pack housed in the control cavity of the guitar.^[8]

Features and functionality[edit]

The Robot Guitar appears to have the standard four knobs for individual pickup volume and tone controls; however, in place of the bridge pickup tone knob, there is the Master Control Knob (MCK).^[8] The control functions like a “push-pull” knob: when in the down position, it functions like a standard control. When in the up position, however, the MCK is what coordinates the automatic tuning for the guitar by sending the information and power to the neck PCB through the strings. Then the PCB activates the robot tuners by contact.^[8]

Users can choose from seven factory presets for tunings, six of which are editable.^[7] Each tuning can be returned to 'standard' tuning of A (440 Hz) by simply pulling up on the MCK knob, and strumming the strings lightly.

Similar systems[edit]

While Gibson advertised the guitar in America as a 'world first,'^[9] similar systems developed by Transperformance have been in use for decades. Jimmy Page currently uses a Les Paul Goldtop with the Transperformance system in it. This system is also endorsed by Graham Nash as well as Ed Roland.^[10] The drawback to the Transperformance system is that it requires heavy modification to the instrument, including routing and installing multiple cams and cantilevers.^[11]

References[edit]

1. ^Reader, Ruth (29 January 2008). 'Gibson Guitar Releases New Self-Tuning Guitar'. VOA News. Voice of America. Archived from the original on April 15, 2009. Retrieved 2 January 2009.
2. ^ ^abcGibson Robot Guitar
3. ^Limited Edition First RunArchived 2009-02-20 at the Wayback Machine
4. ^'Robot Les Paul Studio'. Archived from the original on 2008-04-23. Retrieved 2008-03-30.
5. ^'Robot SG'. Archived from the original on 2008-04-11. Retrieved 2008-03-30.
6. ^Transperformance Archived 2008-07-04 at the Wayback Machine
7. ^ ^abcBlackett, Matt. 'Gibson Robot Guitar.' Guitar Player, February 2008
8. ^ ^abcGibson Guitar Corporation
9. ^The Gibson Robot Guitar is Coming! - gibson.com 2007-11-07
10. ^'Tronical. Tronical Artists (15 March 2008)'. Archived from the original on 20 February 2008. Retrieved 25 March 2008.
11. ^Gizmag. The Transperformance self-tuning guitar. (15 March 2008)

External links[edit]

In control theory a self-tuning system is capable of optimizing its own internal running parameters in order to maximize or minimize the fulfilment of an objective function; typically the maximization of efficiency or error minimization.

Self-tuning and auto-tuning often refer to the same concept. Many software research groups consider auto-tuning the proper nomenclature.

Self-tuning systems typically exhibit non-linearadaptive control. Self-tuning systems have been a hallmark of the aerospace industry for decades, as this sort of feedback is necessary to generate optimal multi-variable control for non-linear processes. In the telecommunications industry, adaptive communications are often used to dynamically modify operational system parameters to maximize efficiency and robustness.

Examples[edit]

Examples of self-tuning systems in computing include:

• TCP (Transmission Control Protocol)
• Microsoft SQL Server (Newer implementations only)
• FFTW (Fastest Fourier Transform in the West)
• ATLAS (Automatically Tuned Linear Algebra Software)
• libtune (Tunables library for Linux)
• PhiPAC (Self Tuning Linear Algebra Software for RISC)
• MILEPOST GCC (Machine learning based self-tuning compiler)

Performance benefits can be substantial. Professor Jack Dongarra, an American computer scientist, claims self-tuning boosts performance, often on the order of 300%^[1].

Digital self-tuning controllers are an example of self-tuning systems at the hardware level.

Architecture[edit]

Self-tuning systems are typically composed of four components: expectations, measurement, analysis, and actions. The expectations describe how the system should behave given exogenous conditions.

Measurements gather data about the conditions and behaviour. Analysis helps determine whether the expectations are being met- and which subsequent actions should be performed. Common actions are gathering more data and performing dynamic reconfiguration of the system.

Self-tuning (self-adapting) systems of automatic control are systems whereby adaptation to randomly changing conditions is performed by means of automatically changing parameters or via automatically determining their optimum configuration ^[2]. In any non-self-tuning automatic control system there are parameters which have an influence on system stability and control quality and which can be tuned. If these parameters remain constant whilst operating conditions (such as input signals or different characteristics of controlled objects) are substantially varying, control can degrade or even become unstable. Manual tuning is often cumbersome and sometimes impossible. In such cases, not only is using self-tuning systems technically and economically worthwhile, but it could be the only means of robust control. Self-tuning systems can be with or without parameter determination.

In systems with parameter determination the required level of control quality is achieved by automatically searching for an optimum (in some sense) set of parameter values. Control quality is described by a generalised characteristic which is usually a complex and not completely known or stable function of the primary parameters. This characteristic is either measured directly or computed based on the primary parameter values. The parameters are then tentatively varied. An analysis of the control quality characteristic oscillations caused by the varying of the parameters makes it possible to figure out if the parameters have optimum values, i.e. if those values deliver extreme (minimum or maximum) values of the control quality characteristic. If the characteristic values deviate from an extremum, the parameters need to be varied until optimum values are found. Self-tuning systems with parameter determination can reliably operate in environments characterised by wide variations of exogenous conditions.

In practice systems with parameter determination require considerable time to find an optimum tuning, i.e. time necessary for self-tuning in such systems is bounded from below. Self-tuning systems without parameter determination do not have this disadvantage. In such systems, some characteristic of control quality is used (e.g., the first time derivative of a controlled parameter). Automatic tuning makes sure that this characteristic is kept within given bounds. Different self-tuning systems without parameter determination exist that are based on controlling transitional processes, frequency characteristics, etc. All of those are examples of closed-circuit self-tuning systems, whereby parameters are automatically corrected every time the quality characteristic value falls outside the allowable bounds. In contrast, open-circuit self-tuning systems are systems with para-metrical compensation, whereby input signal itself is controlled and system parameters are changed according to a specified procedure. This type of self-tuning can be close to instantaneous. However, in order to realise such self-tuning one needs to control the environment in which the system operates and a good enough understanding of how the environment influences the controlled system is required.

In practice self-tuning is done through the use of specialised hardware or adaptive software algorithms. Giving software the ability to self-tune (adapt):

1. Facilitates controlling critical processes of systems;
2. Approaches optimum operation regimes;
3. Facilitates design unification of control systems;
4. Shortens the lead times of system testing and tuning;
5. Lowers the criticality of technological requirements on control systems by making the systems more robust;
6. Saves personnel time for system tuning.

Gibson Auto Tuning Guitar

Literature[edit]

1. ^http://appliedmathematician.org/pdf/news/781.pdf Faster than a Speeding Algorithm
2. ^http://bse.sci-lib.com/article099233.html Big Soviet Encyclopedia, Self-Tuning Systems (in Russian)

Auto Tuning Guitar System Review

External links[edit]

• Frigo, M. and Johnson, S. G., 'The design and implementation of FFTW3', Proceedings of the IEEE, 93(2), February 2005, 216 - 231. doi:10.1109/JPROC.2004.840301.

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