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@ -5,10 +5,10 @@ draft = true
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Tags
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: [Multivariable Control](multivariable_control.md)
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: [Multivariable Control]({{< relref "multivariable_control" >}})
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Reference
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: ([Albertos and Antonio 2004](#org22a156f))
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: ([Albertos and Antonio 2004](#orga1617be))
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Author(s)
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: Albertos, P., & Antonio, S.
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@ -17,14 +17,19 @@ Year
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: 2004
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## [Decentralized Control](decentralized_control.md) and Decoupled Control {#decentralized-control--decentralized-control-dot-md--and-decoupled-control}
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## Introduction to Multivariable Control {#introduction-to-multivariable-control}
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Decentralized control is decomposed into two steps:
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1. decoupled the plant into several subsystems
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2. control the subsystems
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## Linear System Representation: Models and Equivalence {#linear-system-representation-models-and-equivalence}
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The initial effort of decoupling the system results in subsequent easier design, implementation and tuning.
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## Linear Systems Analysis {#linear-systems-analysis}
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## Solutions to the Control Problem {#solutions-to-the-control-problem}
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## Decentralised and Decoupled Control {#decentralised-and-decoupled-control}
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### Decoupling {#decoupling}
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@ -32,7 +37,7 @@ The initial effort of decoupling the system results in subsequent easier design,
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In cases when multi-loop control is not effective in reaching the desired specifications, a possible strategy for tackling the MIMO control could be to transform the transfer function matrix into a diagonal dominant one.
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This strategy is called **decoupling**.
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[Decoupled Control](decoupled_control.md) can be achieved in two ways:
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[Decoupled Control]({{< relref "decoupled_control" >}}) can be achieved in two ways:
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- feedforward cancellation of the cross-coupling terms
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- based on state measurements, via a feedback law
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@ -61,7 +66,7 @@ Although at first glance, decoupling seems an appealing idea, there are some dra
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#### SVD Decoupling {#svd-decoupling}
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A matrix \\(M\\) can be expressed, using the [Singular Value Decomposition](singular_value_decomposition.md) as:
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A matrix \\(M\\) can be expressed, using the [Singular Value Decomposition]({{< relref "singular_value_decomposition" >}}) as:
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\begin{equation}
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M = U \Sigma V^T
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@ -72,10 +77,10 @@ where \\(U\\) and \\(V\\) are orthogonal matrices and \\(\Sigma\\) is diagonal.
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The SVD can be used to obtain decoupled equations between linear combinations of sensors and linear combinations of actuators.
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In this way, although losing part of its intuitive sense, a decoupled design can be carried out even for non-square plants.
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If sensors are multiplied by \\(U^T\\) and control actions multiplied by \\(V\\), as in Figure [1](#orgbba6502), then the loop, in the transformed variables, is decoupled, so a diagonal controller \\(K\_D\\) can be used.
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If sensors are multiplied by \\(U^T\\) and control actions multiplied by \\(V\\), as in Figure [1](#orgd447864), then the loop, in the transformed variables, is decoupled, so a diagonal controller \\(K\_D\\) can be used.
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Usually, the sensor and actuator transformations are obtained using the DC gain, or a real approximation of \\(G(j\omega)\\), where \\(\omega\\) is around the desired closed-loop bandwidth.
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<a id="orgbba6502"></a>
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<a id="orgd447864"></a>
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{{< figure src="/ox-hugo/albertos04_svd_decoupling.png" caption="Figure 1: SVD decoupling: \\(K\_D\\) is a diagonal controller designed for \\(\Sigma\\)" >}}
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@ -99,47 +104,29 @@ If some of the vectors in \\(V\\) (input directions) have a significant componen
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## Implementation and Other Issues {#implementation-and-other-issues}
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There are two main categories for the implementation of MIMO control:
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- Decentralized, Decoupled, Cascade
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- Centralized, optimization based
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A fundamental reason to use cascade and decentralized control in most practical applications is because they require less modelling effort.
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Other advantages of cascade and decentralized control are:
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- its behaviour can be easily understood
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- standard equipment can be used (PID controllers, etc.)
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- their decoupled behavior enables easier tuning with model-free strategies
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- decentralized implementation tends to be more fault-tolerant, as individual loops will try to keep their set-points even in the case some other components have failed.
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## Appendices {#appendices}
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### [Anti-Windup Control](anti_windup_control.md) {#anti-windup-control--anti-windup-control-dot-md}
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In practice, it is possible that an actuator saturate.
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In such case, the feedback path is broken, and this has several implications:
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- unstable processes: the process output might go out of control
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- multi-loop and centralized control: even with stable plants, opening a feedback path may cause the overall loop to become unstable
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The wind-up problem can appear with integral action regulators: during significative step changes in the set point, the integral of the error keeps accumulation and when reaching the desired set-point the accumulated integral action produces a significant overshoot increment.
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In SISO PID regulators, anti-windup schemes are implemented by either stopping integration if the actuator is saturated or by implementing the following control law:
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\begin{equation}
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u = K(r - y) - K T\_D \frac{dy}{dt} + \int K T\_i^{-1} (r - y) + T\_t^{-1} (u\_m - u) dt \label{eq:antiwindup\_pid}
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\end{equation}
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where \\(u\\) is the calculated control action and \\(u\_m\\) is the actual control action applied to the plant.
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In non-saturated behaviour, \\(u=u\_m\\) and the equation is the ordinary PID.
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In saturation, \\(u\_m\\) is a constant and the resulting equations drive \\(u\\) down towards \\(u\_m\\) dynamically, with time constant \\(T\_T\\).
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### Summary of SISO System Analysis {#summary-of-siso-system-analysis}
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### [Bumpless Transfer](bumpless_transfer.md) {#bumpless-transfer--bumpless-transfer-dot-md}
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### Matrices {#matrices}
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When switching on the regulator, significant transient behavior can be seen and the controller may saturate the actuators.
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The solution is similar to that of the wind-up phenomenon: the regulator should be always on, carrying out calculations by using \eqref{eq:antiwindup_pid}.
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### Signal and System Norms {#signal-and-system-norms}
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### Optimisation {#optimisation}
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### Multivariable Statistics {#multivariable-statistics}
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### Robust Control Analysis and Synthesis {#robust-control-analysis-and-synthesis}
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## Bibliography {#bibliography}
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<a id="org22a156f"></a>Albertos, P., and S. Antonio. 2004. _Multivariable Control Systems: An Engineering Approach_. Advanced Textbooks in Control and Signal Processing. Springer-Verlag. <https://doi.org/10.1007/b97506>.
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<a id="orga1617be"></a>Albertos, P., and S. Antonio. 2004. _Multivariable Control Systems: An Engineering Approach_. Advanced Textbooks in Control and Signal Processing. Springer-Verlag. <https://doi.org/10.1007/b97506>.
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@ -1,23 +0,0 @@
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+++
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title = "Mastering system identification in 100 exercises"
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author = ["Thomas Dehaeze"]
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draft = false
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+++
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Tags
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:
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Reference
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: ([Schoukens, Pintelon, and Rolain 2012](#org4021f9f))
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Author(s)
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: Schoukens, J., Pintelon, R., & Rolain, Y.
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Year
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: 2012
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## Bibliography {#bibliography}
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<a id="org4021f9f"></a>Schoukens, Johan, Rik Pintelon, and Yves Rolain. 2012. _Mastering System Identification in 100 Exercises_. John Wiley & Sons.
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title = "Decentralized Control"
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author = ["Thomas Dehaeze"]
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draft = false
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+++
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Tags
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:
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Decentralized control is a way to control a MIMO system by individually controlling the inputs and outputs using SISO controllers.
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@ -36,37 +36,37 @@ Tags
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Papers by J.E. McInroy:
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- ([O’Brien et al. 1998](#org320ae46))
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- ([McInroy, O’Brien, and Neat 1999](#orgea92441))
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- ([McInroy 1999](#orgfb23e22))
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- ([McInroy and Hamann 2000](#org90e178e))
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- ([Chen and McInroy 2000](#org418808c))
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- ([McInroy 2002](#orgaa607f0))
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- ([Li, Hamann, and McInroy 2001](#org7176257))
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- ([Lin and McInroy 2003](#org6427256))
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- ([Jafari and McInroy 2003](#orga8add64))
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- ([Chen and McInroy 2004](#org3f36881))
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- ([O’Brien et al. 1998](#orgf349082))
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- ([McInroy, O’Brien, and Neat 1999](#org5767dd1))
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- ([McInroy 1999](#org2c21b8d))
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- ([McInroy and Hamann 2000](#org4297441))
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- ([Chen and McInroy 2000](#org8bb7a6a))
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- ([McInroy 2002](#org9b28444))
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- ([Li, Hamann, and McInroy 2001](#orgf3f89be))
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- ([Lin and McInroy 2003](#org950f17b))
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- ([Jafari and McInroy 2003](#orge2968a9))
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- ([Chen and McInroy 2004](#org5ac50ad))
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## Bibliography {#bibliography}
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<a id="org3f36881"></a>Chen, Y., and J.E. McInroy. 2004. “Decoupled Control of Flexure-Jointed Hexapods Using Estimated Joint-Space Mass-Inertia Matrix.” _IEEE Transactions on Control Systems Technology_ 12 (3):413–21. <https://doi.org/10.1109/tcst.2004.824339>.
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<a id="org5ac50ad"></a>Chen, Y., and J.E. McInroy. 2004. “Decoupled Control of Flexure-Jointed Hexapods Using Estimated Joint-Space Mass-Inertia Matrix.” _IEEE Transactions on Control Systems Technology_ 12 (3):413–21. <https://doi.org/10.1109/tcst.2004.824339>.
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<a id="org418808c"></a>Chen, Yixin, and J.E. McInroy. 2000. “Identification and Decoupling Control of Flexure Jointed Hexapods.” In _Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)_, nil. <https://doi.org/10.1109/robot.2000.844878>.
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<a id="org8bb7a6a"></a>Chen, Yixin, and J.E. McInroy. 2000. “Identification and Decoupling Control of Flexure Jointed Hexapods.” In _Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)_, nil. <https://doi.org/10.1109/robot.2000.844878>.
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<a id="orga8add64"></a>Jafari, F., and J.E. McInroy. 2003. “Orthogonal Gough-Stewart Platforms for Micromanipulation.” _IEEE Transactions on Robotics and Automation_ 19 (4). Institute of Electrical and Electronics Engineers (IEEE):595–603. <https://doi.org/10.1109/tra.2003.814506>.
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<a id="orge2968a9"></a>Jafari, F., and J.E. McInroy. 2003. “Orthogonal Gough-Stewart Platforms for Micromanipulation.” _IEEE Transactions on Robotics and Automation_ 19 (4). Institute of Electrical and Electronics Engineers (IEEE):595–603. <https://doi.org/10.1109/tra.2003.814506>.
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<a id="org6427256"></a>Lin, Haomin, and J.E. McInroy. 2003. “Adaptive Sinusoidal Disturbance Cancellation for Precise Pointing of Stewart Platforms.” _IEEE Transactions on Control Systems Technology_ 11 (2):267–72. <https://doi.org/10.1109/tcst.2003.809248>.
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<a id="org950f17b"></a>Lin, Haomin, and J.E. McInroy. 2003. “Adaptive Sinusoidal Disturbance Cancellation for Precise Pointing of Stewart Platforms.” _IEEE Transactions on Control Systems Technology_ 11 (2):267–72. <https://doi.org/10.1109/tcst.2003.809248>.
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<a id="org7176257"></a>Li, Xiaochun, Jerry C. Hamann, and John E. McInroy. 2001. “Simultaneous Vibration Isolation and Pointing Control of Flexure Jointed Hexapods.” In _Smart Structures and Materials 2001: Smart Structures and Integrated Systems_, nil. <https://doi.org/10.1117/12.436521>.
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<a id="orgf3f89be"></a>Li, Xiaochun, Jerry C. Hamann, and John E. McInroy. 2001. “Simultaneous Vibration Isolation and Pointing Control of Flexure Jointed Hexapods.” In _Smart Structures and Materials 2001: Smart Structures and Integrated Systems_, nil. <https://doi.org/10.1117/12.436521>.
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<a id="orgfb23e22"></a>McInroy, J.E. 1999. “Dynamic Modeling of Flexure Jointed Hexapods for Control Purposes.” In _Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328)_, nil. <https://doi.org/10.1109/cca.1999.806694>.
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<a id="org2c21b8d"></a>McInroy, J.E. 1999. “Dynamic Modeling of Flexure Jointed Hexapods for Control Purposes.” In _Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328)_, nil. <https://doi.org/10.1109/cca.1999.806694>.
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<a id="orgaa607f0"></a>———. 2002. “Modeling and Design of Flexure Jointed Stewart Platforms for Control Purposes.” _IEEE/ASME Transactions on Mechatronics_ 7 (1):95–99. <https://doi.org/10.1109/3516.990892>.
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<a id="org9b28444"></a>———. 2002. “Modeling and Design of Flexure Jointed Stewart Platforms for Control Purposes.” _IEEE/ASME Transactions on Mechatronics_ 7 (1):95–99. <https://doi.org/10.1109/3516.990892>.
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<a id="org90e178e"></a>McInroy, J.E., and J.C. Hamann. 2000. “Design and Control of Flexure Jointed Hexapods.” _IEEE Transactions on Robotics and Automation_ 16 (4):372–81. <https://doi.org/10.1109/70.864229>.
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<a id="org4297441"></a>McInroy, J.E., and J.C. Hamann. 2000. “Design and Control of Flexure Jointed Hexapods.” _IEEE Transactions on Robotics and Automation_ 16 (4):372–81. <https://doi.org/10.1109/70.864229>.
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<a id="orgea92441"></a>McInroy, J.E., J.F. O’Brien, and G.W. Neat. 1999. “Precise, Fault-Tolerant Pointing Using a Stewart Platform.” _IEEE/ASME Transactions on Mechatronics_ 4 (1):91–95. <https://doi.org/10.1109/3516.752089>.
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<a id="org5767dd1"></a>McInroy, J.E., J.F. O’Brien, and G.W. Neat. 1999. “Precise, Fault-Tolerant Pointing Using a Stewart Platform.” _IEEE/ASME Transactions on Mechatronics_ 4 (1):91–95. <https://doi.org/10.1109/3516.752089>.
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<a id="org320ae46"></a>O’Brien, J.F., J.E. McInroy, D. Bodtke, M. Bruch, and J.C. Hamann. 1998. “Lessons Learned in Nonlinear Systems and Flexible Robots through Experiments on a 6 Legged Platform.” In _Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207)_, nil. <https://doi.org/10.1109/acc.1998.703532>.
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<a id="orgf349082"></a>O’Brien, J.F., J.E. McInroy, D. Bodtke, M. Bruch, and J.C. Hamann. 1998. “Lessons Learned in Nonlinear Systems and Flexible Robots Through Experiments on a 6 Legged Platform.” In _Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207)_, nil. <https://doi.org/10.1109/acc.1998.703532>.
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