ACTC Developed Software Packages and Toolboxes

The ACTC produces it's own software packages, with the aim of providing intuitive user friendly tools for many of the common controller designs, reducing the engineering effort required for such tasks. Comprehensive manuals and examples are provided and complementary training courses often exist.

This page contains a list of Software Packages produced by the ACTC. These are available to ACTC members free of charge.

Some of these are now available on-line (ACTC Members only) from our Download Centre, or simply click on the appropriate "Download Now" link.

Standalone Packages
PROBE - Control Loop Benchmarking and Performance Assessment Software

PROBE is the ACTC's own control loop benchmarking tool, which was launched in February 2003. PROBE allows the performance of control loops to be compared against a number of benchmarks, including the well known Minimum Variance (MV) benchmark, using standard operating data. The more advanced benchmarks do require some knowledge of the process under control, though for MV only the loop dead-time is required.

Control loop benchmarking using PROBE is a three stage process; firstly standard loop operating data is collected, this is then imported into PROBE which calculates a % performance relative to a theoretical best controller. This allows any poorly performing loops to be readily identified. The vital final step involves taking appropriate corrective action (e.g. re-tuning, correcting a faulty sensor or actuator, or eliminating a disturbance).

The current version of PROBE operates standalone (i.e. does not require any other packages) and runs in a MS-Windows environment.

The software is available on a CD-ROM, which includes a 45-day evaluation license. For ACTC members licenses are free-of-charge, but are tied to the duration of membership. Please contact us for a copy of the CD-ROM or a new activation code.

MATRIXX Toolboxes
4 DoF Non-linear Ship Modelling Package for MATRIXX

This toolbox has been developed by the ACTC for the Marine SIG and consists of a 4DoF non-linear dynamic ship model built using SystemBuild. The present model is for a high speed container ship, though other ship models and additional features will be developed in the future to create a truly useful and generic model.

MATLAB/Simulink Toolboxes
6 DoF Non-linear Ship Modelling Package

This Matlab/Simulink based toolbox extends the functionality of the 4DoF package to provide more ship models, including underwater vehicles, and the full six degrees of freedom systems. Propulsion systems, weapons systems and environmental models can all be easily incorporated into the vehicle models.

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EASY_KIT Toolbox

EASY_KIT is an integrated graphical front end for MATLAB that allows engineers in industry to design robust controllers (PID, LQG, H2 and H∞) without the need for in-depth expertise of the various MATLAB control toolboxes and associated theory. The package integrates all the general stages of control design, including plant model specification, weighting function tuning, frequency and time responses and linear or non-linear simulations. A worked example looks at the dynamic ship positioning problem and an on-line tour guide of the package is included.

Genetic Algorithms for System Identification Toolbox

This software accompanies the ACTC Case Study Report "Genetic Algorithms for System Identification" (CS20/2000), and it should be used in conjunction with the Case Study report. The software is written for MATLAB. SIMULINK is only required to generate test data and to run the demonstrations.

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Model Based Predictive Control Toolbox for Matlab

Version 1.2 now available - compatible with Matlab R12.1 and R13.

The Model-Based Predictive Control (MBPC) Toolbox for MATLAB is an integrated graphical environment which allows engineers to design and test predictive control algorithms without detailed knowledge of the subject. This allows predictive controllers to tried on system simulations very quickly, removing the design burden from the engineer.

The Toolbox uses a step by step process to allow the user to synthesise a predictive controller. The fixed inputs and desired outputs of the system are specified before simulation. The package automatically generates Kalman filter settings and predictive controller parameters which stabilise the system. Finally, a simulation of the system incorporating the designed predictive controller can be used to evaluate performance.

The package includes the following features:

  • Controller designs for both unconstrained and dynamically constrained operation
  • Static optimisation
  • State-space framework, useful for large systems
  • Standard GPC and the new LQGPC algorithms, which provides improved robustness
  • Reference, disturbance and measurement noise models
  • A full nonlinear gas turbine model for demonstration purposes

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Self-Tuning Control Software

This linear identification and control design tool for MS-DOS uses Recursive Least Squares algorithms (Peterka's square root filtering or Bierman's UD factorisation) to identify a discrete plant model. Controllers can be specified as open loop, fixed gain PID, self-tuning PID, self-tuning LQG, self-tuning H∞ or self-tuning generalised predictive control (GPC). The ability to interface to a real plant via a serial communications link is included, and is specifically set-up for a Turnbull TCS controller. This can be re-programmed by the user for use with other systems.

Nonlinear Self-Tuning Control Software

This is an extension of the above Linear Self-tuning Control Software package, where the identification and plant can now include nonlinear elements. A Recursive Extended Nonlinear Least Squares algorithms (using Bierman's UD factorisation) is used to identify the discrete plant model and the same controllers as provided in the Linear Self-Tuning package are available. The ability to interface to a real plant via the serial link still exists. The improved user interface now works under MS-Windows.

Robust H2 Feedback/Feedforward Control Design Toolbox (Polynomial Approach)

This toolbox complements the MATLAB Robust Control Toolbox by implementing robust controller designs, either H2, H∞ or mixed H2/H∞, using the polynomial approach. An interactive menu allows the user to enter plant models, gains and weightings associated with the controller. Both frequency and time domain analysis of open loop and closed loop systems may be performed. Includes four design examples and an on-line tour guide of the package.

Robust Control Toolbox

This MATLAB toolbox is intended for solving some frequently encountered scalar LQG and H∞ control problems, both in continuous and discrete time. Generalised or mixed sensitivity H∞ controllers or standard or generalised LQG controllers can be specified, coupled with appropriate filter elements for the weightings. Both frequency and time domain analysis of closed loop systems are available.

Multivariable Robust Control Toolbox

This MATLAB based package is used to design and test optimal multivariable robust controllers and acts as a Graphical User Interface extending the MATLAB Robust Control Toolbox. Both LQG and H∞ controllers can be designed using either the state-space approach (using the Robust Control Toolbox) or the polynomial approach (internal to the MRC Toolbox). The analysis can be in either frequency or time domain.

Note: This toolbox operates in the OpenWindows or X-Windows environments running on a Sun workstation.