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MotionSolve User Guide
MotionSolve is a system level, multibody solver that is based on the principles of mechanics.
MotionSolve Optimization Guide
Introduction
The MotionSolve Optimization Guide explains the design sensitivity and optimization capabilities in MotionSolve.
The Relationship Between the Optimization Toolkit and MotionSolve
This section summarizes the structure of the software that is provided for optimization.

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What's New
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Overview
MotionSolve^® is an integrated solution to analyze, evaluate, and optimize the performance of multibody systems.
Tutorials
Discover MotionSolve functionality with interactive tutorials.
MotionSolve User Guide
MotionSolve is a system level, multibody solver that is based on the principles of mechanics.
- Introduction to MotionSolve
- Platform Support, Recommended Hardware, and Licensing
- Run MotionSolve
- Model Systems
- Model Simulations
- Visualize Results - Animation and Request Plots
- Couple MotionSolve with Other Software
- Customization Capabilities
- Analysis Tips
- NLFE Bodies Introduction
- User Subroutines in MotionSolve
- msolve API
- MotionSolve Verification Manual
- MotionSolve Optimization Guide
  - Introduction
    The MotionSolve Optimization Guide explains the design sensitivity and optimization capabilities in MotionSolve.
    - The Relationship Between the Optimization Toolkit and MotionSolve
      This section summarizes the structure of the software that is provided for optimization.
  - Optimization Capabilities in MotionSolve
    Optimization capabilities in MotionSolve include equations of motion for a multibody system, design variables and limits, and analysis support.
  - Application Areas
    Optimization is a vast area that has a many applications in diverse areas such as engineering, economics, business and medicine.
  - Optimization Input Data
    The input data for an optimization is organized in a python parametric model class with methods that operate on the class.
  - Optimization Output Data
    Every optimization run generates a variety of files.
  - Advanced Topics
    Advanced topics include a scaling optimization problem and tips on how to debug optimization runs.
  - SLA Suspension Example
    This example, referred to as MV3010 in this section, describes the optimization of an SLA suspension and is also available in MotionSolve tutorial topics/solvers/ms/optimization_using_mv_hs_intro_r.html.
  - PID Controller Example
    In this example, we are designing a PID controller whose job is to minimize the effects of a disturbance force on the position, velocity, and acceleration of a block.
  - Glossary
- MotionSolve Environment Variables
- References
MotionSolve Reference Guide
This manual provides a detailed list and usage information regarding command statements, model statements, functions and the Subroutine Interface available in MotionSolve.

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The Relationship Between the Optimization Toolkit and MotionSolve

This section summarizes the structure of the software that is provided for optimization.

In MotionView, an Optimization Wizard guides you through a step-by-step process for defining optimization problems.
Parametric models are typically built in MotionView. These models are exported in a format that the MotionSolve Optimization Application can understand.
The Optimization Application is a layer of Python code that relies on the MSOLVE API to communicate with MotionSolve. Optimization specific capabilities are embedded in this layer.
The Optimization Application also requires the specification of an optimization problem. This manual will show you how to specify optimization problems with several examples.
The core optimization capabilities in the Optimization Application are obtained from the SCIPY package, scipy.optimize.minimize
The optimizer performs several MotionSolve simulations. Data for each simulation is stored in a separate directory.

This is illustrated in the figure below:

Figure 1.

Two examples are extensively discussed in this manual.

Path optimization for a 4-bar mechanism
Suspension camber vs. ride height curve optimization