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How the Stewart Platform Is Modeled Initializing the Stewart Platform Identifying the Simulink and Mechanical States of the Stewart Platform |
This section explains the essential details of modeling the Stewart platform in the SimMechanics environment. To understand the section better, use any top-level model from the case studies of this chapter, except the models of Trimming and Linearizing Through Inverse Dynamics. These are different because they lack a controller subsystem and consist of a plant model alone.
The control design model, mech_stewart_control, is this section's example.
In three of the case studies, a larger control system model contains a Plant subsystem that incorporates the platform.
The Plant subsystem models the Stewart platform's moving parts, the legs and top plate. Open this subsystem.
Stewart Platform Model (Control Design Version)
Each of the legs is an instance of a library block located in another library model, mech_stewartplatform_leg or mech_stewart_control_equil_leg.
Select one of the leg subsystems and right-click. Select Link Options, then Go To Library Block, to open this library.
Open the masked library block, Leg Subsystem, and the individual Body and Joint blocks that make up a whole leg.
Now close the blocks, subsystems, and linked libraries and return to the top-level model.
Except in the Trimming and Linearizing Through Inverse Dynamics study, the Stewart platform models contain controllers imposing actuating forces that guide the platform's motion to follow as closely as possible a nominal or reference trajectory. Implementing a controller requires computing the motion errors, the difference of the reference and actual motions of the platform. All the case study models use proportional-integral-derivative (PID) control.
Each model controller requires a reference trajectory.
Open the Leg Reference Trajectory subsystem.
This set of blocks generates the set of six leg lengths, as functions of time, corresponding to a desired trajectory for the top plate.
Open the subsystem called Top Plate Reference. This set of blocks generates a reference trajectory in terms of linear position and three orientation angles, as a function of time. The workspace variable freq sets the frequency of the reference motion.
Stewart Platform Reference Trajectory Subsystem (Control Design Version)
The reference trajectory provided uses sinusoidal functions of time to define the rotational and translational degrees of freedom.
If you want, you can design and implement another reference trajectory of your choosing and replace this sub-subsystem.
Whatever comes out of Top Plate Reference, the subsystem Leg Reference Trajectory assumes the translational position/three-angle form for the top plate. The rest of the Leg Reference Trajectory subsystem transforms these six degrees of freedom (DoFs) into the equivalent set of six DoFs expressed as the lengths of the six platform legs. The reference trajectory output of the subsystem is a six-vector of these leg lengths.
The actuating force on leg r is a function of the motion error. The error requires finding the instantaneous length of each leg from the positions of that leg's top and bottom connection points.
Defining the Length of a Stewart Platform Leg
The motion error is the difference of the desired or reference length of the leg and its instantaneous or actual length:
The reference length Ltraj(t) is given as a function of time by the output of the Leg Reference Trajectory subsystem. The vectors p, pt,r, and pb,r are defined in the preceding figure. The orthogonal rotation matrix R specifies the orientation of the top plate with respect to the bottom.
All the Stewart platform models use a simple PID controller and Joint Sensor blocks to measure motion. The simplest implementation of trajectory control is to apply forces to the plant proportional to the motion error. PID feedback is a common form of linear control.
A PID control law is a linear combination of a variable detected by a sensor, its time integral, and its first derivative. This Stewart platform's PID controller uses the leg position errors Er and their integrals and velocities. The control law for each leg r has the form:
The controller applies the actuating force Fact,r along the leg.
If Er is positive, the leg is too short, and Fact,r is positive (expansive).
If Er is negative, the leg is too long, and Fact,r is negative (compressive).
If Er is zero, the leg has exactly the desired length, and Fact,r is zero.
The real, nonnegative Kp, Ki, and Kd are, respectively, the proportional, integral, and derivative gains that modulate the feedback sensor signals in the control law:
The first term is proportional to the instantaneous leg position error, or deviation from reference.
The second term is proportional to the integral of the leg position error.
The third term is proportional to the derivative of the leg position error.
The result is Fact,r, the actuator force (input) applied by the controller to the legs. The proportional, integral, and derivative terms tend to make the legs' top attachment points pt,r follow the reference trajectories by suppressing the motion error.
The case study, About Controllers and Plants, discusses controlling platform motion in greater detail. In that study, you also use an H-infinity controller, as well as use transfer functions to take motion derivatives.
In addition, consult References earlier in this chapter.
When representing the physical components of the Stewart platform model with SimMechanics blocks and the control components with Simulink blocks, you must define the geometry of its initial state and the mass parameters of the Stewart platform bodies. Although each case study in this chapter uses a variant model, all initialize the platform and controller configuration in a common way.
Geometric, mass, dynamical, and controller information is specified in the block dialogs by referencing variables in your MATLAB workspace. An M-file script accompanies the Stewart platform models and sets these values.
Running this script configures the blocks in their starting geometric state, with the correct mass properties for the bodies. When you open it, each model uses the same initialization M-file as a pre-load function. To see this setting,
Stewart Platform Initialization M-File
| File | Purpose |
|---|---|
| mech_stewart_studies_setup | M-file script to fill the workspace with geometric, dynamical, and controller data. |
| inertiaCylinder | M-file function called by mech_stewart_studies_setup. Computes the principal inertias of a solid cylinder. |
The script first defines basic angular unit conversions and axes. The World coordinate system (CS) is located at the center of the immobile base plate. The connection points on the base and top plate are defined with respect to World. These definitions include the offset angle of 60 degrees between the base and top plates, the radii of both the base and top plates, the initial position height of the top plate, and the vectors pointing along the legs. The array of top points is permuted so that the same index represents the top and bottom connection points for the same leg.
The script calculates the revolute and cylindrical axes used in the joint blocks of the leg subsystems. There are two revolute axes for each Universal joint that connects an upper leg to the top plate, one cylindrical and one revolute axis for the linear motion of the Cylindrical joint connecting upper and lower legs, and two revolute axes for each Universal block that connects a lower leg to the base plate. The script then configures all 13 moving bodies by defining coordinate systems at the center of gravity (CG) of each.
The top plate's home configuration is symmetric equilibrium: flat, with equal leg lengths specified by the workspace vector leg_length.
The script defines the mass properties of all bodies. These comprise the inertia tensors and masses for the top plate, the bottom plate, and the legs. The mass properties calculation assumes that the platform is made with steel. The script calls the function inertiaCylinder to calculate the inertia tensors and masses of the legs and the top and base plates, given the material density, the length and inner and outer radii of the leg cylinders, and the thicknesses and radii of the top and base plates.
In its final steps, the script defines motion and control constants as workspace variables: motion frequency, derivative filtering cutoff, leg actuator force saturation, and controller gains. Each case study model uses some or all of these constants, which you can change as desired.
Real force actuators are saturate at a specific force level. The Force Saturation block limits the actuating force to the value of the workspace variable force_act_max.
The integral (I) part of the PID controller exhibits an extended response time whose overall effect is controlled by the ratio of Ki to Kp. The Integrator for the I part has a nonzero Initial condition field, specified by the workspace variable initCondI, adjustable to compensate for initial transient behavior. The script initializes its value to
(upper_leg_mass+lower_leg_mass+(top_mass*1.3/6))*9.81/Ki
corresponding to the leg forces in symmetric equilibrium.
Motion and Filtering Constants
| Dynamical Feature | Workspace Variable | Associated Natural Frequency | Associated Time Scale |
|---|---|---|---|
| Top plate motion | freq = π rad/s | freq/2π = 0.5 Hz | 2π/freq = 2 s |
| Filtered derivative cutoff | A = 100*freq = 100π rad/s | A/2π = 50 Hz | 2π/A = 0.02 s |
PID Controller Constants
| Dynamical Constant | Workspace Variable |
|---|---|
| Force saturation | force_act_max = 3e5 newtons (N) |
| Integral (I) gain | Ki = 1e4 (newtons/meter/second) (N/m-s) |
| Proportional (P) gain | Kp = 2e6 newtons/meter (N/m) |
| Derivative (D) gain | Kd = 4.5e4 newtons-seconds/meter (N-s/m) |
For the purposes of SimMechanics motion analysis, you need to know the model's Simulink and mechanical states. These are distinct from the system's degrees of freedom (DoFs) and depend on the analysis mode you choose.
If you use a controller or other subsystem made up of pure Simulink blocks with your Stewart platform, your model might contain Simulink states. For example, Integrator and Transfer Fcn blocks each have an associated state, and State-Space blocks can have many.
The default Stewart platform controller is a PID subsystem, which integrates six feedback signals and thus has six Simulink states. In the Analyzing Controllers and Designing and Improving Controllers studies, you can also choose to use the filtered derivative, which has 12 transfer functions and thus adds 12 Simulink states.
A mechanical system modeled with Joint blocks contains mechanical states distinct from Simulink states that include both joint position and velocity. In Forward Dynamics mode, the Stewart platform contains 52 tree states, of which 12 are independent.
The joints and their related DoFs are discussed in Counting Degrees of Freedom in the Stewart Platform preceding.
Joint Primitives and States. Each Joint consists of one or more primitives. The position and velocity of a joint primitive each have a state. The Stewart platform has 36 joint primitives and thus potentially 72 states.
Cutting Joints and Obtaining the Tree States. Because the Stewart platform has closed topology, SimMechanics model will cut five of the Joints to arrive at an equivalent open-topology or tree machine. These Joints are replaced internally by equivalent cutting constraints.
Five Universals and 5*2*2 = 20 joint primitives are eliminated this way. The equivalent open machine thus has 72 - 20 = 52 tree states.
Counting the Cutting Constraints. Not all these states are independent. There are 40 equivalent constraints that replace the cut Joints.
Each cut Universal imposes one rotational and three position constraints.
Each constraint also constrains the corresponding velocity.
There are five cut Joints.
Thus there are 5*2*4 = 40 invisible constraints generated by the cutting.
Finding the Independent States. Thus the Stewart platform model has 52 - 40 = 12 independent mechanical states, corresponding to the six independent DoFs and their velocities.
You can also analyze the Stewart platform's motion in inverse dynamics and locate steady-state operating points.
Because the Stewart platform is a closed-loop machine, you must simulate its inverse dynamics in the Kinematics mode.
You can find operating points in the Trimming mode with the Simulink trim command.
In both the inverse dynamics and trimming cases, the Simulink states associated with the SimMechanics joint primitives are not the DoFs, but the (invisible) joint-cutting constraints that reduce the tree states to independent states. The state values measure how well the constraints are satisfied. A zero value means a constraint is satisfied perfectly.
In the mechanical part of the Stewart platform model, there are 52 tree states and 12 independent states. Thus the SimMechanics model counts 52 - 12 = 40 cutting constraints. In the Kinematics and Trimming modes, these 40 constraints are the mechanical states.
Open Topology and Inverse Dynamics Mode. If the Stewart platform had an open topology, you would simulate its inverse dynamics in Inverse Dynamics mode instead. However, there would be no closed loops, and the simulation would not cut any Joints. With no cutting constraints, an open topology machine has no states in Inverse Dynamics or Trimming mode.
Learn more about SimMechanics states and loops in the Modeling Mechanical Systems chapter:
Consult the mech_stateVectorMgr command reference as well.
For more about analysis modes, see
Simulating and Analyzing Mechanical Motion in the Introducing SimMechanics Software chapter.
The Analyzing Motion chapter.
To view mechanical animation, consult the SimMechanics Visualization and Import Guide.
With the SimMechanics visualization window open, you can view the platform motion from different perspectives. View the platform in the xy-plane, from above. Then switch the view to the xz- or yz-plane.
The initial state of motion specified by the reference trajectory is slightly different from the home configuration and generates an initial transient.
 | About the Stewart Platform | Trimming and Linearizing Through Inverse Dynamics |  |
Learn more about Simulink through this collection of videos, articles, technical literature and the Getting Started with Simulink Guide.
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