Robert E. Skelton

Mohamed Khaled, Srivignesh Srinivasan, Alkassoum Toure et al.

Drilling and Extraction Automated System (DREAMS) is a fully automated prototype-drilling rig that can drill, extract water and assess subsurface density profiles from simulated lunar and Martian subsurface ice. DREAMS system is developed by the Texas A&M drilling automation team and composed of four main components: 1- tensegrity rig structure, 2- drilling system, 3- water extracting and heating system, and 4- electronic hardware, controls, and machine algorithm. The vertical and rotational movements are controlled by using an Acme rod, stepper, and rotary motor. DREAMS is a unique system and different from other systems presented before in the NASA Rascal-Al competition because 1- It uses the tensegrity structure concept to decrease the system weight, improve mobility, and easier installation in space. 2- It cuts rock layers by using a short bit length connected to drill pipes. This drilling methodology is expected to drill hundreds and thousands of meters below the moon and Martian surfaces without any anticipated problems (not only 1 m.). 3- Drilling, heating, and extraction systems are integrated into one system that can work simultaneously or individually to save time and cost.

Raman Goyal, Manoranjan Majji, Robert E. Skelton

This paper proposes a model-based approach to control the shape of a tensegrity system by driving its node position locations. The nonlinear dynamics of the tensegrity system is used to regulate position, velocity, and acceleration to the specified reference trajectory. State feedback control design is used to obtain the solution for the control variable as a linear programming problem. Shape control for the gyroscopic tensegrity systems is discussed, and it is observed that these systems increase the reachable space for the structure by providing independent control over certain rotational degrees of freedom. Disturbance rejection of the tensegrity system is further studied in the paper. A methodology to calculate the control gains to bound the errors for five different types of problems is provided. The formulation uses a Linear Matrix Inequality (LMI) approach to stipulate the desired performance bounds on the error for $\mathcal{H}_\infty$, generalized $\mathcal{H}_2$, LQR, covariance control and stabilizing control problem. A high degree of freedom tensegrity $T_2D_1$ robotic arm is used as an example to show the efficacy of the formulation.

Yuling Shen, Muhao Chen, Manoranjan Majji et al.

This letter presents a data-based control design for reference tracking applications. This design finds the optimal control sequence, which minimizes a quadratic cost function consisting of tracking error and input increments over a finite interval [0,N]. The only information needed is the first N+1 Markov parameters of the system. This design is employed on a tensegrity morphing airfoil whose topology has been described in detail in this letter. A NACA 2412 airfoil with specified morphing targets is chosen to verify the developed design. The principle developed in this letter is also applicable to other structural control problems.