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Hybrid Control System Verification Tools

 

In theory, the approaches to hybrid controller design discussed in the previous section guarantee that the requirements specification is satisfied by design. In practice, system complexity often limits the applicability of automatic controller synthesis methods, and currently, a common approach to the design of hybrid controllers involves independently coming up with a reasonable design for both the discrete and continuous parts. The combined hybrid controller is then put together by means of interfaces, and verification is carried out to ensure that it satisfies certain properties. Typically, some design errors are found, and the verification attempt supplies the design engineer with diagnostic information that is helpful for reformulating the design. The process of simulation, verification attempts, and redesign is iterated until a successful design is obtained.

This approach has been motivated by the success of verification techniques for finite-state systems. Verification tools for finite state machines have been in use for years (SPIN [10], SMV [12], COSPAN [13], VIS) and proven successful for the automatic analysis of discrete problems such as communication protocols and digital circuits. The push towards stronger verification techniques has been in the direction of extending the standard finite state machine results to incorporate progressively more complicated continuous dynamics. The first extension has been for systems with clocks [14, 15]. Verification tools for finite state machines with clocks have been implemented (KRONOS [16], UPPAAL [17], and Timed COSPAN [28]) and used successfully for the automatic analysis of real-time hardware, and software [19]. The possible values of clocks range over the real numbers. Hence the state space of real-time systems is infinite and automatic verification must proceed symbolically, by representing sets of states using symbolic constraints (instead of state enumeration). Symbolic state space analysis techniques have been extended from real-valued clock variables to all real-valued variables whose trajectories can be characterized using piecewise-linear envelopes [20]. If the guarded assignments and invariants of hybrid automata are linear constraints on continuous states, and the differential equations are replaced by linear constraints on first derivatives, then we obtain the class of linear hybrid automata, which can be analyzed fully automatically. A typical linear constraint on first derivatives is a rectangular differential inclusion tex2html_wrap_inline1125 , which can be used to model, for example, time measured by clocks with bounded drift, or distance covered by vehicles with bounded speed. The only computer package capable of dealing with the full class of linear hybrid automata, HYTECH, is under development by one of our team members [21].

For hybrid automata, verification or design for verification is a complex problem. In work in our group, we have produced interesting new approaches involving the use of game theory and differential inclusions. However, it is fair to say that the approaches have the following difficulties:

  1. The model checking approaches of theoretical computer science, which are algorithmic grow in computational complexity very rapidly, with the end result that problems are undecidable in all but the simplest classes of hybrid systems: referred to as linear hybrid automata.
  2. Deductive approaches involving ``theorem proving'' techniques are ad-hoc and require considerable inspiration for deriving invariants associated with these methods.
  3. The synthesis approach, which we have pioneered solves the problem of checking, but deriving ``pre-verified'' hybrid systems. However, it is based on a game and hence is verified to be ``worst case'' safe.

next up previous
Next: Architectures for Decentralized Control Up: Current Methods and Tools Previous: Hybrid Control System Synthesis

S Sastry
Sun Aug 9 11:27:47 PDT 1998